sexism in stem essay

The challenge of gender bias: experiences of women pursuing careers in STEM

A look at the difficulties and biases women in stem careers face written by the freshmen women in science and engineering (wise) llc cohort on the topic of women in stem.

Women pursuing STEM careers have faced many challenges in the past, and they continue to do so today. In the past, many of these challenges were built into the framework of our public and private institutions and our legal system. Women, for example, were not allowed to attend college and earn a college education until 1840, when Catherine Brewer was the first woman to earn a bachelor’s degree. Gaining a graduate degree wasn’t possible until 1849, when Elizabeth Blackwell earned her medical degree (U.S. News, 2009).  Without access to higher education, women had no chance of gaining enough experience and expertise to secure a job of any significance, let alone a career in STEM.

Barriers limiting women’s access to higher education were not eliminated in the mid 1800s with the brave actions of Brewer and Blackwell.  The historical prejudices that denied women access to higher education in that century are present today in the minds of many who serve as members of college admissions committees and hiring authorities. According to a study conducted by researchers at Yale University, when provided with identical application materials across all applicants, both male and female faculty rated the male applicants more competent and more employable than female applicants (Moss-Racusin, Dovidio, Brescoll, Handelsman, 2012). Despite holding comparable levels of experience or knowledge, men are consistently chosen over women.

It is an unfortunate truth that gender bias can present challenges even in the circumstance of a woman being identified as the best candidate for a given position and the hiring process initiated.  Across the full spectrum of hiring levels – from entry level to executive level – the salary or wage offered to women can reveal gender bias. According to the Stanford School of Business, the entry level salary for a male employee is on average more than $4,000 higher than their female coworkers (Stanford Business, 2021).  Because women are less likely to be awarded promotions, the wage gap between women and their male coworkers becomes larger and larger over time. A paper published by the Pew Research Center concluded that, in STEM fields, men earn 40% more than women (Fry, Kennedy, & Funk, 2021).  This significant gap in earnings between women and men in the STEM field leads to significant differences in the ability of women and men to pay off debts incurred as part of their undergraduate and graduate education and to establish a solid financial footing as they move through their peak earnings years and into retirement.

Barriers women face in the workplace go far beyond those associated with lower pay and reduced opportunities for career advancement. The impacts of gender bias and discrimination are even greater when a woman holds the identity of mother or primary caregiver for another family member. A study conducted at the University of California, San Diego revealed that “43% of women in STEM careers left their full-time job within 4-7 years of having their first child...compared to 23 percent of new fathers” (Cech & Blair-Loy, 2019). Women are often forced to choose between being an important contributor to the STEM field and being a mother, while men are allowed to be both without having their professional commitment or parenting abilities called in question. In fact, in a study conducted by the Department for Business, Innovation and Skills (BIS) and the Equality and Human Rights Commission, one third of private sector employers reported that they believe that women who are pregnant or new mothers are “generally less interested in career progression” (Equality and Human Rights Commission, 2018). Women are often overlooked for promotions and, without prospects for growth within their company, many women pursue jobs at different companies, and sometimes within different employment sectors, that allow for professional growth.

Women who hold a non-white racial identity sometimes experience even more extreme forms of workplace bias and discrimination, including having to rise to higher hiring and workplace performance requirements than their white male and female coworkers, being paid lower salaries than their white male and female coworkers, having to assert their rightful status within the workplace more often than their white male and female coworkers, and experiencing less support from women co-workers than white women.  Joan Williams, Katherine Phillips, and Erika Hall published a study that examined the prevalence of gender bias among women of color in the workplace (Williams, 2020). These researchers investigated prejudices in women's daily work life by conducting in-depth interviews with women of color and administering an extensive battery of questionnaires to a diverse group of women working in STEM.  Findings from their study and a thorough review of the literature revealed four unique types of bias that influence the ways women of color are regarded in the workplace (Ngo, 2016).   One of the identified biases is the Prove It Again bias.  This bias is considered to be in effect when men are hired and/or offered advancement opportunities based on their potential , while their women coworkers are hired and/or offered advancement opportunities based on ratings of their current performance and historical successes.  Some experience of the Prove It Again bias is reported by nearly 65 % of women, with as many as 77% of Black women in STEM reporting experience with this particular form of gender bias (Williams, 2020). 

The Maternal Wall bias arises out of the belief that women lose their ability and commitment to work after having children.  Nearly two-thirds of scientists with children said that parental leave influenced their coworkers’ views of their commitment to the workplace (Williams, 2020).   Interestingly, women scientists without children are impacted by their coworkers views of womanhood and parenting; they report being expected to work longer hours to compensate for work that is not being performed by coworkers who have taken maternity leave. Many everyday workplace experiences challenge women’s very presence as contributing STEM professionals.  Among women holding professional STEM positions, 32% of white women and nearly 50% of women who identify as Black or as Latina report being mistaken for administrative or custodial staff.  These biases have significant implications for the success of women of color and all women working in STEM settings.

Harassment in the workplace can take many different forms and can be targeted towards anyone holding any position within a given organization.  That said, harassment often plays out in the context of power hierarchies; persons of higher professional rank and power are more able than persons of lower professional rank and power to use their professional power in ways that meet the definition of workplace harassment. (Wright, 2020).  Sexual harassment appears to be a particular frequent form of workplace harassment.  Holly Kearl, Nicole Johns, and Dr. Anita Raj authored a report of findings from a national study of sexual harassment and assault occurring in workplaces across the United States (Kearl, Johns, & Raj, 2019).  According to their report, 38% of women and 14% of men have reported experiencing sexual harassment at work.  Much of what can be considered “the STEM education and workspace” has been and continues to be male dominated.  Although the gap is decreasing, women still make up only 28% of the STEM workforce (AAUW, 2021). 

Research suggests that sexual harassment continues to be a particularly significant problem for women working in male-dominated STEM fields.  Sexual harassment simultaneously limits the scientific and technological contributions of women who maintain careers in STEM fields, pushes other talented and high-achieving women out of STEM careers entirely, and prevents young women from entering the field because of the fear that they, too, will become victims of sexual harassment and/or assault.

The information highlighted in this article makes clear that gender bias, biases related to women's racial identities and roles as caregivers, and harassment in the workplace serve as impediments to the success of women in STEM. If companies were truly serious about keeping and advancing women, they would handle these problems in the same way they approach other business issues: by developing objective measures and holding themselves accountable.

Cech, Erin A., and Mary Blair-Loy. “The Changing Career Trajectories of New Parents in STEM.” PNAS. National Academy of Sciences, March 5, 2019. 

Ceci, Stephen J., and Wendy M. Williams. “Understanding Current Causes of Women's Underrepresentation in Science.” PNAS. National Academy of Sciences, February 22

“Characteristics of Public School Teachers.” Coe. Accessed November 2, 2021.

Fry, R., Kennedy, B., & Funk, C. (2021). STEM Jobs See Uneven Progress in Increasing Gender, Racial and Ethnic Diversity.

“Historic Firsts in Women's Education in the United States.” U.S. News, March 11, 2009.

Ngo, Sarah. “Race and Gender Bias: Forces Driving Women of Colour out of STEM.” Simon Fraser University, July 27, 2016. 

“Pregnancy and Maternity Discrimination Research Findings.” Equality and Human Rights Commission, May 25, 2018.

“What’s Behind the Pay Gap in STEM Jobs?” Stanford Business, February19, 2021. 

Wright, S. (2020). Hierarchies and bullying: an examination into the drivers for workplace harassment within organisation. Transnational Corporations Review, 12, 162-172.

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The 5 Biases Pushing Women Out of STEM

• Joan C. Williams

A new study looks at race as well as gender.

By now, we’ve all heard about the low numbers of American women in science, technology, engineering, and math (STEM). Some argue it’s a pipeline issue – that if we can interest more young girls in STEM subjects, the issue will resolve itself over time. But that’s not convincing. After all, the percentage of women in computer science has actually decreased since 1991 .

• Joan C. Williams is a Sullivan Professor of Law at University of California College of the Law, San Francisco and the founding director of the Center for WorkLife Law. An expert on social inequality, she is the author of 12 books, including Bias Interrupted: Creating Inclusion for Real and for Good (Harvard Business Review Press, 2021) and White Working Class: Overcoming Class Cluelessness in America (Harvard Business Review Press, 2019). To learn about her evidence-based, metrics-driven approach to eradicating implicit bias in the workplace, visit www.biasinterrupters.org .

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MIT Science Policy Review

Reducing gender bias in STEM

Stephanie Mabel Kong * , Katherine Margaret Carroll, Daniel James Lundberg, Paige Omura, and Bianca Arielle Lepe

Edited by Friederike M. C. Benning and Anthony Tabet

Article | Aug. 20, 2020

* Email: [email protected]

DOI: 10.38105/spr.11kp6lqr0a

• Gender discrimination continues to persist in STEM disciplines.
• Federal, state, and local institutions can take steps to promote STEM role models, extracurricular enrichment and provide clear, progressive laws on gender discrimination, pay transparency and parental leave.
• Institutions can enact policies to improve workplace diversity and job accessibility by systematically addressing gender biases and providing better metrics for assessing gender equity.

Article Summary

Women continue to be underrepresented in science, technology, engineering, and math (STEM). Gender discrimination and gender bias reinforce cultural stereotypes about women and their ability to perform in male-dominated STEM fields. Greater policy intervention can bolster national response to gender-based harassment and discrimination. There are four major efforts that individual institutions, local governments, and the federal government can support to combat gender discrimination in STEM: (1) invest in early education initiatives for increasing female representation,(2) institute stronger state and federal policies around gender discrimination, (3) foster workplace practices that promote diversity, and (4) develop better quantification and metrics for assessing gender discrimination to enact more meaningful policies.

Gender discrimination is unfavorable treatment on the basis of gender. In the United States, the Civil Rights Act of 1964 outlawed gender discrimination in hiring, firing, pay, job assignments, promotions, as well as sexual harassment [1]. But if history is any indication, ensuring non-discriminatory workplace policies and practices is a slow process. Discriminatory practices are rooted in larger cultural and social norms, and the definition of gender discrimination is continually evolving. While the topics discussed herein may also apply to other forms of discrimination, the authors have chosen to focus on gender discrimination as it relates to women in science, technology, engineering, and math (STEM).

Gender equity is a problem in STEM

Gender disparity by the numbers

The percentage of women earning degrees in STEM fields illustrates the gender disparity within the United States. With the exception of the life sciences, women are underrepresented across all STEM fields [2]. Between 2008-2015, women earned 35.1% and 34.5% of undergraduate and PhD STEM degrees, respectively [3]. In 2016, women only made up 20.1% of computer science doctoral degree conferrals [4]. Further, fewer women occupy senior positions within STEM. In 2008, women only held a quarter of full-time junior faculty positions in engineering [5]. Women leave academia at a much higher rate than men, due in part to persistent gender biases [6, 7]. In hiring, for example, science faculty are found to rate identical resumes with male names higher than those with female names, and were willing to offer higher salaries to the male applicant [8].

This bias extends to industry as well. Women make up slightly less than a quarter of those employed, with particular underrepresentation in engineering and computer jobs [9, 10]. Women are also 30% less likely to be called to interview for a job than an equally qualified male counterpart [11]. Once hired, men are promoted at a 30% higher rate than women. This leads to female underrepresentation in higher-paying and higher-ranked roles in business [12]. Other reasons for increased attrition of women in academia include disparities in funding support and salary [5].

Gender discrimination from inequitable system design

Current social, workforce, political, healthcare, and technical systems favor men [13]. The emergence of such bias is the result of two key, erroneous assumptions: (1) standards designed for men apply equivalently to women and (2) systems do not need to be re-designed for women.

Standards that apply equally for men and women produce inequitable, and often, unsafe outcomes for women. The crash test dummy is designed for the 50th percentile male. This standard results in women being 47% more likely to be seriously injured and 71% more likely to be moderately injured in a car crash when compared to male drivers [14]. In a 2016 survey on the lack of Personal Protective Equipment (PPE) designed for women, 57% of the female participants reported that PPE “sometimes or significantly” hampers their ability to do their job [15]. The general presumptions of equitable baselines have posed unfair and, in many cases, unsafe conditions for women.

Although the systems designed for men have not changed, the environment and people that those systems serve, have. The current standard office temperature was designed in the 1960s to support the resting metabolic rate of an average forty-year-old, 70 kg male, overestimating the metabolic rate of women by as much as 35% [16]. This correlates to a recommended temperature increase for women between 2 to 4 degrees Fahrenheit [17]. A 2019 study found that women perform better at higher temperatures, suggesting that workplaces with both men and women may increase their productivity by raising the temperature [18]. The fact that the changing workplace demands of the 21st-century have largely gone unnoticed reflects a greater need to re-adjust systems that now serve large populations of both men and women.

So what can we do about it?

Start Early

Ever since the 1970s, the U.S. has supported policies to help protect and promote the education of women, including Title IX of the Education Amendments Act of 1972 and the Women’s Educational Equity Act (WEEA) in 1974 [19]. However, women still remain underrepresented in many disciplines in the U.S. Female under-representation in STEM begins in early childhood. A poll of over 200 New York kindergarten students found that a gender-brilliance stereotype exists as early as the age of six years old, where the characteristic of being “really, really smart” is associated more with white men than white women [20]. It is much harder to correct for this gender-brilliance bias once it has already been taught [13]. Early education initiatives intended to break down gendered stereotypes about who is “smart” or “good” at science are likely to be more effective with early elementary and even pre-K students. (1) Establishing diverse role models to promote diversity in STEM fields and (2) supporting extracurricular STEM programs are two techniques for preventing women from opting out of joining the STEM workforce at a higher rate than men.

Diverse role models promote diversity in STEM fields

The inclusion of diverse STEM role models in common media outlets promotes diversity in STEM fields and fosters a positive association of women and STEM from an early age and onwards. In film, men are depicted in STEM professions at five times the rate at which women are depicted. In family films, men are 14 times more likely to be depicted in STEM professions than women [21]. Classrooms, the media, and popular culture are avenues through which this bias can be checked. A 2016 report from the Obama White House highlighted three ways in which the entertainment industry can increase diverse STEM content: (1) increasing the representation of STEM professionals, (2) emphasizing the variety of STEM occupations, and (3) discrediting existing STEM misconceptions [21]. There is positive evidence to support that this approach is effective. For example, a recent study found that female 9th and 10th grade students perform better in science when the images in their textbooks include counter-stereotypic images of female scientists [22]. Another study found that exposure to non-stereotypical role models increased the self-efficacy of female computer scientists [23]. Given that these disparities in diverse STEM representation still persist, there has not been enough political response and accountability measures to these findings.

Extracurricular STEM programs lead to higher numbers of women majoring in STEM disciplines

Supporting a variety of STEM-related extracurricular activities is an effective way of attracting and retaining women to STEM disciplines [24].

There is a significant drop in computer science interest as girls age. Girls Who Code, an extracurricular program with a computer science focus for girls interested in programming, reports that interest reduces from 66% to merely 4% in girls between the ages of six to eighteen, respectively [25]. By offering year-long clubs, after-school activities, and summer immersion programs, participants of Girls Who Code study computer science in college at “15 to 16 times the national average” [26].

FIRST (For Inspiration and Recognition of Science and Technology) is a research and robotics community open to students from kindergarten through grade 12 [27]. FIRST competitions and challenges focus on current problems facing the STEM community. While estimates from a 2016 National Science Board report indicate that 13.7% of men and 2.6% of women entering college intend to major in engineering [28], male and female alumni of FIRST programs intend to major in engineering at a rate of 67% and 47%, respectively [29]. These after-school programs aid in the retention of students who are interested in engineering by maintaining interest through the time they enter college.

An important aspect of drawing more women to STEM is letting them know that they belong. Empowering young women to get involved in current “real-world” issues, like climate action, poverty, or sustainability, is a big part. Pretty Brainy, a program developed by the Women’s Foundation of Colorado, uses a methodology called design thinking to capture students’ interest to serve their communities and develop authentic solutions [30]. The results of this methodology are encouraging. According to a survey by Pretty Brainy in 2018, the program led to an increased interest in innovation and design in 100% of the surveyed girls. A stronger interest in science and technology as a direct consequence by the program was reported by 92% of surveyed girls [31].

After school STEM curricula have been effective in generating STEM interest. A recent analysis of 160 afterschool STEM programs across 11 states found that 80% of the participating students reported an increase in their science career knowledge and 73% reported an increase in their “science identity”—a personal belief that the student can succeed at science [32]. These results demonstrate the tangible importance that STEM-focused extracurricular programs can bring to advancing the STEM pathway. Gilbert et al. suggests that “for every child enrolled in an afterschool program today, there are two children who would be enrolled if an opportunity were available and affordable” [33]. Greater accessibility to these programs for marginalized groups is a critical part of creating a diverse STEM workforce.

Reform state and federal laws on gender discrimination pay transparency and parental leave

Although gender discrimination was declared illegal by the federal government, acts of gender discrimination often fall into a gray area in practice [34]. What constitutes unlawful discrimination is often determined on a case-by-case basis in state courts. Policymakers can aid by (1) providing nuanced definitions for sex-based discrimination at the federal and state level, (2) requiring pay equity transparency from employers and (3) adopting a standard parental leave policy.

Detailed definitions for sex-based gender discrimination promotes the elimination of biased workplace policies

The scope and depth of gender discrimination laws vary widely by state. California has adopted clear guidance, with separate definitions for sex and gender discrimination, and explicit examples of discriminatory actions in the workplace. Given that women are often more likely to volunteer for non-promotable tasks [35], California legislature now requires employers to factor both paid and unpaid (voluntary) work into promotions [34]. Many states only prohibit “sex and gender discrimination”—without defining what constitutes sex and gender discrimination. Virginia only outlaws gender discrimination for businesses above a certain size. Alabama has no state laws on sex and gender discrimination. In addition, most states permit some level of gender discrimination in occupations where sex is “required by business necessity” [36]; but well over half do not define what qualifies as a “business necessity”—leaving it subject to employer interpretation. This has been a controversial topic for several sectors where sex or gender can be considered a bona fide occupational qualification (BFOQ), e.g. the sex industry, military, and law enforcement [36]–[39].

Allowing employer interpretation of these policies has consequences. Companies have refused to provide workplace accommodations to pregnant women working jobs that require strenuous labor, despite providing such accommodations to employees with other medical needs [40]. Additionally, these discrimination cases disproportionately affect women of color, and black women in particular—who make up 14% of the female labor force, but represented 28.6% of the charges of pregnancy discrimination filed with the EEOC between 2011-2015 [41]. These cases continue to occur despite the Pregnancy Discrimination Act of 1978 [42], indicating that employers rarely understand what responsibilities they have in ensuring non-discriminatory workplace policies.

In STEM, gender discrimination is just as rampant. Grant eligibility is often determined from years since receiving a PhD degree, but that grant schedule rarely accounts for time off on maternity leave [43]. Pregnant graduate students and postdocs often face blatant discrimination from their professors, who hold the power to cut funding and jobs if having a child is viewed as “slacking off” [44]. While universities have Title IX offices to protect the victim in such cases, these university offices and programs can only go so far if those in power do not interpret such actions as discrimination.

Nuance in the law can help institutions and employers understand and eliminate policies that lead to gender discrimination. As an institutional example, the Office of Civil Rights (OCR) can work with colleges and universities to develop better procedures for enforcing Title IX policies [45]. When the law is less subject to interpretation, fair treatment is enforceable. However, while clearer definitions can lend guidance to how society identifies discriminatory actions, laws that are too specific run the risk of failing to cover all cases of gender discrimination and limiting the powers of the courts. It is important that laws strike a delicate balance between providing clear, actionable guidance and ensuring that the courts have the freedom to continually refine such definitions, based on case-specific circumstances.

Legislative action for pay equity transparency narrows the gender wage gap

In STEM, the gender pay gap is nuanced. The gender pay gap is smallest in life science disciplines and largest in computer science and engineering. A recent Bloomberg report on the best paid jobs in STEM calculate that female computer systems analysts and electrical engineers earn 85 cents for every dollar men earn [46]. These gaps persist even after controlling for demographic variables (e.g. race, family, seniority) [47].

Countries around the world are taking action. However, creating effective policies relies on accurate, representative data. Acquiring such data is challenging—especially from private companies. To address this, many countries require private companies to make pay data public. Since 2017, all large UK companies must publish mean and median hourly wages, all bonuses, as well as the proportion of males and females receiving bonuses and the proportion of males and females in each pay quartile [48, 49]. German companies with more than 500 employees must publish regular reports on gender parity [50]. Companies in Iceland must prove that they provide equal pay to their employees [51], and are externally audited [52]. This is all in stark contrast to the U.S. The Equal Employment Opportunity Commission (EEOC) will soon cease collecting wage data after complying with the two-year federal court order to obtain these figures [53]–[55]. Studies on the gender wage gap in STEM primarily rely on sample surveys and smaller pools of respondents. It can be challenging to gain population-level statistics for implementing nation-wide policies without census-level reporting of pay data.

Salary transparency is the first step in understanding how to best implement policy [56]. Without pay transparency, it is impossible to conduct the meta-analyses required for effective policy efforts.

Mandated parental leave shifts cultural stereotypes about hiring and promoting women

It is no secret that having a family disproportionately affects women. According to a 2010 survey of STEM careers, only 57% of new mothers worked full time, compared to 78% of new fathers [57]. Still, the U.S. has very few federal laws to protect the careers of women in STEM. The U.S. lags behind when it comes to federally mandated paid maternity leave. Out of the 36 member nations comprising the Organization for Economic Co-operation and Development (OECD), the U.S. is the only nation that does not provide government-mandated maternity leave [58]. Mandated maternity leave can ensure uniformity in workplace policies around pregnancy and paid leave.

Maternity leave alone can reinforce gender stereotypes about a woman’s responsibility to do the majority of child-rearing [59]. Moreover, women who take longer maternity leaves are less likely to be promoted or receive pay raises—leading to stalled career growth. In order to ensure that not all of the burden for child care falls on the mother, 24 countries in the OECD provide paid paternity leave. In recent years, states like California, New York, New Jersey, and Rhode Island have provided publicly-funded paid parental leave [60].

Paid parental leave can aid in reducing the cultural stigma associated with hiring women. Many women who work often take on the additional role of rearing children. This can lead to gender discrimination at work in project assignments and promotions if supervisors feel the need to assign smaller roles to women with families. In addition, studies indicate that even if a working mother is the household’s sole breadwinner, and child-rearing duties are shared equally between both parents, social norms around her implied duties and additional responsibilities as a being mother may prevent her from being seen as equally capable to her male colleagues [61, 62]. As some scholars have noted, “gender equality is slowed to the extent that efforts are focused exclusively on women” [63]. If both men and women are held responsible for taking time off to care for children, it is likely that cultural stereotypes will shift.

Build better workplace cultures

Although women have begun to move into traditionally male domains, gendered expectations and stereotypes remain. By taking a top-down, system-wide approach to combating divisive stereotypes, academic and corporate leadership can lay a strong foundation for workplace diversity and inclusion.

Gender neutral hiring processes ensure unbiased hiring processes

Decades of research have shown that people have a bias towards preserving the status quo. Researchers at the University of Colorado’s Leeds School of Business tested the strength of biases by examining the effect of gender, which was implied via manipulation of candidate names, on a candidate’s likelihood of being hired from a four-candidate finalist pool. Where there were two men and two women in the pool, the likelihood of hiring a woman was 50%. However, when there was only one woman and three men, the likelihood of hiring a woman dropped to 0%, suggesting that if a candidate pool is even slightly more male, employers are extremely unlikely to select a female [64].

Gender-blind hiring policies and technology that aids in removing gender from the application can help remove bias against female candidates. GapJumpers is a software platform that conducts tailored technical screens of job applicants prior to showing the employer any biographical information. Only after the employer selects candidates to interview based off of their test score will the employer see names and resumes [65]. For companies that do not have the budget for paid options like GapJumpers, there are custom alternatives to achieve gender-blind hiring. The American Alliance of Museums, a non-profit with 40 employees in Virginia, explicitly told candidates not to include their name, address, college name, or graduation date on their resume. Each resume is assigned a number, and applicants are referred to by their number until invited for in-person interviews. Candidates who send in resumes with identifying information are simply not considered [66].

Mentorship and targeted training programs facilitate promotion of women to executive positions

The corporate funnel to top executive positions is not conducive to promotion of diverse candidates, as women lag behind men at various management levels. Based on five years of data across more than 300 organizations, McKinsey and LeanIn.Org’s Women in the Workplace 2019 report found that significantly more men than women are promoted to the position of first-level manager. Only 72 women to every 100 men are promoted (or externally hired) to become a manager for the first time [12, 67]. To combat this systemic barrier, mentorship programs that connect minorities with experienced managers or role models as well as clearly articulated promotion criteria can help prepare potential managers and level the playing field.

The gender biases continue higher up the ladder, as the corporate funnel does not enable minorities to pursue C-suite positions. As of December 2019, despite the fact that 50% of American jobs belong to women [68], only 6.6% of Fortune 500 CEOs are women [69]. A Wall Street Journal study of executives at the largest publicly traded firms by market value shows that “line roles,” which are roles with profit-and-loss responsibilities, are what set executives on the CEO track. Men dominate roles with these responsibilities, such as heading a division, unit or brand. Conversely, women often lead divisions like human resources, administration or legal—all of which have no profit-and-loss associated with them [70]. Providing women and men alike with training, preparation for, and exposure to roles with profit-and-loss responsibilities can additionally increase the likelihood of promotion to CEO later in one’s career.

Sanofi SA is one example of a STEM company that collected and examined its internal data to identify gender discrepancies, implemented a women-focused management trainee program, and has seen quantifiable results from that program. In 2012, Sanofi looked at the gender breakdown of its internal “talent pipeline” and discovered that the percentage of women in management roles dropped at every level, with the steepest “drop-off […] just below the senior-leadership level” [70]. To combat this discrepancy in female representation in senior leadership, Sanofi implemented a six-month leadership program in which 30+ women per year receive executive coaching and a high-responsibility project outside of their primary business area. Since the global launch of Sanofi’s program in 2018, one-third of the 92 program participants were promoted. Additionally, women now lead all five of Sanofi’s North America businesses, which were previously run by five men [70, 71].

A critical piece in ensuring actionable insights is the continued collection and reporting of gender data at each management level. With a more complete dataset, gender breakdown at each management level could be further correlated with financial performance and analyzed (1) within a given corporation, (2) across similar/rival corporations, and (3) across various fields and industries.

Accommodating flexible working arrangements and modeling healthy work-life balance reduces “motherhood bias”

Women make up the minority of employees in the tech industry and the responsibilities of parenthood fall disproportionately on them. Women often encounter a “maternal wall bias,” in which “colleagues view mothers—or pregnant women—as less competent and less committed to their jobs” [61, 72]. Existing gender stereotypes make women vulnerable to being seen as less effective if a company has a “workaholic” culture that rewards face time over performance.

Employers can reduce stigma for working mothers by normalizing regular or flexible work hours for all employees. Managers themselves can embrace normal work hours and encourage their team to follow suit. If a male manager says he is leaving exactly at 5 pm to pick up his children from school, his colleagues, male and female, may feel more comfortable leaving the office the next time they have family priorities. Schedule flexibility does not mean employees must work less; an employer could implement a set 40-hour work week yet allow for daily flextime. For example, an employee could start work at 7 am to leave by 3 pm for familial or other duties [73].

Ultimately, responsibility falls on corporate leadership to implement policies that combat gender discrimination. However, every individual can help build a healthy workplace environment by actively encouraging flexible work. Individuals will have varied professional and personal priorities at different stages of their careers, so work-life flexibility can provide benefits across the board, while mitigating negative stigma that disproportionately affects working women.

Drive policy decisions with data

Quantifying gender discrimination is necessary for effective policy design. Data-driven analysis of policies to improve gender discrimination can validate an approach and facilitate wider implementation. Conversely, when a policy does not have the desired outcome, adequate data collection can help policymakers improve their strategy in an informed way. Through (1) mandated collection and reporting of this data, and (2) using this data to evaluate and hold institutions accountable for their behavior, gender discrimination can be more fully understood and reduced.

Mandated collection and reporting of gender specific data increases awareness of gender diversity

Aiming to increase corporate accountability and awareness about gender representation and diversity, the Bloomberg Gender-Equality Index tracks public companies who are “committed to supporting gender equality through policy development, representation, and transparency” [74]. The index presents a standardized reporting framework and tracks companies and organizations in STEM and beyond measuring how they promote gender equality across five dimensions: (1) female leadership and talent pipeline, (2) equal pay and gender pay parity, (3) inclusive culture, (4) sexual harassment policies, and (5) pro-women brand [75]. The collection and public presentation of this data provides power to current and future members of the U.S. workforce to make informed decisions and puts societal pressure on corporations to reduce gender discrimination within their organizations.

Collecting sex-disaggregated data is also essential for protecting women’s health. During the 2002-2004 SARS outbreak in China, pregnancy was treated like any other condition and was not systematically tracked, thus hampering the later understanding of the World Health Organization on the clinical manifestations of pregnancies complicated by SARS [76]. An early analysis of sex-disaggregated data for the COVID-19 pandemic suggests that there are gendered differences in disease diagnosis, mortality and vulnerability [77]. Many factors that contribute to the “differential vulnerability” that women and men experience reveal the importance of sex-disaggregated data collection [78].

Developing metrics reinforces organizational accountability to reduce gender discrimination

A number of international metrics to measure gender equity currently exist. The Gender Empowerment Measure (GEM) measures the equity of opportunities afforded to men and women. The Gender Equity Index (GEI) is used by the European Union to measure gender equity related to work, money, knowledge, time, power and health of their member states. Such metrics provide a high-level overview of gender equity. In comparison, the Athena SWAN award of the United Kingdom is an example of a national metric already finding use in helping promote women’s status in science. The award, which serves as an institutional report card recognizing good practices in recruiting, retaining, and promoting women in scientific fields, can be used to inform and aid other organizations in proving gender parity and reducing gender discrimination [79]. Organizations that wish to apply need to sign a charter stating their commitment to advancing the careers of women, and specifically reducing underrepresentation and the pay gap. Institutions which participated in the program saw more equal workloads between men and women, as well as an increase in women’s confidence and leadership [80].

Taking inspiration from the Athena SWAN award, the New York Stem Cell Foundation (NYSCF) convened a working group for the Initiative on Women in Science and Engineering (IWISE) that proposed “seven actionable strategies for advancing women in STEM” [81]. One of the strategies was creating an institutional gender equality report card that would enable the quantification of gender disparity and the degree to which policies and interventions are effective in reducing such disparities [82]. The report card was piloted over four years, during which NYSCF obtained data from more than 500 institutions across 38 countries. In an effort to evaluate the effectiveness of gender equity policy interventions, the report card combines qualitative assessments of institutional initiatives intended to support women with statistics on gender representation in academia. Subsequent analysis of the data highlighted several trends; gender representation decreased as seniority increased; women had low representation in seminar-speaker and influential committee roles [82]. A second phase of this initiative will commence to share learnings from high-scoring institutions.

The collection and reporting of data and the establishment of clearly defined and actionable metrics facilitate the formulation of effective gender discrimination policies. However, it is important to avoid several pitfalls: First, responsibility for adhesion to the standards should be shared equally—as gender equity work often falls disproportionately on women [81]. Second, such standards should introduce flexibility, as seen with the Athena SWAN award, which encourages adoption by allowing all levels to make meaningful change. Last, information collected by any source should be shared widely and publicly, allowing those who make policy to have the most complete understanding of the situations they are aiming to rectify.

Conclusions

The disproportionately lower representation of women in STEM fields is a reflection of underlying issues rooted in gender bias and discrimination. While we’ve increased representation in certain STEM fields, not all sectors have seen similar successes. Even when gender parity is reached within a field, there are still stark differences in the gender makeup of senior leadership. Without intervention and active discussion, STEM will continue to perpetuate the same biases that reinforce gender stereotypes. Our current environment—from early education to adulthood—is not set up to afford women equitable opportunities to succeed in male-dominated STEM careers. Accordingly, changing this dynamic will require concerted effort and engagement from many parties on multiple fronts: early education initiatives to promote diversity in STEM, state and federal legislation to guide institutional policies on wages and parental leave, inclusive workplace cultures to foster mentorship and encourage work-life balance, and collection of gender-specific data and metrics of accountability to create data-driven policy decisions.

Kong, S. M., Carroll K. M., Lundberg, D. J., Omura, P. & Lepe, B. A. Reducing gender bias in STEM. MIT Science Policy Review 1 , 55-63 (2020).

Open Access

This MIT Science Policy Review article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ic

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Stephanie Mabel Kong

Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA

Katherine Margaret Carroll

Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA

Daniel James Lundberg

Paige omura, bianca arielle lepe.

Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA

Addressing Sexism in STEM Is On A New Journey

In a new book, tc’s marie miville and colleagues examine enduring sexism and real-world strategies for success leveraged by women in science, technology, engineering and math.

Since the 1970s, which marked the era of a new feminist movement and the federal Title IX requiring equal opportunities for women in higher education, there have undeniably been more opportunities for women to teach or launch successful careers in the so-called STEM fields — science, technology, engineering and math — in which a female presence had once been nearly invisible.

Yet to the women who’ve been on the cutting edge of progress in the STEM professions, the storyline of that half century is still dominated by the routine, frustrating obstacles of a culture that continues to be dominated by men. For TC’s Marie L. Miville , Professor of  Psychology and Education  and Vice Dean for Faculty Affairs , these structural barriers are epitomized by the story she was told by a female professor who landed a prestigious university post and then wasn’t told when department meetings were held – or even given a key to its offices.

Miville, a leading authority on gender and racial differences in academia, said “there are individual success stories, laws that have been passed, and all sorts of scholarship and fellowship programs that have occurred in the last 50 years that have given a lot of individual girls and women a boost up. But sometimes girls and women are finding that still the glass ceiling — some of those structures — are still stubbornly there.”

The tension between the green shoots of progress for women in the STEM fields and the deep structural barriers that remain in place and have discouraged some from pursuing career dreams are at the heart of a new book by Miville and three female co-authors.

Marie L. Miville, Professor of Psychology and Education and Vice Dean for Faculty Affairs, and her latest book. (Photos courtesy of TC Archives and Springer) 

Women And The Challenge of STEM Professions: Thriving In a Chilly Climate , published by Springer, is indeed an overview of the many hurdles faced by female scientists, mathematicians and engineers — particularly in the campus environment — in areas such as advancement, or simply achieving recognition for their work. But the book also places an upbeat emphasis on success stories and positive strategies of women who’ve launched fulfilling careers and found happiness despite those lingering barriers.

Miville said in an interview that the project came about during the depths of the pandemic. It started with discussions she’d been having with Patricia Arredondo, a psychologist based at Arizona State University, around statistics showing that many girls who start their schooling with an interest in the STEM fields eventually abandon them by college, despite the decades-long push for female empowerment.

Miville and Arredondo would go on to strengthen the project’s ties to TC, bringing on alumna Christina Capodilupo — a member of the President’s Advisory Council and an adjunct assistant professor specializing in data research — and then one of Miville’s doctoral students, Tatiana Vera. Vera not only helped organize the effort but brought a much needed youthful perspective about the lingering roadblocks faced by women entering the field. Miville said both the presence of three Latina co-authors — versed in the ways that racial and cultural issues can intersect with gender — and their grounding in psychology aimed to bring some fresh perspectives to the ongoing conversation about the slow pace of progress for women in STEM.

The book’s core case could certainly be made through statistics. It notes that the number of U.S. women in engineering has not increased since the early 2000s and the rate of female deans, department heads, and faculty at universities has hovered at barely more than one-third. But at the center of the book is a focus on the experiences of 10 women and the ups and downs of their careers in STEM.

For example, a postdoctoral researcher named Emma told the authors she felt discouraged from pursuing a traditional career in STEM: “I would have scientific ideas, talk about them with my PI, get little feedback on whether or not they were good. But then I’d hear that they were using those ideas that I had talked about and were being done by someone. I was like, wait a minute. I talked about that with him.”

But Emma also reported finding her path forward with the help of mentorship, which the book finds often was critical for those women who do ultimately find satisfaction in their STEM careers. Other best practices described in the book include strategies for more assertiveness and for overcoming the negativity of their male colleagues whose competitiveness often has the effect of stifling female empowerment.

“I hope girls and women and all the readers take away a hopefulness from the stories that they read,” Miville said of the book. “So it is challenging – but also not just possible but very likely that you can successfully navigate your own pathway to success, wherever that takes you.”

— Will Bunch

Tags: Psychology Counseling & Clinical Psychology Psychology STEM / STEAM Women/maternal studies

Programs: Clinical Psychology

Departments: Counseling & Clinical Psychology

Published Monday, Sep 26, 2022

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How are gender stereotypes affecting perceptions of STEM careers?

Gender stereotypes need to change as they will prevent talented students from pursuing a career in the discipline. Image:  UNSPLASH/[email protected]

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Stay up to date:.

• Gender bias is a factor that influences the categories of 'soft science' or 'hard science'.
• Research shows that people are more likely to describe a field as a 'soft science' when they believe it to have a higher proportion of women within it.
• Men, and some women, are less likely to pursue a career in a field with a higher proportion than 25% of women within it, leading to salary decrease in the field.
• Gender stereotypes need to change as they will prevent talented students from pursuing a career in the discipline.

The big idea

One factor that influences the use of the labels “soft science” or “hard science” is gender bias, according to recent research my colleagues and I conducted.

Women’s participation varies across STEM disciplines. While women have nearly reached gender parity in biomedical sciences, they still make up only about 18% of students receiving undergraduate degrees in computer science, for instance.

In a series of experiments, we varied the information study participants read about women’s representation in fields like chemistry, sociology and biomedical sciences. We then asked them to categorize these fields as either a “soft science” or a “hard science.”

Across studies, participants were consistently more likely to describe a discipline as a “soft science” when they’d been led to believe that proportionally more women worked in the field. Moreover, the “soft science” label led people to devalue these fields – describing them as less rigorous, less trustworthy and less deserving of federal research funding.

Why it matters

Over the past decade, a growing movement has encouraged girls and women to pursue education and careers in science, technology, engineering and math, or STEM. This effort is sometimes described as a way to reduce the wage gap.

By encouraging women to enter high-paying fields like science, technology and engineering, advocates hope that women on average will increase their earning power relative to men . Others have hoped that, as women demonstrate they can be successful in STEM, sexist stereotypes about women’s ability and interest in STEM will erode.

Our research suggests this may not be the case. Stereotypes about women and STEM persist, even in the face of evidence that women can and do productively participate in STEM fields. These stereotypes can lead people to simply devalue the fields in which women participate. In this way, even science and math can end up in the “ pink collar ” category of heavily female fields that are often devalued and underpaid .

What other research is being done

Other research has found that explicit “science equals men” stereotypes were weaker among people who majored in science disciplines with high participation by women, like biological sciences, compared to those who majored in fields with few women, like engineering. This finding suggests that exposure to women in your own field can shift the gender stereotypes you hold.

But our studies more closely align with other research suggesting that, rather than reducing gender stereotyping, women’s increased participation results in the devaluation of more heavily female fields.

When women make up more than 25% of graduate students in a discipline, men – and to a lesser extent women – become less interested in pursuing that discipline , and salaries tend to go down . Other studies have found that the same job is seen as deserving a lower salary when positioned in a “female field” than when it is listed in a “male field.” Together, this suggests that the presence of women, and not characteristics of the job or field, is what leads to devaluation and lower pay.

The COVID-19 pandemic and recent social and political unrest have created a profound sense of urgency for companies to actively work to tackle inequity.

The Forum's work on Diversity, Equality, Inclusion and Social Justice is driven by the New Economy and Society Platform, which is focused on building prosperous, inclusive and just economies and societies. In addition to its work on economic growth, revival and transformation, work, wages and job creation, and education, skills and learning, the Platform takes an integrated and holistic approach to diversity, equity, inclusion and social justice, and aims to tackle exclusion, bias and discrimination related to race, gender, ability, sexual orientation and all other forms of human diversity.

The Platform produces data, standards and insights, such as the Global Gender Gap Report and the Diversity, Equity and Inclusion 4.0 Toolkit , and drives or supports action initiatives, such as Partnering for Racial Justice in Business , The Valuable 500 – Closing the Disability Inclusion Gap , Hardwiring Gender Parity in the Future of Work , Closing the Gender Gap Country Accelerators , the Partnership for Global LGBTI Equality , the Community of Chief Diversity and Inclusion Officers and the Global Future Council on Equity and Social Justice .

What still isn’t known

Participants who worked or planned to work in science were just as likely as the rest of the population to use gender as a cue to categorize soft vs. hard sciences. But in scientists, we found no connection between that tendency and their beliefs about women’s ability in science and math. That is, scientists’ levels of sexism, as measured by self-report, were unrelated to their inclination to call fields with many women “soft sciences.”

We don’t know how scientists and non-scientists ended up making the same connection between gender and soft science labels. It’s possible that people who work in science are just more aware of norms against expressing such gender stereotypes – meaning their self-reports are less likely to reflect their true beliefs and actually more closely match those of non-scientists.

But it’s also possible that something else is driving their use of the “soft science” label. For example, to our surprise, women who worked in science were more likely compared to men in science to label fields with many women as “soft sciences.” This could reflect the tendency for some women who experience sexism in their fields to distance themselves from other women as a way to protect themselves from being targets of sexism.

What’s next

Science advocates must grapple with the fact that women’s work in scientific fields can result in fields being devalued. For society to benefit fully from the broad spectrum of scientific disciplines, advocates may need to address gender stereotypes more directly.

Gender stereotypes about STEM could also affect which fields talented students choose to pursue. The label of “soft science” might be a turnoff for high-achieving students who want to prove their strengths – or, conversely, students who are insecure about their abilities might avoid a major described as a “hard science.”

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Women Fighting Stereotypes and Systemic Discrimination in STEM

While half the world is female, fewer than 30 percent of the world’s Science, Technology, Engineering, and Mathematics (STEM) professionals are women.

Earth Science, Engineering, Mathematics

Women in a Science Lab

While half the world is female, less than 30 percent of the world’s Science, Technology, Engineering, and Mathematics (STEM) professionals are women.

Photograph by Lightfield Studios Inc./Alamy Stock Photo

Science is the  systematic ,  evidence -based study of how the natural world works. Presumably, this  objective  pursuit would be free of  bias  and welcoming to those with the desire and talent to pursue it, but that has not always been true for women. While about half the human  population  is female, fewer than 30 percent of the world’s Science, Technology, Engineering, and Mathematics (STEM) professionals are women.

Women with research positions in academic STEM do their jobs well. They publish at a similar rate as men with their research having roughly the same impact, according to this study by UNESCO : https://uis.unesco.org/en/topic/women-science. However, women’s STEM careers are often less productive than men’s STEM careers because women’s careers are shorter and they have higher dropout rates, according to the March 2020 paper. Each year, women have nearly a 20 percent higher chance of leaving  academia  than men do.

Gender representation in STEM differs by field. Women often outnumber men in  biological  fields. However, men far outnumber women in physics, computer science, and engineering.

Like other male-dominated jobs in the United States, science and engineering received a huge  influx  of women with the onset of World War II. With huge numbers of men away fighting, women were encouraged to enter spaces they had been excluded from. When the war ended and men returned to the  work force , women were expected to leave the lab and the office. But some women fought to remain in STEM. American women in STEM justified their positions as assets to the nation as it fought the  Cold War .

Fighting for their place in the world of STEM has been even tougher for Black and brown women. That is not to say that Black, Indigenous, and other women of color have not made their mark on science. Katherine Johnson, a Black woman, made the calculations to ensure U.S. astronaut John Glenn orbited Earth and returned safe. Sarah Al-Amiri led a team of fellow Arab women in placing an orbiter around Mars, making the United Arab Emirates just the fifth country to do so.

All too often these achievements are the  exception , not the  norm . Historically, there have been legal, social, and cultural barriers to entry and advancement in these fields. Studying and working in STEM has been traditionally marketed as men’s work. Systemic discrimination, unconscious bias , and sexual harassment can also prematurely ends women’s STEM careers.

In the United States, women are 47 percent of the employed  civilian   work force , but only 25 percent of the STEM work force . In the U.S., women of every  ethnicity  are underrepresented in STEM jobs, except for Asian women. Asian women make up 4.3 percent of STEM occupations while accounting for 2.8 percent of the employed work force . White women are about 32 percent of the work force , but about 17 percent of those working in STEM.

Those numbers are bleaker for Black and brown American women. Latinas comprise 6.7 percent of the work force , but just 1.7 percent of STEM jobs. Black women account for 6.0 percent of the work force and 2.2 percent of STEM occupations . Women who self-identified by other racial designations, such as Indigenous or Pacific Islander, were too few to be analyzed . A similar breakdown is seen with the attainment of STEM bachelor’s degrees with Black and Latina women earning fewer than their  proportion  of STEM degrees.

The U.S. is not exceptional with its lack of women in the STEM work force. Worldwide, women make up just over 29 percent of STEM researchers. There are just 17 nations where women make up the majority of STEM researchers.

As technology advances, more STEM professionals are sought out. Nations receive an economic boost with added STEM workers, making them appealing to governments. In the United States alone, STEM work accounts for 69 percent of the gross domestic product. This calculation includes many jobs that don’t require a college degree, like X-Ray technician.

The lack of women in STEM fields doesn’t just hurt society, but women themselves. STEM occupations are highly valued professions with higher salaries than other careers. Yet when compared to men, women in STEM are paid less.

The need is so high it often outpaces the ability of employers to fill them. Women of color are a huge part of the world’s people and talent pool. By underutilizing Black and brown women in these positions, their respective nations are losing out on their skills and  perspective . Research shows upping diversity improves problem solving, which is a key to any STEM job.

NOTE: While we recognize neither sex nor  gender  is a  binary , data used to study STEM and sex is limited to such. Thus, this story will be using these limited terms.

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Original research article, the gender gap in stem fields: the impact of the gender stereotype of math and science on secondary students' career aspirations.

• 1 Institute for Educational Sciences, University of Basel, Basel, Switzerland
• 2 Swiss Federal Institute for Vocational Education and Training SFIVET, Bern, Switzerland
• 3 Institute of Educational Science, University of Bern, Bern, Switzerland

Studies have repeatedly reported that math and science are perceived as male domains, and scientists as predominantly male. However, the impact of the gender image of school science subjects on young people's career choice has not yet been analyzed. This paper investigates the impact of the masculinity image of three school subjects—chemistry, mathematics, and physics—on secondary students' career aspirations in STEM fields. The data originated from a cross-sectional study among 1'364 Swiss secondary school students who were close to obtaining their matriculation diploma. By means of a standardized survey, data on students' perception of masculinity of science school subjects were collected using semantic differentials. The results indicate that for both sexes, math has the strongest masculinity attribution, followed by physics as second, and, finally, chemistry with the lowest masculinity attribution. With respect to gender differences, our findings have shown that among female students, the attribution of masculinity to the three school subjects does not differ significantly, meaning that female students rated all subjects similarly strongly as masculine. Within the group of male students however, the attribution of masculinity to math compared to chemistry and physics differs significantly, whereas the attribution of masculinity to chemistry and physics does not. Our findings also suggest that gender-science stereotypes of math and science can potentially influence young women's and men's aspirations to enroll in a STEM major at university by showing that a less pronounced masculine image of science has the potential to increase the likelihood of STEM career aspirations. Finally, the paper discusses ways of changing the image of math and science in the context of secondary education in order to overcome the disparities between females and males in STEM.

Introduction

Gender segregation in the vocational orientation of adolescents has been well documented for decades in most OECD countries ( OECD, 2006 , 2012 ). The persistence of gendered paths in career choices has recently been reflected in the current Global Gender Gap Report of the World Economic Forum (WEF), which states that on average men are underrepresented in the fields of education, health and welfare whereas women are underrepresented in the STEM fields ( WEF, 2017 , p. 31). Moreover, on the basis of the occupational aspirations of 15-year-old adolescents, the prognosis for change in gender-based disparities in occupational and academic choices suggests that gender segregation in the education and labor market will remain persistent ( OECD, 2017 ).

The persistence of horizontal gender segregation in educational and occupational fields contributes decisively to the spread of gender-stereotypic beliefs about a natural fit of women in careers in more expressive and human-centered fields and men in technical and math-intensive fields ( Charles and Bradley, 2009 ). Gender stereotypes are part of a broader belief system that includes attitudes toward female and male family roles, female and male occupations, and gender-associated perceptions of the self. As bipolar constructs, gender stereotypes imply that what is masculine is not feminine and vice versa ( Deaux and LaFrance, 1998 ; Worell, 2001 ; Renfrow and Howard, 2013 ). The social role theory ( Eagly and Wood, 2012 ) suggests that gender roles and their occupants are highly visible in everyday contexts and that gender stereotypes emerge in response to the observation of women and men in different social roles and in role-linked activities related to occupational choices ( Koenig and Eagly, 2014 ). This theoretical assumption was confirmed in a study by Miller et al. (2015) , which analyzed how women's enrollment in science courses relates to the gender-science stereotype. Based on a survey of about 3,50,000 participants in 66 nations, this study concluded that explicit and implicit national gender-science stereotypes were weaker in countries with a higher female enrollment in tertiary science education. This study also demonstrated that stereotypes about science were strongly gendered, even in countries with high overall gender equity. In addition, a meta-analysis of two major international data sets—“Trends in International Mathematics and Science Study” (TIMMS) and the “Programme for International Student Assessment” (PISA)—has confirmed that gender equity in education is important not only for girls' math achievement but also for girls' self-confidence and valuing of mathematics ( Else-Quest et al., 2010 ). Furthermore, a cross-national data analysis has indicated that gender differences in math are closely related to cultural variations in opportunity structures for girls and women, in particular to gender equity in school enrollment, women's share of research jobs, and women's parliamentary representation (ibid., p. 103). Accordingly, the low proportion of women in STEM leads to the spread of a gender stereotypical image of math and science as a male domain and beliefs about male supremacy in technical and math-intensive fields. In turn, such beliefs affect young people's career choices, leading to a mutual reinforcement of gender stereotypes, and gender gaps in career related interests and choices ( Nosek et al., 2009 , p. 10,596).

In Switzerland gender segregation is also persistent and is especially noticeable in the STEM field ( FSO, 2013 ). In educational tracks at the universities of applied science, with only 21.3% of women enrolled in STEM courses in academic year 2017–2018. However, some STEM fields are more strongly gender segregated than others. The lowest proportion of women is in the fields of informatics (10.4%) and technology (8.5%), whereas in the fields of chemistry and life-sciences the proportion of women is considerably higher (43.7%) ( FSO, 2019a ). In secondary education, gender is almost balanced in chemistry and biology (girls 18.4% and boys 20.5%) as a subject of specialization, whereas considerably more boys (18.4%) than girls (4.4%) decided to specialize in the subjects math and physics ( FSO, 2019b ). It is, thus, important to distinguish between different STEM disciplines and subjects when addressing the gender gap in the STEM field ( Rosser, 2012 ; Ertl et al., 2017 ).

Following this notion, our study aimed to analyze the gender stereotype of school science subjects among female and male students and the impact of gender-science stereotypes on the career aspirations of young people. The ultimate goal of our study is to provide a more comprehensive understanding of gender equity in STEM.

The Gender Stereotype of Math and Science

The gender stereotype of math and science has been analyzed via a variety of quantitative and qualitative methods (review in Makarova and Herzog, 2015 ). Among those are the Draw-A-Scientist Test (DAST) (e.g., Chambers, 1983 ; Finson, 2002 ; Scherz and Oren, 2006 ), the Implicit Association Test (IAT) (e.g., Greenwald et al., 1998 ; Nosek et al., 2002 , 2009 ), explicit stereotype assessments using attitude questionnaires (e.g., Kessels, 2005 ), semantic differential assessments (e.g., Herzog et al., 1998 ; Makarova and Herzog, 2015 ), and individual or group interviews (e.g., Archer et al., 2010 ).

Studies that applied the DAST method reported that students from kindergarten to high school perceive a scientist as a male person. The children's drawings contained very few portrayals of female scientists and these few drawings were mostly drawn by female students. For example, in a study among students from kindergarten through fifth grade there were only 28 pictures of a female scientist out of 4,807, and all of these 28 drawings were drawn by girls ( Chambers, 1983 ); in a study surveying students in grades 2–12 only 135 pictures out of 1,600 displayed female scientists and only six out of 135 pictures of a female scientist were drawn by male students ( Fort and Varney, 1989 ); in a study among students of 9–12 years of age, there were only 72 pictures of a female scientist out of 223, and of those 72, only 13 pictures were drawn by male students ( Huber and Burton, 1995 ). The precise way in which a scientist was pictured by middle school students was reported in a study by Scherz and Oren (2006 , p. 977): “The common image was that of a scientist as a bespectacled male with unkempt hair in a white lab-coat.” Moreover, the following quote from a study by Mead and Metraux (1957) on high-school students' image of a scientist highlights how persistent the scientist-stereotype remains over decades. The image of a scientist is depicted in students' essays as “a man who wears a white coat and works in a laboratory. He is elderly or middle aged and wears glasses … He may wear a beard, may be unshaven and unkempt” ( Mead and Metraux, 1957 , p. 386). Finally, the most recent meta-analysis of five decades of U.S. DAST studies based on 78 studies ( N = 20,860) among children grades K-12, shows a growth in children's depictions of female scientists in later decades. However, the more female scientist appeared only in drawings by young children, but science was still associated with men among older children ( Miller et al., 2018 ). The authors conclude that despite the increase of women's representation in science over the last decades, children still observe more male than female scientists in their social environments ( Miller et al., 2018 , p. 1,943).

Furthermore, research on gender stereotypes has revealed that science is not only associated with a male person, but that masculine traits are also attributed to it. A study by Archer et al. (2010) suggested that although young children do not have profound knowledge about science subjects, they attribute masculine traits to science at an early age. In the same vein, a study by Cvencek et al. (2011) reported that as early as second grade children perceive that math is a male domain, demonstrating the American cultural stereotype. In addition, a study among high school students reported that better performance in STEM subjects was attributed to boys, and masculine traits to a person who works as a scientist ( Hand et al., 2017 ). Another study among school children and university students by Weinreich-Haste (1981) assessed the gender image of different academic subjects using ratings on a six-point masculine-feminine scale. The study reported that math, physics and chemistry had the strongest connotation as masculine academic subjects. Moreover, it showed that science subjects were not only rated as masculine but also associated with a set of attributes commonly associated with masculinity such as being hard, complex, based on thinking rather than on feelings ( Weinreich-Haste, 1981 , p. 220f.). In contrast, a study on gender perception of school subjects among students aged 11–12 years, which applied a seven-point masculine-feminine scale, reported that while physics was rated as significantly more masculine, chemistry and mathematics were rated as neither masculine nor feminine ( Archer and MacRae, 1991 ).

To summarize, we can state that the male stereotype of science and of a scientist is persistent and appears as early as in kindergarten age, while the association of science with men is especially persistent among older children. Research has also shown that students predominantly perceive science subjects (math, physics, and chemistry) as a male domain, although findings do not provide a clear picture as to which of these subjects is more strongly associated with male gender. The reason is the very broad age-range of students (K-12) across reported studies, lack of comparison of gender stereotypes of different school subjects within one study, different methodology (explicit and implicit assessment) used to assess gender stereotypes of science, as well as the time span between findings of different studies. Thus, further research on the perception of masculinity of chemistry, math, and physics among school students is needed to gain deeper insight into the impact of the gender stereotypes of science subjects on STEM-career aspirations.

Gender Differences in the Perception of Gender-Science Stereotypes

Research on gender-science stereotypes has illustrated differences between female and male youth with respect to the endorsement of stereotypic beliefs about STEM . A study among primary school students illustrated that stereotypical beliefs that STEM school subjects are more suitable for boys than for girls were more strongly endorsed by boys than by girls. Moreover, this study has shown that students with stereotype-consistent interest in STEM-related school subjects were particularly likely to endorse gender-science stereotypes. Consequently, especially boys who were highly interested and girls who were relatively uninterested in STEM-related school subjects were more likely to believe that STEM school subjects constitute a male domain ( BlaŽev et al., 2017 ). In line with this, a study among high school students has shown that girls reported lower self-efficacy in math and science compared to boys ( Hand et al., 2017 ). Finally, a study among first-year university students indicated that negative stereotypes of women's engineering and mathematical ability were more strongly endorsed among male students, whereas female students were more likely to report higher perceptions of their engineering abilities ( Jones et al., 2013 ).

With respect to the perception of different STEM disciplines , studies among adolescent youth have shown that female students show a more pronounced gender stereotype for math compared to male students, who are less likely to exhibit implicit gender-stereotypic associations ( Steffens et al., 2010 ). In line with these findings, a study by Nosek et al. (2002 , p. 44) reported that even women who had selected math-intensive majors had difficulties in associating math with themselves because they associated math with the male gender. Also, studies that analyzed the gender stereotype of physics found that, among high school students, being interested in physics was associated with the male gender ( Kessels, 2005 ; Kessels et al., 2006 ) and that, among girls, being interested in physics endangered their self-identification with the female gender ( Kessels et al., 2006 ). Furthermore, a typical teacher of mathematics and physics was imagined to be a man ( Kessels and Taconis, 2012 ). Finally, a study among secondary school students in Switzerland showed that, among female students, the semantic profile of math and physics correlated negatively with the semantic profile of the female gender, whereas the semantic attributes of chemistry were significantly related neither to the male nor to the female gender. From the male students' point of view the semantic profile of math correlated negatively with the semantic profile of the female gender, whereas the semantic attributes of chemistry and physics were positively related to the semantic profile of the male gender. Whereas, the female gender was strongly associated with traits such as soft, playful, soulful, dreamy, lenient, frail, and flexible, among the semantic traits associated with math and physics were attributes such as hard, serious, distant, sober, strict, robust, and rigid. Overall, this study has shown that among the three school subjects analyzed in the study, math and physics were either negatively associated with female or positively associated with male gender. In contrast, chemistry was the least gender stereotyped because among female students there were no significant associations of the term chemistry with either gender term and among male students no negative association with the term woman ( Makarova and Herzog, 2015 ). These findings are interesting in light of students' preference for their subject of specialization in secondary schools in Switzerland ( FSO, 2019b ) showing that chemistry is chosen almost equally often by boys and girls, whereas math and physics are largely avoided by girls as subjects of specialization. Accordingly, students' gender-related perception of different science subjects may differently impact their preferences of STEM subjects at school and vice versa.

To summarize, we can state that female and male students indicate different patterns of gender-science stereotype. It seems that male participants show more endorsement of the gender-science stereotype by regarding STEM subjects as more suitable for boys and attributing less abilities in the STEM disciplines to the female gender compared to the male gender. At the same time, female participants are more likely to associate math and science more strongly with the male gender and masculine traits than with the female gender and feminine traits. Finally, previous research has shown that school science subjects differ with respect to their gender-related connotation, and indicating that chemistry has the least pronounced masculine image among secondary school students.

Gender-Science Stereotype and Career Aspirations in STEM

The impact of the gender-science stereotype on students' interest in STEM subjects and their aspirations to pursue a career in STEM fields has been addressed from different perspectives.

Based on Eccles' expectancy-value model, which highlights the impact of culturally based stereotypes and identity-related constructs on educational and occupational choices ( Eccles, 1994 ; Eccles and Wigfield, 2002 ), a number of studies have shown that academic self-concept and subject interests are among the most relevant determinants in students' selection of secondary school majors ( Nagy et al., 2008 ). Similar mechanisms seem to be crucial for career choice or choice of a major in higher education ( Nagy et al., 2006 ). A recent study among female students in STEM subjects with a low proportion of females revealed that gender stereotypes have a negative impact on students' STEM-specific self-concept even among students with good grades in STEM ( Ertl et al., 2017 ).

According to the theoretical framework of Gottfredson (2002 , 2005 ), occupational aspirations are incorporated in the individual self-image developed during socialization from early childhood through adolescence. The process of developing occupational aspirations is embedded in the comparison of one's self-image with the image of an occupation and one's judgment about the match between the two. In this process, the gender image of an occupation is especially crucial for career choice, because the “wrong” sex type of an occupation is more fundamental to self-concept than the prestige of an occupation or individual interests. Applying Gottfredson's theory, the significant impact of the gender image of an occupation on the process of career choice was confirmed in a number of studies ( Ratschinski, 2009 ; Bubany and Hansen, 2011 ). Moreover, research suggests that girls are more likely to narrow their occupational choices because they perceive particular occupations as inappropriate for their gender. Accordingly, girls tend to shift their occupational aspirations to gender-typical occupational expectations more strongly than do boys. At the same time, boys' perceptions of occupations appear to be more gender-stereotypical ( Hartung et al., 2005 ).

Research focusing on self-to-prototype similarity suggests that the lack of similarity between the self and an academic subject is linked to a lower probability of liking this subject or choosing this academic subject as a major ( Kessels, 2005 ; Kessels et al., 2006 ; Taconis and Kessels, 2009 ). Moreover, the perceived closeness between the self and a school subject was predictive for youths' career choice intentions ( Hannover and Kessels, 2004 ; Kessels et al., 2006 ). In the same vein, a study among ninth and tenth-grade students by Neuhaus and Borowski (2018) investigated whether the greater self-to-prototype similarity impacts students' interest in coding courses. This study revealed that, under the condition that course descriptions were related to communal goals, girls showed greater interest in learning to code compare to the agentic-goal condition of the course description ( Neuhaus and Borowski, 2018 , p. 233).

Likewise, a study among students and faculty reported that agentic traits are more strongly associated with success in science than communal traits, discouraging women from pursuing a science career ( Ramsey, 2017 ). Another study among first-year undergraduate students illustrated that implicit stereotypes of science completely accounted for a gap in male and female students' interests to pursue science. Especially the academic aspirations of women who strongly identified as female were affected by the gender stereotypic image of science ( Lane et al., 2012 ). In line with this, a study among first-year women engineering students reported that engineering identification was a significant predictor of persistence in engineering, and that this relationship was stronger for women than men ( Jones et al., 2013 ). Finally, a study among undergraduate science majors demonstrated that a stronger gender-science stereotype has a diminishing effect on identification with science and science career aspirations among women, whereas, among men, a stronger gender-science stereotype boosts their identification with science and their career aspirations in science fields ( Cundiff et al., 2013 ).

To summarize, we can state that gender-science stereotyping has been shown to hinder the self-identification of young women with STEM academic subjects and fields and also to negatively affect their self-concept and their subject interests. These, in turn, hinder female students from opting for a science major and pursuing a career in science. For male students, gender-science stereotyping seems to have the opposite effect and, thus, boosts their career aspirations in STEM.

Focus of the Study

Given that previous research has often focused on gender-science stereotypes of science in general or on stereotypical beliefs about single STEM disciplines, our study contributes to previous research by simultaneously analyzing the gender stereotype of different school science subjects—chemistry, math, and physics—among female and male students. These three science subjects were chosen because females are strongly underrepresented in math and physics within the educational sector and career fields, whereas chemistry has a more balanced gender ratio. This allows us to investigate the impact of gender-science stereotypes of different science subjects on students' aspirations to study STEM. In view of the theoretical and empirical framework of the study, we define the gender stereotype of three school subjects as the extent of association of each school subject with masculine traits (see section Measurements; masculinity index ).

In terms of hypotheses, we firstly expected differences with respect to the degree of masculinity which students attribute to chemistry, math, and physics. We hypothesized that chemistry would be ascribed the lowest degree of masculinity compared to math and physics.

Secondly, we expected gender differences among secondary school students in the association of chemistry, math, and physics with male gender. We hypothesized that this association of the three science subjects with masculine traits would be stronger among female students.

Thirdly, we expected that the gender stereotype of math and science would affect female and male secondary school students' aspirations to enroll in a STEM major at university. We hypothesized that to the extent students conceive of STEM-school subjects as masculine they would be less inclined to aspire to enroll in a STEM major at university. We further hypothesized that stereotyping science subjects as masculine would have a greater negative impact on the STEM aspirations of female than male students.

Participants

The study presented was part of the research project Gender atypical career choices of young women , a project embedded in the Swiss National Science Foundation's Research Program on “Gender Equality” (NRP 60). The study is based on quantitative data which originated from a standardized survey of 1,364 students in Swiss-German-speaking secondary schools. The study was carried out following the ethical principles and codes of the Faculty of Humanities at the University of Bern, which are based on international ethics codes (e.g., of the American Sociological Association and of the American Psychological Association). Accordingly, approval by an ethics authority was not required. Students were informed about the research project and participated in the survey voluntarily. Participants? Informed consent was implied through survey completion; therefore, they were not required to provide written consent to participate. Written parental consent was not necessary either, because all students had reached legal adulthood and could decide for themselves. After the survey all data were anonymized.

The surveyed students were close to obtaining their matriculation diploma (i.e., school leaving certificate), which in Switzerland permits entry into tertiary education. The participants were on average 19 years old ( SD = 1.0). With regard to sex, the percentage of female students (54.1%) was somewhat higher than that of male students (45.9%).

Measurements

Masculinity index.

Data on students' perception of the gender image of the school subjects chemistry, math, and physics were collected using semantic differentials ( Makarova and Herzog, 2015 ). The semantic differential is one of the most popular techniques of explicit attitude assessment ( Millon et al., 2003 ). An explicit measurement of the gender stereotype of science subjects was chosen over an implicit stereotype test, because the study focuses on the salient gender stereotypes of those subjects ( Millon et al., 2003 , p. 356). The semantic differential uses bipolar scales with contrasting adjectives at each end to measure people's reactions to stimulus words and concepts ( Heise, 1970 , p. 235). The methodological advantage of the semantic differential scale is that it highly adaptable in assessing respondents' connotative association with any concept ( Osgood et al., 1957 ; Heise, 1970 ). The basic assumption of the semantic differential is that attitudes toward two associated concepts tend to converge and toward two dissociated (contrasted) constructs tend to diverge ( Heise, 1970 , p. 249). In our study attitudes toward gender and science were measured using semantic differentials consisting of 25 pairs of adjectives with semantically opposite meanings (e.g., hard—soft, strong—weak, robust—frail) to assess the connotations of the four terms man, chemistry, math, and physics on a seven-point scale (1 = greatly, 2 = fairly, 3 = somewhat, 4 = neither, 5 = somewhat, 6 = fairly, 7 = greatly). This instrument is based on the original scale ( Osgood et al., 1957 ) which was initially adapted to the German language by Hofstätter (1973) and then validated in Switzerland in two studies on the gender stereotype of school subjects ( Herzog et al., 1998 ; Makarova and Herzog, 2015 ).

The student sample was divided into groups, with each group completing the semantic differential for one subject term and for the man term: chemistry and man ( n = 406), math and man ( n = 512) and physics and man ( n = 446). In order to avoid response bias, the semantic differential of the subject was introduced at the beginning of the questionnaire and the semantic differential of the term man at the end of the questionnaire. On the basis of these data we calculated a masculinity index by subtracting the 25 items of the man profile from the corresponding items of each subject profile and summing them up to a sum score for each student. At the end of this procedure one value for each student was calculated. For easier interpretation, this value was reversed; a negative value was transformed into a positive value and a positive value into a negative value. Accordingly, the masculinity index expresses the differentiation between high masculinity (low discrepancy between the profiles man and subject; max. = +6) and low masculinity (high discrepancy between the profiles man and subject; min. = −6). For example, a score of 5 on the masculinity index, indicates that the semantic profile of the respective subject (chemistry, math, or physics) and the semantic profile of the term man are very similar, meaning that the discrepancy between the two semantic profiles is low. Figure 1 illustrates our calculation. Moreover, the masculinity index is approximately normally distributed (Kurtosis = 2.09, SE = 0.13; Skewness = 0.47, SD = 0.07) ( George and Mallery, 2016 ).

Figure 1 . Masculinity index of chemistry, math, and physics.

STEM Field Study Choice

To assess the field of study choice, the secondary school students were asked about their subject preference for study at a university or at a university of applied sciences after the successful completion of secondary school. The answers were coded by the gender-type of the field of study, based on the gender distribution of master's degrees obtained at Swiss universities in the year 2010 ( FSO, 2012 ). A field of study was labeled as female-atypical (male-typical) when the proportion of women who received a master's degree in that field was below 30 per cent. In our sample, Mathematics, Statistics, IT, the Natural Sciences and Engineering fall into this category. Since all listed fields of study can be assigned to the STEM area, the category is henceforth labeled STEM study choice. All other fields of study were assigned to the category “non-STEM study choice.” The multivariate analyses were conducted with the dichotomous variable STEM field study choice (STEM field study choice = category 1; non-STEM study choice = reference category 0).

Attribution of Masculinity to Chemistry, Math, and Physics Among Secondary School Students

The attribution of masculinity to the three science subjects among female and male students was subjected to a two-way ANOVA (school subject and students' sex). The overall model yielded an F ratio of F (5, 1, 355) = 15.83 , p ≤ 0.001. With respect to the degree of masculinity attributed to the three science subjects, our analysis of variance indicated significant differences F (2, 1, 355) = 10.76, p ≤ 0.001. Post-hoc comparisons (Bonferroni) has shown that the attribution of masculinity differs significantly between math and chemistry ( p ≤ 0.001) and between math and physics ( p ≤ 0.05). There were no significant differences in the attribution of masculinity to chemistry and physics. The mean values indicated that math has the strongest attribution of masculinity, followed by physics as second, and finally chemistry with the lowest attribution of masculinity (see Table 1 ). With regard to the sex differences in the attribution of masculinity, our analysis of variance yielded significant differences between female and male students F (1, 1, 355) = 63.20, p ≤ 0.001. The ascription of masculinity to the three science subjects turned out to be stronger among female than among male students (see Table 1 ).

Table 1 . Descriptive statistics.

The interaction effect between two factors school subject and students' sex was non-significant F (2, 1, 355) = 2.34, p = ns . Nevertheless, to explore the interaction term in more detail we analyzed the attribution of masculinity to the three science subjects within the group of female and that of male students. For this purpose, the confidence intervals for the three science subjects were calculated. Within the group of female students, the attribution of masculinity to the three school subjects does not differ significantly, meaning that female students rated all subjects similarly as strongly masculine [95% CIs: chemistry [0.19, 0.36], math [0.30, 0.46], and physics [0.23, 0.39]]. Within the group of male students, however, the attribution of masculinity to math and chemistry [95% CIs [0.12, 0.27], [−0.20, 0.02]] as well as to math and physics [[0.12, 0.27], [−0.07, 0.09]] differs significantly, whereas the attribution of masculinity to chemistry and physics does not [[−0.20, 0.02], [−0.07, 0.09]].

Gender Stereotype of Chemistry, Math and Physics and Students' Study Aspirations

First, we analyzed career aspirations among the secondary school students by carrying out x 2 -test ( chi-square test ) for the binomial dependent variable STEM study choice (see Table 2 ). Overall, one sixth of all students aspired to having a STEM major (16.6%). However, aspirations to study STEM subjects were not equally distributed between men and women. While among men every fourth student (24.3%) planned to study STEM, among women only every tenth student (10.1%) was interested in STEM studies.

Table 2 . Study choice.

Second, we analyzed the attribution of masculinity to school subjects (chemistry, physics, and math) among secondary school students who had chosen a STEM compared to those students who had chosen a non-STEM major ( Figures 2 – 4 ).

Figure 2 . Masculinity index of chemistry and career aspirations.

Figure 3 . Masculinity index of math and career aspirations.

Figure 4 . Masculinity index of physics and career aspirations.

Our analysis reveals the following findings for each subject:

• Chemistry ( Figure 2 ): With respect to career aspirations of young women, our results show that female students who opt for a non-STEM study major connotated chemistry significantly strongly as masculine compared to young women with a STEM career choice ( p ≤ 0.01). Among young men there were no significant differences in the attribution of masculinity to the subject chemistry between students who had chosen STEM and those who had chosen another study field.

• Math ( Figure 3 ): Our results show that among female and male students who had potentially chosen a non-STEM major, the attribution of masculinity to math was significantly higher compared to youth with a STEM career choice (female: p ≤ 0.05; male: p ≤ 0.001).

• Physics ( Figure 4 ): Considering female students who had potentially chosen a non-STEM study major, physics was significantly more highly stereotyped as a masculine subject compared to young women with a STEM career choice ( p ≤ 0.001). Among young men there were no significant differences in the attribution of masculinity to the subject physics between male students who had chosen STEM and those who had chosen another study field.

To sum up, young women who aspire to study a STEM major stereotype the three subjects as less strongly masculine compared to young women who aspire to study non-STEM subjects. Among young men, only math was rated as highly masculine among those students who had chosen a non-STEM study program. Thus, for young women as well as for young men with a non-STEM career choice, math has a highly masculine image. What is interesting is that even young women who opt for a STEM field rate the subjects—except physics—as masculine, though only slightly.

Finally, Generalized Linear Models (GzLM) were estimated ( McCullagh and Nelder, 1989 ) to shed light on the impact of the gender image of math and science on the likelihood that female and male students aspire for a STEM field of study. The procedure modeled the choice of a STEM study major as the response category, with all other study fields as the reference category (non-STEM). We aggregated the masculinity index for math and the two science subjects for the model of female students, because separate models showed nearly the same effect for each individual subject, and therefore we could increase the power of the model in terms of cases. The model for male students included only the masculinity index of math as a predictor, since there was no significant effect for science subjects between young men who had chosen STEM and non-STEM ones (see also Figures 2 , 4 ). We report the Exp(β), which indicates the likelihood of an occurrence of the tested effect. If the value is below 1, the likelihood decreases; if it is above 1, the likelihood increases.

Table 3 shows the first model estimated for female students [Likelihood Ratio x ( 1 , 739 ) 2 = 17.09, p ≤ 0.001, Pearson-Chi-Square 60.95 (88, 739) = 0.69]. The findings reveal that a strong masculine image of math and science decreases the likelihood of young women choosing a STEM study (Exp(β) = 0.44; p ≤ 0.001). In other words, if young women do not perceive math and science as predominantly masculine, they opt significantly more often for studying a STEM major.

Table 3 . Impact of the masculine image of math and science on secondary students' career aspirations.

The second model was estimated for male students [Likelihood Ratio x ( 1 , 267 ) 2 = 9.22, p ≤ 0.01, Pearson-Chi-Square 73.90 (66, 267) = 1.12]. The results show that the masculinity of math is also a predictor of young men's career aspirations. The higher the masculinity image, the lower the likelihood of a STEM study choice (Exp(β) = 0.48; p ≤ 0.01).

To conclude, both models show that the image of chemistry, math and physics has an impact on students' career intentions. If the image of the three subjects has strong masculine connotations, career choice is unlikely to be within the STEM field.

This study contributes to the line of research on the gender stereotype of science by analyzing the gender-related image of three school subjects . It provides, moreover, more refined knowledge on the impact of gender stereotypical perception of math and science on female and male secondary school students' choice to enroll in a STEM university degree program.

In line with the findings of a study by Weinreich-Haste (1981) , our results reveal that students not only perceive chemistry, math and physics as masculine, but also that there is a considerable difference in the strength of the association of each subject with the male gender. According to our findings, math is most strongly perceived as a masculine subject among female and male secondary school students, followed by physics and then chemistry, which has the weakest masculine connotations. The weak masculine connotations of chemistry have also been reported by other studies ( Archer and MacRae, 1991 ; Makarova and Herzog, 2015 ). Consequently, we could confirm the first hypothesis stating that chemistry is accorded the lowest degree of masculinity compared to math and physics.

With respect to differences between female and male students in the gender-stereotypical connotations of science, our findings illustrate that female secondary school students perceive all three subjects considerably more strongly as a male domain than do male students. These findings are consonant with findings of previous studies on strong associations of math and physics with the male gender among female adolescents ( Nosek et al., 2002 ; Kessels, 2005 ; Kessels et al., 2006 ; Steffens et al., 2010 ). In addition, our results illustrate that male students regard only math as strongly masculine, whereas physics and chemistry have a comparably low score on the masculinity index. Thus, our findings confirm our second hypothesis by showing that the association of the three science subjects with masculine traits are stronger among female students.

With regard to the impact of the masculinity image of math and science on secondary students' career aspirations , the findings of our study show that young women who potentially chose STEM as a field of study at university perceived all three school subjects—math, physics, and chemistry—as less masculine than did those young women who chose other majors. Moreover, our results suggest that among female students a strong masculine image of math and science decreases the likelihood of choosing a STEM major at university. These findings propose that masculine traits associated with science subjects at school constitute a major obstacle, particularly for young women's self-identification with science ( Nosek et al., 2002 ; Cundiff et al., 2013 ) and for their aspirations to become researchers ( Šorgo et al., 2018 ). Regarding the career aspirations of young women , our study supports the notion that stereotypical beliefs about math and science prevent young women from entering a STEM career ( Lane et al., 2012 ; Ramsey, 2017 ).

Finally, our results on the career aspirations of young men in relation to the stereotypical gender connotations of school subjects show that young men with non-STEM career aspirations perceived only math but not science subjects as significantly more strongly masculine than did young men who chose a STEM major. Furthermore, a strong association of math with masculine traits negatively affected male students' STEM career aspirations. These findings suggest that young men who opted for non-STEM majors do not fit the masculinity stereotype and therefore the strong masculine connotations of math may have an inhibiting impact on their career aspirations similar to that on the STEM career aspirations of young women. A possible interpretation of these findings is that, among young women as well as among young men, the lack of similarity between their self-image and the image of an academic subject not only affects their choice of specialization in secondary school ( Kessels, 2005 ; Kessels et al., 2006 ; Taconis and Kessels, 2009 ) but also leads to a lower probability of choosing those subjects in their further educational career.

Overall, the findings of our study confirm our third hypothesis by illustrating that the higher the extent of association of STEM-school subjects with masculine traits, the lower is the likelihood to enroll in a STEM major at university—both for female and male students. However, our findings also suggest that gender-science stereotypes have a stronger negative impact on the STEM aspirations of female than male students because a strong masculine image of math and science significantly decrease the likelihood of choosing a STEM major among female students, whereas only a strong masculine image of math significantly decrease the likelihood of enrollment in a STEM major among male students.

Our findings have some implications for overcoming the gender disparities in STEM. As the gender-related image of an academic discipline has a considerable effect on young people's career aspirations, a critical evaluation of the school subjects' image might be one way to break through the gender-image-driven limitations of the career horizons of female and male students. For example, a study in Computer Science has shown that women's interest in studying Computer Science can be increased through a change of image of this academic discipline ( Cheryan et al., 2013 ). The image of a school subject can, for example, be depicted in school textbooks. An empirical analysis of science textbooks in secondary education not only illustrated the overrepresentation of male protagonists but also revealed stereotypical portrayals of science and scientists ( Makarova et al., 2016a ). Since stereotypic representations in textbooks have an effect on male and female secondary school students' understanding of and anxiety about science ( Good et al., 2010 ), an effort needs to be made to overcome stereotypical gender representations in textbooks at all educational levels. Especially since decisions to enroll in a field of study or choose a field of work in vocational education are made relatively late, and since gender images of school subjects have most likely by then been internalized and settled, reflections about gender stereotypical images of math and science subjects should preferably be encouraged in early childhood . For example, a study by Archer et al. (2010) suggested that although young children do not have profound knowledge about science subjects, they attribute masculine traits to science at an early age. Moreover, gender stereotypical beliefs should be also tackled among teachers and other gatekeepers who are potentially involved in the development of vocational interests among children and secondary students. As the study of Thomas (2017) showed, a teacher's implicit science-is-male stereotype can contribute to gender differences in female students' motivational beliefs and probably also their gendered educational choices. Finally, Else-Quest et al. (2010) suggest that proximal factors such as quality of teaching mediate the effect of gender inequality on math achievement. Thus, rise in gender equity in education can also promote boys' academic development.

Our study is subject to a few limitations . Firstly , our study has a cross sectional design and is, therefore, limited to suggesting a causal relationship between the masculinity image of science and youth career aspirations. Secondly , our study assesses the career aspirations of secondary school students and not their actual enrollment in particular majors at the university. Although this operationalization of career choice has been applied by other studies ( Nagy et al., 2006 ; Watt, 2006 ), it does not exclude the possibility that the anticipated choice of a study major does not necessarily lead to the actual choice of the same major after enrollment at university. Thirdly , we should note that our study applies an explicit assessment of masculinity connotations of school subjects by using a semantic differential with 25 opposite semantic meanings. Thus, we cannot rule out that an open-ended questionnaire on masculinity image would yield different results on the semantic connotations and the strength of masculinity of the target school subjects. Moreover, we calculated the masculinity index based on the similarity of the semantic profiles of the term man and the corresponding subject term. As the present study does not include measures of the semantic ratings of the term woman we cannot compare the attribution of the feminine traits to chemistry, math and physics and its impact on the STEM study choice. Finally , the gender-related image of school subjects and their implications are one of several determinants that affect the career aspirations of male and female secondary school students. Since we did not control for other potential determinants in the explanatory models (e.g., self-image of students, their abilities, or interest in science), our results are limited to the investigation of the impact of gender-science stereotype on students' aspirations. It has been demonstrated that further school-related factors, such as the instructional design of science classes ( Aeschlimann et al., 2016 ), teachers' support and encouragement ( Aeschlimann et al., 2015 ) as well as family-related factors, and also peers can considerably influence the career-choice decisions of young people ( Makarova et al., 2016b ).

Author Contributions

All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.

The authors gratefully acknowledge the Swiss National Science Foundation for financial support of the study Gender atypical careers of young women (Grant no. 4060-129279).

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords: gender, career aspirations, science, mathematics, secondary school students

Citation: Makarova E, Aeschlimann B and Herzog W (2019) The Gender Gap in STEM Fields: The Impact of the Gender Stereotype of Math and Science on Secondary Students' Career Aspirations. Front. Educ. 4:60. doi: 10.3389/feduc.2019.00060

Received: 28 December 2018; Accepted: 11 June 2019; Published: 10 July 2019.

Reviewed by:

Copyright © 2019 Makarova, Aeschlimann and Herzog. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Elena Makarova, elena.makarova@unibas.ch

This article is part of the Research Topic

Gendered Paths into STEM. Disparities Between Females and Males in STEM Over the Life-Span

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Bridging the gender gap: why do so few girls study Stem subjects?

To attract more girls to study Stem subjects at university, we need to tackle the stereotypes they are exposed to early on

You will no doubt be aware that women are underrepresented in Stem (science, technology, engineering and maths) occupations. They make up 14.4% of all people working in Stem in the UK, despite being about half of the workforce. This is well short of the country’s goal of a critical mass of 30%. Increasing women in Stem is forecast to increase the UK’s labour value by at least £2bn.

There is a whole tangle of reasons why the gender gap in Stem exists. One is a pipeline issue – fewer girls than boys choose to study Stem subjects at secondary school and university. Interventions internationally mean the numbers of girls in Stem subjects are creeping up very slowly, but the gap remains surprisingly resistant nonetheless.

Are girls biologically worse than boys at Stem subjects at school?

Biological explanations tend to rely on the fact that boys are better at spatial tasks while girls are better at verbal recall tasks. However, these differences are very small and their link to Stem ability is tenuous .

Meta-analyses consistently show that girls and boys are on average much more similar than they are different across a range of skills. For instance, a meta-analysis of gender differences in mathematics, based on 100 studies and testing more than three million people, found that girls outperformed boys overall in primary school, there was no difference in secondary school and there was only a very slight and inconsistent male advantage for complex problem solving.

Typically, girls do as well as or outperform boys in Stem classwork but do worse on tests. The International Student Assessment ( Pisa ) reports on 276,165 15-year-olds from 40 countries who take identical tests in mathematics and reading. In 2015 , the average difference between high-achieving boys and girls was 19 points, the equivalent of about half a year at school. But these differences disappeared when factoring in reported levels of self-confidence or anxiety towards mathematics. On average, girls were more anxious about tests than boys were, and this seems to have affected their score.

Are gender gaps socially constructed?

Luigi Guiso and colleagues used the Pisa data to explore gender differences in maths performance. Overall, girls’ maths scores averaged 10.5 points (2%) lower than the mean average for boys, but this difference varied by country. In Turkey, for instance, the gender gap is greater (boys outperform girls by 22.6 points) while in Iceland the gender difference is reversed: girls outperform boys by 14.5 points.

The researchers then classified each country on the basis of gender equality, ie how much they treated women as equal to men. In more gender-neutral countries such as Norway and Sweden the maths gender gap disappeared. They state that if Turkey were characterised by the same gender equality seen in Sweden, the gender gap in maths would be eliminated.

Then why are there fewer women in Stem careers even in more gender-neutral countries?

These cultural effects suggest the gender gap in Stem careers should disappear in more gender-neutral countries. Yet we still find a higher proportion of men in Stem-related careers than women, even in gender-neutral Sweden. A study of 1,327 Swedish secondary school students explored why more boys are attracted to Stem subjects at university and more girls are attracted to subjects in the Heed (health, elementary education and domestic) spheres.

This difference was partially explained by “social belongingness”: teenagers felt they would fit in better in subjects that had more of their own gender. But another important factor was “self-efficacy”: the belief that one can succeed in a domain. We tend to approach domains where we feel we are competent and avoid those in which we do not. Boys and girls both had high self-efficacy in the Heed subjects, but boys chose not to pursue them. The researchers suggest that this may reflect the low social value and rewards associated with careers in these spheres.

In contrast, girls on average had much lower self-efficacy ratings in Stem, despite outperforming boys across school subjects. Even in one of the most gender-neutral countries in the world and despite the evidence of their own marks, girls still seem to be succumbing to the stereotype that girls aren’t as capable in these subjects.

Where do gender stereotypes come from?

This is a complicated question, and the answer is: lots of places. Even young children can absorb and be influenced by gender stereotypes, and these can be as detrimental for boys as they are for girls but in different ways. A recent study by Lin Bian, Sarah-Jane Leslie and Andrei Cimpian has shown that five-year-old girls are just as likely to say that girls can be “really, really smart” but from six years up they think brilliance is much more likely in boys .

From this age girls are also more likely to be attracted to a game if it is described as being for children who “work really hard” than if it is described as being for children who are “really smart”. Again, this is despite the fact that girls, on average, are outperforming boys in these subjects at school. These findings suggest gendered notions of intelligence are picked up very early and start having an effect on the sorts of interests that girls pursue.

How can we attract more girls to Stem subjects at university?

Research from these different perspectives converge on the idea that there is little to no difference in boys’ and girls’ average ability at Stem subjects. This means that in order to attract more girls to study Stem subjects at university and enter Stem careers, we need to tackle the stereotypes they are exposed to and we need to do this early.

One way to encourage girls is to use appropriate role models. As part of a campaign to coincide with today’s International Women’s Day, Speakezee , a platform that connects academics with non-academic audiences, is working with the Institute of Physics and the Girls’ School Association to send young female graduate Stem students into schools to talk to and inspire young teenage girls to consider pursuing Stem topics at A-level. Professor Brian Cox may be the popular face of physics for mass viewing audiences in the UK, but young girls need individuals they are more likely to relate to if they are to be persuaded not to abandon their Stem potential.

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Racism, sexism and disconnection: contrasting experiences of Black women in STEM before and after transfer from community college

• DeeDee Allen   ORCID: orcid.org/0000-0001-8459-2397 1 ,
• Melissa Dancy 2 ,
• Elizabeth Stearns 3 ,
• Roslyn Mickelson 3 &
• Martha Bottia 3  

International Journal of STEM Education volume  9 , Article number:  20 ( 2022 ) Cite this article

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Repeated calls to diversify the population of students earning undergraduate degrees in science, technology, engineering, and mathematics (STEM) fields have noted the greater diversity of community college students and their potential to thus have an impact on the racial/ethnic composition of 4-year degree earners. In this paper, we investigate barriers and supports to Black women’s success in STEM, using longitudinal interview data with seven Black women who were enrolled at community colleges and stated an interest in majoring in STEM at 4-year institutions.

Our findings highlight a contrast between community colleges and universities. At community colleges, Black women were able to form supportive relationships with professors and peers, downplayed the potential of racism and sexism to derail their STEM ambitions, and saw little to no impact of bias on their educational experiences. Those students who transferred characterized university climates very differently, as they struggled to form supportive relationships and experienced racism and sexism from professors and peers.

Conclusions

We conclude using Patricia Hill Collins’ Domains of Power framework to categorize students’ experiences, then end with recommendations for change that will result in less alienating experiences for Black women, among other minoritized students.

Introduction

Current research on the status of STEM education in the United States indicates reason to be concerned with access, inclusivity and persistence, especially when it comes to the success of minoritized groups. For example, although Black women account for 11.4% of all college graduates, they make up only 2.5% of the STEM workforce and that number sharply declines when referring to the more mathematically based fields, such as physics, chemistry, engineering and math (National Science Foundation [NSF], 2019 ). The lack of equity necessitates that the experiences of Black women in STEM be examined to better understand and dismantle prohibitive structures and cultures to ensure that all STEM participants have equitable access to rewards, as well as to ensure that work in STEM is as robust and creative as possible.

Discussions regarding efforts to diversify the populations of students pursuing study in STEM fields repeatedly emphasize the possibility that students attending community college are a diverse group that represent an untapped resource (Bahr et al., 2017 ; Dowd, 2011 ; Wang, 2009 ). Research differs on whether attending a community college is associated with a greater or lesser probability of eventually earning a degree from a 4-year institution (Doyle, 2009 ; Perez-Felkner et al., 2019 ; Wang et al., 2019 ), or more specifically a STEM degree (Dinh & Zhang, 2021 ; Marco-Bujosa et al., 2021 ; Zhang, 2021 ). Even less clear is how Black women interested in STEM majors experience community college and potential transitions to 4-year universities. Studies that examine the experiences of Black women who have transferred from community colleges (e.g., Jackson, 2013 ; Reyes, 2011 ) typically do so only after the students have transferred to 4-year institutions, thus missing the important community college experiences that shape trajectories.

In this study, we look at two axes of identity—race and gender—and their intersections for Black women who started their pursuit of a STEM degree at a community college. Specifically, we report on a longitudinal panel of interviews with seven Black women, conducted 3 years apart, focused on understanding their STEM trajectories.

This study has several aspects that fill important gaps in understanding about the experiences of a minoritized group in STEM: Black women community college students. First, we use an intersectional approach, discussed below, to examine the STEM experiences of Black women and investigate how their positionality influences their experiences. Second, we use a longitudinal approach with interviews at two timepoints that allow investigation of the classroom and campus experiences across multiple institutions which remain largely understudied. This longitudinal perspective allows a valid examination of how STEM attitudes change from a time when students were enrolled at community college and uniformly positive about the possibility of majoring in STEM at a 4-year institution to a time 3 years later when the situation with respect to their attitudes and experiences in STEM was drastically different.

Conceptual frameworks: intersectionality and domains of power

We use an intersectional approach. Intersectionality refers to the idea that aspects of people’s identity (e.g., race, gender, class, sexual orientation) interact to build identity and to condition people’s lived experiences (Collins, 2015 ; Crenshaw, 1990 ). In this study we focus exclusively on the experiences of Black women. By centering Black women in our research, and thereby positioning them as knowledge producers, we illuminate the intersecting forms of oppression they experience and their unique experience as Black women, and thus seek to avoid the erasure of identity that would come with a broader examination of the experiences of women or people of color (Bowleg, 2008 ; Crenshaw, 1990 ; Haynes et al., 2020 ; Ireland et al., 2018 ).

Moreover, we draw on Collins’ ( 2009 , 2015 , 2019 ) work on domains of power to describe the multiple ways in which Black women’s identities evoke oppressive reactions from people who have traditionally held power in STEM (i.e., White men). Collins identifies four domains of power: interpersonal, structural, disciplinary, and cultural. The interpersonal domain refers to personal experiences as people relate to one another, i.e., the daily interactions between individuals. The structural domain refers to institutional and organizational arrangements, i.e., policies. The disciplinary domain refers to the rules and their enforcement that uphold social hierarchy. And finally, the cultural domain refers to institutions and practices that justify social inequalities. We use the domains of power framework to more fully illuminate the power structures at work in community college and university classrooms. As Collins describes, “The domains-of-power framework enables a more finely-tuned analysis of how unjust power relations are organized and resisted” (Collins, 2019 , p. 170).

Using Collins’ domains of power framework as a base, our research question focuses on how and when social processes reinforce or challenge existing intersectional inequalities during the community college-to-university STEM trajectory for Black women.

Background research

Research on black women in stem.

Despite significant systemic structural barriers, many Black women persist and thrive in STEM. In fact, they tend to have higher levels of interest in science than White women (Hanson, 2008 ; Verdín, 2021 ). A number of studies have identified experiences that increase persistence and success for women of color in STEM (Carlone & Johnson, 2007 ; Espinosa, 2011 ; Ireland et al., 2018 ; Jackson et al., 2013 ; Ko et al., 2014 ; Ong et al., 2018 ). For example, Ko et al. ( 2014 ) identified eight strategies Black women and women of color generally employ for success in STEM, including avoiding unhelpful advisors and using peer networks to counteract isolation. Developing a solid identity as a scientist has also been effective for women of color (Carlone & Johnson, 2007 ), with findings echoed in Ireland et al.’s ( 2018 ) synthesis of sixty studies on Black women and girls in STEM. Navigating these strategies takes time and energy, which increases the demands on women of color to succeed.

There is a substantial body of research detailing the influence of both gender and race, and their intersections, on the experiences of STEM students (Hill et al., 2010 ; Madsen et al., 2013 ; National Academy of Sciences [NAS], 2011 ; Nguyen & Riegle-Crumb, 2021 ; Ong et al., 2011 ; Rainey et al., 2018 , 2019 ; Rugheimer, 2019 ; Tate & Linn, 2005 ). The underlying historical and social contexts that have given rise to inequity have also been detailed in the literature (Annamma et al., 2019 ; Gholson, 2016 ). In math, Gholson ( 2016 ) lays out many reasons for the absence of research on Black women—their invisibility—and the need for research that focuses on Black girls and women. These bodies of work suggest the environment and structures in STEM lead to a “chilly climate” (Flam, 1991 ; Hall & Sandler, 1982 ; Seymour & Hewitt, 1996 ; Seymour & Hunter, 2019 ) for women and students of color, resulting in diminished achievement, low satisfaction, and high attrition rates. Women of color experience multiple forms of oppression in STEM environments, exacerbating the chilly climate beyond that experienced by White women or men of color, in a phenomenon scholars refer to as a “double-bind” (McGee, 2020 ; Ong et al., 2011 ).

The climate in STEM frequently alienates Black women in multiple ways. They report feelings of isolation, invisibility and a lack of belonging (Hanson, 2008 ; Johnson, 2011 ; Ko et al., 2014 ) that are amplified by their low representation within many STEM fields. Black women are frequently the only women of color in these environments, simultaneously heightening their visibility and positioning them as outsiders. In addition, Black women are alienated in STEM through the sexist and racist words and actions of peers and professors, including microaggressions (Lee et al., 2020 ; Park et al., 2020 ; Robinson et al., 2016 ; Sue et al., 2007 ; Wilkins-Yel et al., 2019 ), harassment, and discrimination (Ong et al., 2011 ).

Four common categories of microaggressions women of color in STEM experience include: questioning of their skills and expertise in STEM-related topics; messages that communicate, either explicitly or implicitly, that they do not belong in STEM; having their presence and voice overlooked; and encounters that are specifically influenced by gender and race (Wilkins-Yel et al., 2019 ). The impact of these microaggressions is to decrease sense of belonging for women of color (Ong et al., 2011 ) as well as negatively impact their mental health (Nadal et al., 2014 ). Thomas et al. ( 2018 b) interviewed a number of successful Black women in the computer science field who confirmed the intersectional discrimination that exists for Black women. The main barriers facing STEM, in addressing high attrition rates and low satisfaction of Black women, and women and people of color generally, are cultural and systemic. Thus, addressing the problem of underrepresentation will require cultural and systemic solutions.

Community colleges as pathways to STEM

In 2018–19, nearly, 35% of all college students in the United States were enrolled in a 2-year postsecondary institution ( National Center for Educational Statistics [NCES], n.d. ). In addition, community colleges enroll disproportionately higher numbers of students from racial/ethnic groups historically excluded from STEM than 4-year institutions ( NCES, n.d. ). When combined with a growing body of research that points to the positive environment that community colleges are able to offer, the community college pathway represents a potential systemic solution to diversifying STEM. However, there is not enough intersectional research available to determine whether Black women reap the full benefits of that positive environment.

The culture of the community college environment has demonstrated the necessary support for Black women and the success of women in general. For example, strong support systems, including interactions with faculty and advisors, are important in the academic success of Black women students in STEM and also play an important role in shaping the intent to transfer and persist (Jackson et al., 2013 ; Jorstad et al., 2017 ). Such supportive environments in community colleges do lead to student success while also increasing confidence in STEM (Starobin & Laanan, 2008 ; Starobin et al., 2016 ). While, in general, research points to the positive environments that can be provided by community colleges, it is important to note that environments likely vary by institution.

Research on the success of women, in general, has found that community colleges provide an intellectually rigorous and comfortable learning environment (Hu & Ortagus, 2019 ; Jackson & Laanan, 2011 ; Jackson et al., 2013 ; Jackson et al., 2013 ; Perez-Felkner et al., 2019 ; St. Rose & Hill, 2013 ; Starobin et al., 2016 ), where women are more likely to take advantage of student services than men (Miller et al., 2006 ) and receive more benefit from the learning and advising experience (Packard et al., 2011 ; Starobin & Laanan, 2008 ). Women also perform better than men in entry level math courses at community colleges (Wolfle & Williams, 2014 ). Strayhorn and Johnson ( 2014 ) found that satisfaction among Black women with their community college experience is dependent upon background traits, age, faculty engagement, family responsibility, and grades. Age was reported as a particularly important factor, with older Black women reporting higher levels of satisfaction.

Research on the success of Black students in general suggests that high attrition is related to institutional factors, such as teaching philosophy, role models, faculty and peer interaction, and campus environment (Carroll, 1998 ; Holmes et al., 2000 ; Lang, 1992 ; Lewis & Middleton, 2003 ). A larger body of research encompasses the experiences of Black men in the transfer pipeline and confirmation of such institutional factors (Bush & Bush, 2010 ). Several studies have looked at the transfer process for Black students or Black male students (Berhane et al., 2020 ), but very little is reported in terms of the experiences of Black women.

Despite the promises offered by the community college setting, data on the success of transfer students is mixed, especially for Black women. For example, there is some question whether Black and Latinx students transfer to 4-year universities as frequently as White and Asian–American students do (Crisp & Nuñez, 2014 ; Malcom, 2010 ; Martinez-Wenzl & Marquez, 2012 ) and whether female students do so as frequently as male students (Dougherty & Kienzl, 2006 ; Surette, 2001 ). Nationwide data on the transfer and persistence of Black women from community colleges into 4-year university STEM programs are difficult to come by due to variances in reporting and definitions of persistence. Thus, we turn to data from administrative educational records in North Carolina, which we collected as part of our ongoing work. These numbers are based on longitudinal educational records of public school students who graduated from high school in 2004, then attended one of the sixteen public 4-year universities in North Carolina within the next 7 years. Table 1 includes the percentages of students in various categories who persisted to graduation after declaring a STEM major. Despite the suggested advantages of the community college environment, administrative records from the North Carolina high school class of 2004 show lower persistence rates from STEM major declaration to graduation for Black women transferring from community colleges than for Black women who began study at 4-year universities (40.7% vs. 64.8%). Moreover, the persistence rate for Black women transferring from community college is lower than for most other race*gender groups who make a similar transfer, with 50.0% of Latinas, 88.9% of Asian–American women, and 61.4% of White women persisting from STEM major declaration to graduation (authors’ calculations from class of 2004 educational records provided in Table 1 .).

When students find academic success in the community college setting it can also be difficult for them to translate that success to 4-year institutions due to a variety of institutional factors. Transfer students are very likely to feel the discrepancy between the supportive community college environment and a relative lack of support at the 4-year institution (Laanan & Jain, 2016 ). This experience is very common for all transfer students and is referred to as “transfer shock” (Hills, 1965 ; Ivins et al., 2017 ) and has also been studied for STEM-specific populations (Lankin & Elliott, 2016 ). There are limited studies as to how transfer shock may be racialized and gendered, but those that do exist suggest that, while many women of color receive the positive support needed during their time at community colleges (Reyes, 2011 ), their experience may have a significant negative shift after transfer. It is also possible that such transfer shock may be ameliorated by close working relationships between community college and 4-year university faculty (Jackson et al., 2013 ; Scott et al., 2017 ; Zamani, 2001 ), relationships that may be rarer with faculty from research-oriented predominantly White institutions.

In summary, though community colleges serve as a significant entry point for Black women in STEM, and there are numerous institutional factors that predispose the community college system to being supportive of entry, research is mixed on what role community colleges play in either providing or limiting access for Black women. This work aims at providing a rich qualitative accounting that highlights the community college and university experiences of seven Black women along their STEM transfer pathways.

Data and methods

Description of data set.

Analysis for this paper is based on a longitudinal set of in-depth interviews with students interviewed at two timepoints, 3 years apart. The subset of interviews we analyze in this paper is those with self-identified Black women who participated in the Roots of STEM–Community College interviews in the spring of 2015 and follow-up interviews in the spring of 2018. In 2015, we distributed a screening survey to students who were enrolled at one of eleven community colleges in North Carolina, chosen to represent both urban and rural portions of the state, as well as different regions. The screening survey went out via email to students who were enrolled as degree-seeking, or curriculum education, students; those who were taking continuing education classes were not recruited.

Approximately 3800 students from eleven community colleges responded to the screening survey. For interviews, we selected students who attended public school in North Carolina, were 18 years of age or older, and were planning to attend a 4-year university and considering a major in STEM. Of the respondents, about 480 qualified to be interviewed and indicated an interest in participating in the study. In selecting interviewees for the broader project, in which we investigate why there are persistent gender and racial inequalities among those who major in STEM fields, we aimed for overrepresentation of women and students of color to get information from a broad subsection of minoritized groups.

Potential interviewees were contacted via email to set up an interview (either via videoconference or phone). Interviewers were matched with interviewees by gender and race when possible. The interviews lasted between 30 min and 1 h and were audio recorded and transcribed. Students were paid $25 for participation in each interview. In total, we interviewed 120 students in 2015 who stated an interest in transferring to a 4-year university to earn a STEM degree.

The interview protocol for all students included general questions about their majors (“thinking back over the course of your life, what contributed to your becoming a _____ major?)”; their interest in science and how that interest changed throughout their lifetimes; questions concerning pedagogical experiences and interactions with teachers (“do you feel your high school math classes were taught well? Why or why not?”); science identity and confidence issues (“how have your feelings about your ability to do math/science changed over time?”); and questions concerning if/how gender and race influence STEM experiences (see Additional file 1 for examples of interview questions). All researchers had the latitude to use the interview protocol in a semi-structured fashion and to probe when an interviewee offered a particularly opaque or intriguing response to a question. At the end of the interview, respondents were asked whether they would consent to follow-up interviews in several years’ time, then asked to give additional contact information if they were interested.

About 3 years later, in the spring semester of 2018, the research team contacted the original set of interviewees to facilitate an additional interview with each. In this follow-up, we used different interview protocols depending on the respondent’s current educational status: out of formal education altogether; enrolled at community college; attending both community college and a 4-year institution; or enrolled (or graduated) from a 4-year university. We re-interviewed 68 of the 120 students from 2015. Once again, the semi-structured interview protocol allowed the interviewers some leeway in the order in which questions were asked. All other procedures with respect to interview recording, confidentiality, and interviewee compensation were identical to those used in the first wave of interviews. Of the 68 students that were interviewed at different times in their educational trajectory, seven identified as Black women.

Across protocols, there were some questions that were identical and some that were particular to the educational status of those being asked the questions. All respondents were asked questions about their academic experiences in community colleges, along with gendered or racialized educational experiences. For students who had left formal education, a section of the protocol focused on the reasons why they had decided not to pursue a 4-year degree in STEM. Students who were enrolled in 4-year universities or who had graduated were also asked about their academic experiences and social experiences at 4-year schools.

Analytic approach

The coding strategy we used was largely the inductive approach found in grounded theory (Glaser & Strauss, 1967 ). The research team worked together in an iterative process to develop a general coding scheme to be used as broad markers. The three first authors read the entirety of the set of interviews, then discussed emergent themes in those interviews, taking detailed notes during the discussion. Two overarching themes emerged that were particularly salient to the experiences of our interviewees. The first was experiences related to the classroom and campus environment and second their specific experiences with oppression.

The research team then iteratively coded and discussed individual interviews, until reaching agreement on what items should be coded as classroom and campus experiences, as well as experiences with oppression, including what respondents named as racism, sexism, and their intersections. Within these two broad areas, we identified themes that mapped onto Collins’ domains of power. Throughout, we found illustrative examples of how science is maintained as a venue that values the participation and contributions of White men above others: we call attention to these examples in the analysis.

For classroom and campus experiences we coded any mention of concepts closely related to institutional characteristics (e.g., campus size, climate), course structure (class size, format of instruction), class dynamics (e.g., interactions with teacher or students during class), personal interactions with instructors (e.g., availability, care, one on one interaction), and comparisons between the 2-year and 4-year experiences (e.g., discrepancies in teaching style, interactions, supports). Any mention of gender or racial issues or a combination thereof by the student was subsumed in the “oppression” category, to include discussions of racial composition in various majors, as well as educational experiences that the students perceived as being conditioned on their identities as Black women. Because we interviewed students before transfer, at a time when they were enthusiastic about majoring in STEM, we have greater confidence that the explanations that they give in later interviews for leaving STEM are not simply the result of attempts to emphasize positive experiences in other fields to allow themselves to maintain dignity in the face of having left STEM.

Positionality statement

The work presented here is the result of a multiyear, multigrant project spanning almost a decade of research devoted to understanding student experiences and academic trajectories in STEM majors, especially for students of minoritized groups, to inform practices that will create more equitable outcomes. All of the authors identify as middle-class women with four identifying as White and the other as Latina. Our professional experiences are largely centered in academia, teaching, and educational research. One of us is a community college chemistry instructor with a background in chemical education research, one has taught university level physics and has a background in physics education research, and the other three are university level social scientists that have extensive experience in researching STEM students’ success. Throughout our respective careers, each of us has sought ways to promote equity and contribute to the body of knowledge on racism and sexism. All the authors of this paper were involved in the study design and data collection, while the first three authors completed the majority of analysis and writing for this paper. Graduate student researchers also assisted with the interviews; they included three Black women, one Black man, and one White woman, all of whom moved on to non-academic employment by the time this paper was drafted. Interviewers were matched with interviewees by gender and race when possible. Acknowledging the analysis team was White and likely had some blind spots as a result, we engaged in multiple reflective conversations about potential alternative interpretations that we may have overlooked due to our positionality. We sought out an additional perspective by working with a paid consultant who is a Black middle-class woman with a physics background. She provided feedback on an early version of this work. Throughout the process, we have worked to ensure that the participants’ voices were amplified in our analysis.

Findings: student’s stories

Below we present summaries of each interviewee’s stories, highlighting significant impacts on their STEM trajectories. We follow with a detailed discussion of patterns in their experiences related to classroom and campus experiences and then a discussion of patterns in their experiences related to oppression.

Overview of participants

All seven of our participants started at the community college on track for a STEM major. They were all excited about their STEM futures and felt confident in their abilities to succeed. Discouragingly, by the second round of interviews 3 years later, they had all either left STEM, were planning to leave, or stated they wished they had left. There was not a woman left who was still in STEM and happy about it. These students reported many discouragements that ultimately led to their exiting the STEM trajectory. Few of these discouragements were driven by their social class, as the students represent various socioeconomic backgrounds, with several coming from families, where at least one of their parents had advanced degrees. Table 2 provides summary information about each respondent, which we elaborate on briefly below with an emphasis on the main reasons they gave for their STEM departure or desired departure.

Note that all names are pseudonyms.

Maya, Meghan and Tarana: out of STEM before transferring to a 4-year school

Of the seven students, three did not transfer to a 4-year school. Each of their stories is different. Maya, a first generation college student, talked more about art than STEM in her initial interview, wherein she expressed an interest in majoring in industrial engineering. At that point in time, she described science as “something that I am already talented at … I remember back when I was young I would just love to build stuff…. I would want to just work with my hands because I am really good with my hands.” She also attributed her pursuit of STEM to a mentor who shared her faith tradition and advised her to pursue engineering. Three years later, she had switched into industrial design after her community college helped her to better align her career path to her actual interests, stating “I transferred over from associates in science to associates in arts because I spoke to my transfer advisor and I realized that I can take that pathway because in industrial design you can either do it in science or art school …. So, I just choose arts instead of science.” Maya was still enrolled in community college and hoping to transfer to a 4-year institution.

Another student, Meghan, who entered confident and excited to pursue STEM, found her experiences at the community college diminished both her confidence and her interests in STEM and decided to pursue a non-STEM field. At the time of the first interview, Meghan expressed confidence in her abilities “I’ve been tested as academically gifted in math …. another one that comes very easy to me as well is science.” She stated she wanted to pursue STEM “because there aren’t many women in this field and, two, because there aren’t that many minorities and because of the job security that is allowed within that field as well…(and) my mom and my grandma because they were the ones who brought it up, … since these are your strong suits, why don’t you consider going into that field.” Meghan was the first person in her family to attend college. Although she had intended to major in chemical engineering and start her own cosmetics company, she took chemistry twice and found that it “sucked the life out of” her, which led her to consider “is this something I really want to do?” When interviewed the second time, Meghan was out of formal education entirely, working as an administrative assistant, and hoping to go back to school to become a physical therapy assistant.

The third student, Tarana, completed her associate’s degree but faced social class-related struggles in that she lacked the financial resources to continue to pursue a degree at a 4-year school. When interviewed in 2015, Tarana expressed an interest in pursuing a degree in computer science with a goal of becoming a website developer, “I want to be a web developer … and a degree in computer science will help me…. I had someone do a website for me and the girl that was doing it, she showed me a lot about building websites and I just thought it was amazing.” Three years later, she had completed her community college degree, but then ran out of money and was unable to continue her education. An older student with children, Tarana did not have the financial resources to cover the cost of attending a 4-year school and had been unable to find enough scholarship money for her tuition. It is also of note that she did not report any mentors or supportive faculty at her community college who may have been able to help find scholarships or other institutionally based sources of support to lower the barriers that her social class had introduced into her educational pathway.

Rosa and Serena: out of STEM after transferring to a 4-year school

Of the four students who transferred to a 4-year school, two had earned bachelor’s degrees and two were close to finishing. Three transferred into predominantly White institutions, while the fourth (Rosa) transferred to an HBCU but into a program that was dominated by White students. Two of these transfer students, Rosa and Serena, shifted their paths, earning degrees in non-STEM fields. Rosa aligned her interests and her path after learning more about her options. Serena started her pursuit of STEM confident and supported by her family and many positive childhood experiences. Yet, she reported significant discouraging experiences in STEM at the 4-year school, which led her to pursue a non-STEM field. Serena’s story is detailed in a later section due to its richness.

Rosa had initially intended to pursue a degree that would allow her to teach science, “I loved to watch The Magic School Bus and Miss Frizzle was just the coolest science teacher and she made me like science and that kind of just got me interested.” However, she misunderstood what path at the community college would lead her to a teaching career, thinking the required degree program was not available when she was initially enrolling. She then enrolled in a degree program (A.A.S.) at the community college that limited her options with regard to the type of majors she could pursue at 4-year institutions, as not all majors would recognize the credits she earned at the community college. She ended up pursuing agriculture education. Rosa’s family had other educated members, as at least one of her parents and a sibling had graduated from college and earned advanced degrees. Although her programs at the community college were dominated by White men, Rosa felt supported, stating “I had a lot of encouragement from my program chair” and the “hands-on work at (community college) was really rewarding and gratifying, it made me want to keep going.” The support Rosa received at her institution demonstrates the opportunities and responsibilities institutions have to impact the experiences of minoritized students. This is a perspective more fully illuminated by Collins’s ( 2009 , 2015 , 2019 ) domains of power framework, which we discuss in the analysis.

Kamala and Michelle: STILL in STEM after transferring, but with regrets

Two of the seven community college students in our original group of excited STEM pursuers were still in STEM: one had graduated and one was close to graduating. However, they both indicated they would have preferred a different path after becoming discouraged by university experiences. Only one student of the original seven, Kamala, was still planning to continue working in STEM but she spoke at length about the hostile environment for Black women. Although Michelle had graduated with a degree in biology, she was planning to leave STEM after attempting to work in the field and not feeling passionate about it.

Kamala reported pursuing computer science, because “I always had an interest in computers and I always played around computers when I was little… and there’s a lot of jobs out there for it too.” At the community college, she stated her interest in computer science only increased due to “meeting all my new friends that are into this program.” After transferring to a regional university and majoring in computer science, Kamala became discouraged, because “I was the only Black person there. I was the only Black female… I feel like I should have just taken something else.” Although she was still in computer science, Kamala expressed regret for her choice to pursue STEM and a lack of feeling of belonging. The dominance of White men in STEM and the corresponding near dearth of Black women creates a sense of isolation for students, such as Kamala. This is an example of a cultural power system in STEM, which we discuss more fully in the analysis section.

Like Kamala, Michelle had had an interest in science from an early age, stating she wanted to pursue biology, because “It’s really cool… I just always had an interest in science stuff since I was little” and growing up in a family with parents who had earned at least one college degree and an advanced degree. She had a difficult time thinking of any experiences in her life prior to 4-year university that discouraged her from STEM. However, after graduating from a 4-year university with a degree in biology, she wished she had majored in something else and was not intending to continue working in biology. She attributed her diminishing interest to her experience working in the field, stating, “after I graduated I actually worked at biology-related jobs… it was okay but I didn't enjoy it that much, so I ended up leaving the lab.”

Summary of participant trajectories

Two of the seven students left STEM due to stronger interests outside of STEM. Both of these students talked about these other interests in their initial interview and reported being happy with their trajectory when we last spoke to them. Neither of them recounted any significant discouraging experiences in STEM. While they did not stay in STEM, all indications are that community colleges helped them find a path that aligned more with their stated interests.

The other five students reported discouragements that likely worked toward narrowing opportunities for them and toward the maintenance of White and male dominance in STEM. The stories of these five students illuminate the dearth of Black women in STEM. None of them left, because they were not capable: rather, they encountered systemic discouragements that were related to their race and gender and were, in some cases, compounded by social class. We saw in Tarana the loss of a Black woman from STEM due to an inability to pay for college. Megan, Serena and Kamala all described classroom experiences that were largely alienating and uninspiring. Serena and Kamala additionally encountered significant sexism and racism in STEM at their 4-year colleges that left them discouraged. Michelle also discussed uninspiring classroom experiences and sexism but downplayed the significance of these experiences in her decision to leave STEM.

In listening to the stories of these Black women, two major themes emerged that offer insights into the great loss of Black women from the STEM trajectory: classroom and campus experiences that frequently eroded their passions and confidence, as well as sexism and racism that left them feeling alienated and discouraged. Below we discuss these two themes in more detail.

Findings: overarching themes

In analyzing the stories of our participants, two overarching themes related to climate and persistence emerged. The classroom environment, including connection to instructors and peers, played a significant role. In addition, participants described numerous experiences with sexism and racism in creating a hostile environment. Serena’s story was particularly well captured and exemplifies many of the overall themes we discuss in our findings. Her story is presented here as an extended example, highlighting the main findings discussed in greater detail following her story.

Serena’s story: driven from STEM by a hostile environment

Serena started her pursuit of biology at the community college, because she “wasn’t sure what I wanted to do after graduating from high school and it seemed better to go to a community college than to a 4-year school and spend a bunch of money.” She attributed her decision to pursue biology to many influences. These included: passion (“For Christmas I would ask for those little at home science kits that you could do, I had a microscope and stuff. I have always been interested in science.”), confidence (“I was always good at the science classes and the math classes.”), family role models and high school encouragement (“My mom, she is a computer engineer and my high school I went to was an engineering high school so I have been around STEM stuff my entire life.”), and the perception of STEM being a good career choice (“I will always have a job (by majoring in biology) … I do want to go into something that I love but also can pay the bills.”). Notably, in her first interview, when asked if any experiences stood out as discouraging her from majoring in STEM she replied “I honestly cannot think of any. I feel like my whole life has pushed me towards science and technology so I cannot really think of anything.”

At the community college, Serena mentioned only positive experiences that supported her pursuit of biology. Serena spoke about the science courses she took at her community college, stating she enjoyed them and that she felt her teachers cared about her and her success. “I have had really good teachers in all my science classes since I have been at {community college} … I think it is just a really good place to learn your general science classes rather than having to be in a really big huge class at a university… If you don’t understand something it is okay, {my teachers} make it feel like it is okay to ask questions and they make it seem like they are there for you, for you to learn and they make themselves available in that way.” Serena acknowledged the potential for both gender and racial differences in her major but did not express strong concerns about how she would be impacted. When asked about gender she expressed a pro-female bias stating “it is more expected for women to do biology.” In terms of race, she acknowledged there could be a negative impact stating “I guess it would be different just maybe how you interact with the other students in your class and how they interact with you and teachers just interactions within the classroom. They might view you differently because they aren’t expecting to see you there.” However, when asked if she felt she belonged she stated “I do” and when asked if she ever felt out of place she replied “no.” Serena’s experiences are consistent with our overall finding that at the community college, most students anticipated relatively mild impacts of sexism and racism in their trajectory (finding three).

When we spoke with Serena again 3 years later, the once confident and excited STEM student was no longer in STEM, having left to successfully obtain a degree in a social science major. Serena described an unwelcoming environment in biology at the 4-year university, where she transferred that caused her to leave STEM. When asked if her instructors enjoyed teaching she replied “No. None of them…because the school is like R1, research institute whatever the classification is. So, some of them, you know, they don’t want to be teaching there.” Again, Serena’s story is typical. Like others, once they arrived at university, the transfer students reported neutral to unsupportive relationships with teachers and advisors and decreasing social and academic interaction with peers. (Finding Two).

She also noted the impacts of racism and sexism on her departure. “One of the other things I tell people is they don’t prepare you for STEM being a person of color … people expect you to not know what’s going on or they don’t want to work with you… you don’t get the benefit of the doubt, when talking to teachers, when you need some sort of help with the assignment or an extension or something.” Serena went on to directly attribute her experiences to her decision to leave biology, “being a person of color it was going to be 10 times harder for me. It made me think how passionate I am about this? To put up with this. I decided I wasn’t. I love it but not that much.” Serena noted that her only discouraging experiences were after she transferred stating “While I was at {my community college} nothing deterred me from that path. In fact, I think I was actually encouraged… I was discouraged when I got to {my university}”. Serena’s increasing experiences with racism and sexism after transferring were consistent with all interviewees. After entering 4-year institutions, participants reported dramatically greater impacts of race and gender on their educational experiences. (Finding Four).

Throughout her second interview, Serena described a teaching environment in biology that was alienating and provides numerous examples of oppression. As will be addressed in the analysis, and similar to Kamala and Michelle, these feelings of not belonging are rooted in the system of power maintained by White men in STEM. However, Serena’s experiences in her social science major stand in sharp contrast. She reports that a professor in her new department told her “you as a Black woman, you would be so valuable in (social science field). Your perspective is not common and she was very encouraging with that track for me. She is an amazing teacher so it influenced me to switch over to (social science field).” And when speaking of her classes in her new major she spoke favorably saying “Once I got into (social science field), the class sizes were normal, like 20 people. Some classes were 7 or 5 people. It was really nice.”

Serena’s story exemplifies many of the themes we see in our interviews. She began her journey excited and confident, supported by the positive experiences of her schooling and a family that nurtured her interests. Throughout her community college enrollment she reports only positive experiences (Finding One), and does not expect to find racial and gender inequities that would disrupt her STEM pathway (Finding Three). However, upon transfer she experienced a hostile environment in biology (Finding Two). Much of that hostile environment was directly related to her race and gender (Finding Four), which caused her to abandon STEM for a major, where she felt more supported as a Black woman.

Classroom and peer experiences

In this section, we expand on Serena’s account with other interviewees’ experiences. Their accounts were generally in response to interview questions about how courses were taught both in terms of quality and methodology, whether instructors enjoyed teaching, and comparisons between their community college and university experiences. In this analysis, stark differences arose between students’ community college and university experiences.

Community college classroom and peer experiences

Finding One—While attending community college, students generally reported positive classroom environments leading to supportive relationships with instructors and peers.

The students in our sample generally described their community college experiences very favorably. Instructors were depicted as people that were passionate, enjoyed teaching, were helpful and worked with students until they got it. Each of the students in the sample characterized multiple science, math, and/or computer science classes as positive, even for those students that did not transfer. In addition, the students indicated they studied with their peers and felt respected. They felt that relationships with peers were overwhelmingly supportive and positive.

In speaking of their relationships with instructors and advisors at the community college, the students who transferred to a 4-year school recounted how their community college professors put extra effort into relationship building and activities that made the students feel they cared. For example, Kamala said her computer science instructors “really enjoy teaching and put [in] extra activities and also bring in other, extra people like job fairs and people come and talk with us, give us advice on what we should do when we leave college.” Serena also talked about the care for teaching of her professors at the community college and that she developed very supportive relationships with her math instructors that continued after transfer, “Some of them I still talk to, so I do think that they cared and do care about what is going on inside their classroom and the learning that is going on outside of their classrooms as well.” Likewise, Rosa reported a strong support system in her predominantly White male community college program, “I got an outpouring of support from the program. The program was super tiny and I was one of the very few girls and one Black girl. I never felt like my professors didn’t want me there or question why I was there.”

The students that did not transfer also reported positive community college experiences, even if they also struggled in a class. Maya stated that community college “had a positive impact on my life and education,” and her math instructors “were just positive every time they came to class and really just tried to help the students and it seemed like the class was more about learning than about grades.” During the first interview, Tarana mentioned a bad experience with her biology class, but during the second interview it was apparent that Tarana had taken more science classes stating “{the classes} were tough, but I learned a lot” and her “{chemistry} teacher was helpful… a good instructor.” Meghan reported the most negative experiences at the community college stating that both chemistry and pre-calculus “sucked the life out of her” and that her engineering class was not designed well. However, she said that her math teacher “was very passionate about the course material that she was teaching which made it more interesting to take the course,” and her biology instructor “was very enthusiastic.”

In terms of peer relationships, students that eventually transferred to a university described feeling connected to their peers at the community college. For example, Kamala “found a lot of friends in the STEM field… felt comfortable… and asked {them} questions. Or didn’t have to fake or anything if {she} didn’t know something.” Michelle felt very connected, socially, to her peers at the community college, saying “{we} usually form a group and study together; we do stuff together outside of school and everything; we volunteer.” When asked how often she socializes or studies with other students, Serena responded “Pretty often… every time I studied.” Rosa did not suggest a negative experience with peers, but she was less connected. She completed an associate’s program overwhelmingly dominated by White men and reported that she felt comfortable in the curriculum, but sometimes felt out of place socially. “I do sometimes feel out of place,” and socializing “never [happens] off campus, but on campus, we have small talk every day.”

Notably, the students that did not transfer did not report having much social interaction at the community college. Maya and Tarana felt the least connected in their community college experience due to taking online classes. For example, Tarana said “now that I am online everyone is working and doing their own thing, so nobody really has time [to socialize].” Meghan’s social experience was not consistent. She reported that she was not really connected and one “semester I was able to meet a bunch of [science majors] because I was in Intro to Engineering, but, as of lately, I don’t [socialize], I’m not entirely sure of how many I come into contact with.” However, Meghan felt like she belonged and did not feel out of place.

As shown here, the students mentioned overwhelmingly positive community college experiences with a small number of negative experiences often attributed to one bad class or a lack of interaction in the online environment. The students in this study did not point out any additional supports for Black women beyond the supports already in place for all transfer students. However, responses were consistent with the idea that positive relationships and support systems are important to success and persistence, particularly for traditionally marginalized groups. In sum, it appears that various aspects of the community college environment were structured for a broad cross section of students to succeed, in that most students felt enthusiastic and supported throughout their STEM coursework.

University classroom and peer experiences

Finding Two—Once they arrived at university, the transfer students reported neutral to unsupportive relationships with teachers and advisors and decreasing social and academic interaction with peers.

Environments in 4-year universities were a stark contrast to the previous experiences of the students who transferred. The students were likely to cite more instances of positive class discussions and instructor interaction in the community college classroom while speaking very little to very negatively about class formats at the university. Overall, the transfer students in the sample did not describe supportive relationships with faculty or peers at their university. In addition, the larger campus and class sizes exacerbated their feelings of being disconnected.

The transfer students often described the university environment in terms of large classes taught by instructors that did not care about teaching. They recounted being viewed as part of a larger group, rather than as individuals. This prevented students from developing the supportive relationships with instructors they had when at community college. Serena compared her university experience to her community college experience by saying “So, for one they were like way bigger. I went from being in class with twenty people to four hundred people.” This is consistent with Kamala’s experience, she said, “at {my university}, it’s like a big collection of people and they don’t really try to give you one on one attention.” When asked if her instructors at the university enjoyed and are interested in teaching, Serena stated,

“No. None of them… because the school is like R1, a research institute… So, some of them, you know, they don’t want to be teaching there. They want to do their studies [but] they have to teach the class… to get their money and that’s something that’s openly talked about by professors sometimes during classes.”

Rosa’s program was entirely online, which further hindered the development of supportive relationships as directly reflected in the statement, “I don’t have a real relationship with my professors…, but when I went to community college I just talked to my professors because they were right there. We talked about stuff that had nothing to do with the classes sometime. I don’t have that currently.”

Michelle was the only student that reported some positive experiences at the university. She said “Professors would take a lot of their time to really help us understand challenging concepts… and I really liked that.” However, she was more interested in the academic content of the course and did not elaborate on any specific relationships with instructors.

In terms of peer relationships, the findings are very similar to the lack of relationships with instructors found at the university level. Kamala’s interactions with peers were very limited, as she said, “I just go straight to class and go back home. I don’t really associate with a lot of people there, pretty much with anyone there.” When asked about how often she socializes with other students in her major, Serena reported, “not often at all. I have some friends [from a transfer orientation course]… some of them stayed in the biology program and some didn’t even stay [at the university]… there was no socializing with bio majors.” She went on to say “I thought biology at [university] would be something else than it was. It was a very huge program… There were 2500 students. Very impersonal and super competitive…it’s just not an environment to thrive in.” Rosa’s interaction was limited due to the nature of her online program at university. When asked about her ability to make relationships with students in her classes or major, she said, “I think it’s just harder because it’s online, so I just kind of do my thing.”

Again, Michelle’s experience was a little bit different. She transferred from a smaller, more rural community college that did not offer as much student life as the university and had a different perspective on the larger size of the university and the ability to build peer relationships. She said, “student life is very, very minimal at community college. But at [university] it’s very different. Obviously a bigger school… a lot of other students… more diverse… there’s a place for everyone.” It is also clear that study groups had a positive impact on Michelle’s adjustment: “something else that really helped me out was making study groups with some of my classmates… we were all able to relate with each other… I really depended on making study groups [which increased] my confidence.”

When compared to the overwhelmingly positive community college experiences, it is obvious that the students in our sample experienced varying degrees of transfer shock in finding an environment at the university that was generally not as positive. However, as highlighted by Michelle’s experience, better classroom environments and supportive relationships with peers are very important to the overall view of the transition. Where the community college environment was structured for a broad cross section of students to succeed, it is clear that the university environment is not particularly designed for the success of the same broad cross section of students, especially when it comes to Black women. In addition to the stark contrast in classroom and peer experiences, these students also described very notable differences in their racialized and gendered experiences as Black women on the transfer pathway. These differences are presented in the next section.

Racialized and gendered experiences

In reading the stories of these women collectively, their experiences with sexism and racism stand out as being influential to their trajectory, particularly for those students who progressed farther down STEM pathways by transferring to 4-year universities and pursuing STEM majors there. Below, we summarize overarching themes that emerged from an analysis of their reports specific to gender and race. Typically, interviewees made statements regarding gender and race in response to a series of questions that asked them about their perceptions of racism and sexism within their majors and how/whether their own experiences had been influenced by their racial and gender identities. These findings fall into two main categories: predictions of future sexism and racism and experienced sexism and racism. Together, these examples show how these types of oppressions combined to mark science as a comfortable environment for White men and markedly less comfortable for the Black women we interviewed.

Predictions of sexism and racism

Finding Three—At the community college, most students anticipated relatively mild impacts of sexism and racism in their trajectory.

While at the community colleges, students realized that they were heading into fields, where Black women were underrepresented, but they underestimated the extent of underrepresentation and remained confident that it would not affect their trajectories. For example, Tarana was planning to major in computer science when she transferred to a 4-year program and recognized that there would not be many women in STEM, but still thought that 25% of other computer science majors would be women and 20–25% would be Black. Overall, women earn about 18% of computer science undergraduate degrees and Black people earn 8.5%, with Black women accounting for 2.2% of the undergraduate degrees earned in computer science (NSF, 2019 ).

Only some of the interviewees foresaw major issues with respect to underrepresentation. They were all asked whether they thought the experience of pursuing their intended majors would be different for men and for women and for people of different racial groups. While four thought the experiences would be the same by both gender and race, others saw potential differences, stemming from societal expectations and existing gender underrepresentation. For example, Kamala thought that “women may not get a lot of opportunities as men will in computer programming” and was skeptical as to whether Black or Latinx students would be given the same opportunities as White and Asian–American students. Tarana was looking forward to getting a job with her intended computer science degree, even though she did “hear that there aren’t many women in STEM.” And Rosa questioned whether she would feel like she “fit in”, because “there might not be somebody who understands you” due to the underrepresentation of Black people in her agricultural major.

Thus, our interviewees only vaguely noted any potential impact of identity-based oppression in their educational trajectories in the future. However, it is important to note that they were familiar with the fact that their fields of interest were predominantly White and male. Importantly, while they were still enrolled at community college, none of the students thought that any of these potential issues would be sufficient to deter them from the STEM majors they were intending to declare at 4-year universities. None of the respondents mentioned noticing any such oppression in their community college experiences or was able to give any specific examples of experiencing or witnessing any oppression.

Experiences of sexism and racism

Finding Four—After entering 4-year institutions, participants reported dramatically greater impacts of race and gender on their educational experiences.

The second iteration of the interviews offered a particularly stark contrast between students who had not transferred to a 4-year institution and those that had. All of the students who ended their formal education with community college responded in the negative when asked whether gender and race had impacted their experiences within the context of higher education. When asked whether the experience of pursuing their intended majors is different for people of different genders, the students responded with vague notions that there is sexism. Tarana mentioned that “some men tell women that we are not smart enough to do {computer science},” but none detailed specific instances of sexism or it having an impact on their lives. Likewise, Meghan said that “it could be” that there is racism,” but none of the three who did not attend 4-year university offered specific instances or discussed any personal impacts. For example, when asked whether her experiences had been impacted by race, Tarana responded, “I don’t think so. I try not to think about that. I just do what I do.”

Meanwhile, the four students who did transfer to 4-year institutions offered specific instances of how bias played a role in their educational careers as Black women. Interviewees reported numerous instances of sexism and racism at the university. Most notably this included: assumptions they were not competent, messages they did not belong, being ignored, and being talked over. These racist and sexist acts came from both teaching staff and their fellow students. All of the instances described here decreased these students’ sense of belonging within their STEM majors and contributed to their exits from STEM. It is important to note that these processes are intertwined, such that the assumptions of incompetence are sometimes manifested in a tendency of others to ignore or talk over Black women in STEM. These Black women perceived issues with respect to their gender, racial, and intersectional identities at 4-year universities for the first time: none mentioned encountering similar issues at community college.

Interviewees frequently confronted others’ views that they were not competent, as did the graduate students described in Wilkins-Yel et al. ( 2019 ). Serena described how there was “overshadowing…with male counterparts.” She discussed how the male teaching assistants in the lab would “invalidate…viewpoints or questions.” Serena noted that these issues were especially acute in lab settings, where students are collecting data and where they are “measuring stuff or having to do calculations,” and said that there were certain lab courses, where the sexism was worse than others. In these labs, Serena felt that her voice was not heard and that her expertise and skills were devalued.

Michelle had a similar experience with a teaching assistant. When asked whether anyone in biology has encountered sexism, Michelle said, “yes,” and then went on to describe an experience with a lab instructor who would “treat the guys differently than the girls.” She mentioned that this instructor would act in the following way:

“Let's say I made a mistake or read something wrong ... he would be very, very hard on me and say ... why don't you know this, you should know this or this is a waste of my time. But let's say if a guy does the same thing in the lab, he would be open to explaining to them what's going on and why they're wrong.”

In these interactions, Michelle experienced both a delegitimization of her skills by the lab instructor and an implicit message that communicated a lack of belonging in STEM, both of which Wilkins-Yel et al. ( 2019 ) describe as micro-aggressions that students of color experience.

Messages that they did not belong in STEM were sometimes implicit, stemming from the fact that there simply were not many other Black women in these fields. Interviewees discussed how “lonely” it was to be a distinct minority in that they were frequently the only woman of color in given fields or given classes. Serena talked about how “it was going to be 10 times harder” for her to complete a biology major and to work in the biology field “seeing that it is dominated by… White men.” Kamala described the “crap [she] had to deal with” in the computer science field and how being the only Black woman was a discouraging factor that kept her from wanting to pursue a degree in computer science. She went on to say that because she didn’t “look like the average person,” she did not feel as if she belonged in her major and that her classmates stereotyped her as “a ghetto type Black girl”, because she was the only Black woman. Moreover, she felt like, “every single day I go into the class, I always got to prove myself,” a pressure that was particularly acute, because she was the only Black woman in her classes.

Sometimes, these Black women found that they were ignored by other members of the STEM community. For instance, Kamala, a computer science major, said that her gender and race impacted her experiences because of her classmates, whom she described as being “discouraging” and “honestly not trying to listen to my view when I am trying to speak or act like I don’t know what I am talking about.” These microaggressions then led her to question her sense of belonging. She went on to say that in class debates “they don’t really care that a Black person is speaking up or try and consider their viewpoint.” In this instance, she was describing how her professors and fellow students ignored her voice. Serena said she felt “talked over and doubted,” especially in the labs that she mentioned above.

Kamala further described an instance, where her physical presence was also ignored, and then questioned. She recounted an experience with a professor who had told her to come by his office for extra help. When she arrived there, he “thought I was the wrong person. Like said, ‘are you sure you are in the right department and not nursing?’” When faced with a Black woman, this professor thought that she did not belong in computer science and was looking for help in the wrong department, thereby communicating to Kamala his opinion that people who looked like her had no place in computer science. Kamala noted that this interaction was discouraging and made her “not even want to ask the question anymore.” Here, Kamala experienced a type of discrimination stemming from the intersection of her race and gender.

All of these micro-aggressions—being ignored or talked over, assumptions of incompetence, and messages Black women do not belong—are summed up in Serena’s experience. After starting her 4-year college experience as a biology major, Serena left that major for a social science field and graduated with a degree in that social science. As she was considering switching, a professor in her social science major had told her how valuable her perspective was. In contrast, she noted the uninviting climate in biology, from both students and professors. Professors doubted her competence: Serena said that Black students would not “get the benefit of the doubt… when you need some sort of help with the assignment or an extension or something.” From other students, she described a pattern of interaction, wherein students of color “can have a harder time just being approached by other students or even kind of experiencing resistance from your professor or TA, unless the TA is a person of color.”

Serena described struggles with other students that conveyed messages that she did not belong and ignored her voice. These struggles included “people not wanting to work with you,” and Serena characterized them as being more pronounced in interactive situations (i.e., labs) than they were in lecture sections. This example of being talked over, having her competence questioned, and conveying that she did not belong occurred in the last class that she took before dropping her biology major:

“The final shock for me was, I had a lab and it was like me and two White guys and a White woman and one of the guys… didn’t talk very much. The other White guy was older and… would talk over me and the other young lady in our lab group… It was literally just me and him contributing ideas. We were cutting things and examining stuff and if I made a point and said, ‘this is this, I am identifying the body part or whatever,’ and he would always challenge it and call over the TA to settle a dispute. I happened to be right and he would just be, ‘okay, let’s move on,’ but if it was him being right, he would be like, ‘I knew I was right’ and making a big deal out of it and it was like he would challenge me in ways that he did not challenge anyone else in the group even though he spoke over the other young lady and she was adamant but he wouldn’t call the TA over to ask a question.”

Here, Serena experiences racialized and gendered experiences in the classroom and labs as the outcome of her intersectional identity as a Black woman. These experiences with peers and professors combined to drive her out of her STEM major, despite the enthusiasm for the field that she had prior to transferring to a 4-year university.

Our four major findings can be briefly summarized as: (1) students’ experiences at the community college were generally reported to be positive and supportive; (2) after transferring to the university they experienced a generally negative and unsupportive environment; (3) while attending community college, they reported few racialized or gender experiences and anticipated few after transferring; and, (4) once at the university, they encountered substantial racist and sexist experiences that were directly related to their decisions to leave STEM.

Our seven interviewees started on their path toward a bachelor’s STEM degree in community college excited and feeling confident in their ability to succeed. Consistent with current data indicating Black women are generally excluded from STEM (NSF, 2019 ), none were still in STEM without regrets 3 years later.

Two students (Rosa and Maya) described experiences and mentoring at the community college that led them to leave STEM for a field they felt was more aligned with their interests. Neither of these students felt discouraged in their STEM path; rather they simply found other fields that held more interest for them. All indications are that the mentoring they received at the community college helped them down a path that was perhaps better suited for their interests. While these students did not ultimately follow through with the interest in STEM, the nature of their departure does not raise concerns. The other two students who dropped off the STEM path during their community college experience encountered more troubling barriers. Tarana successfully completed her associate’s degree, but did not transfer due to a lack of financial resources and Meghan reported discouraging experiences in her community college chemistry and math courses, academic struggles that are somewhat common for students in those entry-level STEM courses (Cohen & Kelly, 2019 ).

Most concerning of all were the experiences of the three women (Serena, Kamala, Michelle) who earned associate’s degrees at community college and transferred to university still excited and confident in their STEM trajectory. All of these women reported a lack of supportive relationships, alienating classroom experiences and a chilly environment, related to their identities as Black women, that discouraged them to the point of either leaving STEM or staying in STEM but regretting their chosen path. The stories of these seven women align with data indicating that the environment for Black women in STEM is dismal and indicate that race, gender, and their intersections play a significant role in their departure from STEM.

Domains of power analysis

Analyzing our findings through the lens of Collins’s ( 2009 , 2015 , 2019 ) Domains of Power perspective illuminates a multitude of ways that science, writ large, is structured in such a way as to disadvantage Black women, among others. Of note is that we find these power structures to be significantly more pronounced at the university than at the community college. We apply Collins’s framework, because it provides a powerful way of reframing our inductively derived findings into a larger framework that directly points toward systemic solutions.

Below we consider findings through the lens of each of the four domains. Table 3 provides a summary.

Interpersonal domain—interactions between individuals

Our participants talked extensively about interactions with peers and instructors. Their reflections provide extensive documentation of the way power is exerted in the interpersonal domain to the detriment of Black women. When participants were at the community college, they mostly spoke positively of their interactions with both their classmates and their instructors. They reported being treated respectfully and feeling both their classmates and instructors valued them and supported their goals. They experienced few microaggressions or otherwise discouraging interpersonal interactions. In contrast, at the university, interviewees described significant negative interactions with both peers and instructors. University STEM instructors were typically characterized as not caring and discouraging. Both instructors and peers were frequently described as ignoring and talking over Black women. Our participants also recount numerous instances of instructors and peers making comments indicating they held views of these women being incompetent and unexpected in STEM. Participants indicated they were frequently socially isolated and invisible. These repeated negative interactions led our participants to be “fed up” with the environment of STEM.

Structural domain—institutional structures

Participants identified a number of structural elements in their experience that serve to maintain the White and male dominance in STEM. At the community college they spoke of small classes, where teachers knew them as individuals and made time to encourage and mentor students. At the university, in contrast, they identified large impersonal classes as problematic, where one-on-one attention was rare. They described courses as being taught without attention to students’ learning needs and without care if students did not succeed or left the major. In addition, they identified the lack of other Black women in their programs as creating an uncomfortable and unwelcoming environment.

Disciplinary domain—rules and enforcement

We find little in our data to speak to the disciplinary domain at the community college other than to note that very few problems were identified at the community college to which problematic elements in the disciplinary domain would be relevant. At the university level, participants spoke of many incidents of sexist and racist behavior of peers and instructors. There were no consequences when peers or instructors engaged in disrespectful and alienating behavior. There were also no mentions of action on the part of those in authority to set expectations of interpersonal behavior. There was a pervasive disregard for any enforcement of respectful and inclusive behavior related to racial and gendered interactions.

Cultural domain—expectations and norms

If science is regarded as being primarily the province of White men in American culture, then institutions need to take actions to counter those assumptions. Instead, Black women described cultural climates at universities, where there was little, if any, challenge to that notion. Participants described a culture at the community college in which teaching was valued and students felt it was acceptable to not understand and to ask for help. They felt valued by their instructors and their peers as a presence in STEM. At the university, on the other hand, they report a highly competitive environment, where teachers did not care about students’ learning. They spoke at length about a culture that does not view Black women as knowledgeable and competent in STEM. They also described not feeling they belonged in the environment at the university which was attributed in part to a sense that other students and instructors did not consider that Black women belonged in STEM.

Analysis through the lens of Collins’ Domains of Power framework shows a pervasive system of power which reinforces inequity through both action and lack of action. We end with recommendations for change that are illuminated by our analysis.

Recommendations

Recommendation 1—systemic sexism and racism in stem is at the core of the dismal representation of black women and must be acknowledged and addressed.

Racism and sexism create a hostile environment for Black women in STEM. Fairness and equity depends on explicitly acknowledging and addressing the discrimination, harassment, and microagressions Black women encounter to achieve justice.

The women in our study entered study in STEM passionate and confident, and they demonstrated their ability to succeed as they progressed. Though they underestimated the extent of their underrepresentation and the sexism and racism they would encounter, they understood the path they were on would be more difficult for them due to their gender and race. They accepted this challenge and were willing to rise to meet it. However, the extent of the hostile climate they faced ultimately contributed to pushing them out of STEM majors and/or careers. It is also important to note the pervasiveness of this hostile climate, with racist and sexist actions and attitudes coming from peers, teaching assistants, and professors and being enacted through all four of the power domains: interpersonal, structural, disciplinary, and cultural.

The first step toward addressing racism and sexism in STEM is to acknowledge it exists. However, many of those in STEM, especially those who are the majority, i.e., White men, fail to recognize the existence of racism and sexism (Dancy et al., 2020 ). Furthermore, when they do recognize differential impacts they tend to attribute these to how those in the marginalized group “feel”, i.e., lacking confidence, interest or sense of belonging, consistent with a deficit model of understanding inequity (Davis & Museus, 2019 ), rather than attributing impacts to systemic racism and sexism. It is essential to shift the dialogue to place causal responsibility more appropriately. As we saw in our interviews, these women left STEM due to hostile interactions, not because they lacked ability, confidence, or motivation.

While much attention is given to increasing persistence for various minoritized groups in STEM, efforts to address inequity tend to focus on changing those who are marginalized (i.e., tutoring, scholarships, mentoring, etc.) rather than on changing the social and cultural structure that create an inhospitable environment (Fox et al., 2009 ; Grunspan et al., 2016 ; Malcom & Malcom, 2011 ; Ong, 2005 ). While these efforts can be helpful and are well meaning, they are unlikely to result in significant change. Furthermore, they can have the detrimental impact of sending the message that marginalized groups should be more like the dominant group, that the norms of the dominant group are superior (Ong, 2005 ; Simon et al., 2017 ; Tate & Linn, 2005 ).

Our findings support the need for efforts to address systemic racism and sexism in STEM, particularly at the university level. We note that the students in this study generally reported positive and supportive experiences at the community college and encountered the most sexism and racism after transferring. The experiences of the women in this study highlight a need to go beyond providing structures to strengthen members of marginalized groups to actively acknowledge and work to dismantle the racist and sexist environment that undermines their success.

Recommendation 2—Behaviors of mentors and professors can significantly support or undermine the success of Black women in STEM. Until systemic sexism and racism is eliminated, it is essential that marginalized students are provided substantive opportunities to form supportive relationships with instructors and peers

Almost all of the interviewees had supportive relationships with instructors and peers at the community college. These relationships helped the students to succeed in the classroom and to maintain interest and motivation in studying STEM, even when other obstacles presented themselves. Their experiences are echoed in the copious literature on the unique role that community colleges can play in supporting students, and especially students from marginalized groups (Jackson et al., 2013 ; Jorstad et al., 2017 ; Starobin & Laanan, 2008 ; Starobin et al., 2016 ).

Yet once they transferred to 4-year universities, the students lost those supportive relationships. There did not appear to be a university mechanism to facilitate the formation of those types of relationships. Much of the university context, especially the competitiveness within the major and large class sizes with lecture-based instruction, seemed ideally situated to prevent the formation of supportive relationships between students, peers, and faculty. In addition, faculty behavior does not have to be overtly hostile to result in an unwelcoming environment. As we saw in the experiences of our participants, when faculty do not overtly attempt to connect with students, or when they give the appearance of not caring about the students or their learning, this lack of action can have a detrimental impact.

There is variability in the extent to which universities exhibit an environment that is receptive to transfer students. The difficulty in navigating the change in environment is well-established in the concept of transfer shock (Hills, 1965 ; Laanan, 1996 , 2001 ). However, the experiences of the students in our study emphasize the extent to which that transfer shock can be exacerbated by racial and gender minority status in addition to an environment that is already unwelcoming due to their minoritized status.

The STEM transfer pipeline has been under more intense study for the past decade, leading to the development of programs designed to increase retention of STEM transfer students. Such university programs have implemented many of the supports found in the community college setting like intentional advising and mentoring in addition to customized orientations and undergraduate research and have been shown to be effective in improving performance and satisfaction of transfer students (Jackson & Laanan, 2011 ; Johnson, 2011 ; Ong et al., 2011 ; Thomas et al., 2018 b; Thomas et al., 2018 a). However, many of these programs focus on the overall transfer population. University STEM programs must look at the disaggregated data on Black female students and develop programs designed to build supportive relationships and foster retention and success. For example, the opportunity to make personal connections with other Black female STEM students and professionals can increase STEM confidence (Smith, 2016 ). Accountability practices are also a critical component of transfer programs, especially those that revolve around equity (Bensimon & Harris, 2007 ).

Community colleges can offer a supportive environment and viable pathway for Black women early in the STEM academic trajectory, but 4-year institutions must implement mechanisms to foster relationships and supportive structures for Black women transfer students.

Recommendation 3—Instructors should pay explicit attention to student–student interactions and disrupt sexist and racist behaviors

Our participants frequently identified interactions with their peers as being problematic, especially after transferring. Of note, they spoke of being ignored or treated in a condescending manner by peers during assigned group activities (such as lab work). And also of note, they reported very few positive and supportive interactions with peers in their STEM courses after transferring. In several cases, the large class sizes students found in university-level STEM courses exacerbated difficulties in making positive peer connections.

We are not the first to recount this pattern. Repeatedly, studies of women of color in STEM note they experience significant isolation due to being unacknowledged and ignored by peers, for example by being overlooked as lab partners or being consistently left out of study groups (Johnson et al., 2017 ; Ko et al., 2014 ; Ong, et al., 2018 ). In contrast, studies indicate that having strong peer support (Chang et al., 2014 ; Ong et al., 2011 ) and being recognized as competent (Carlone & Johnson, 2007 ) are important factors for persistence and success.

As discussed above, active learning based pedagogies have the potential to improve outcomes for marginalized students (Beichner et al., 2007 ; Freeman et al., 2014 ; Haak et al., 2011 ; Prince, 2004 ). However, while increased student–student interactions offer the promise of improved learning and opportunities to develop positive peer supports, they can also be a source of hostility and discouragement, as our participants spoke to. It is clear from the stories of our participants, as well as others, that peer interactions are a mechanism by which the ownership of science is maintained as White and male.

If instructors do not explicitly confront and disrupt problematic behaviors in group interactions in their courses they are complacent participants in creating a hostile racist and sexist environment, which in turn reinforces STEM as a White and male space. An example of how instructors can disrupt racist and sexist peer–peer interactions is provided by Johnson ( 2020 ) in her study of a physics department, where women of color describe a positive climate. She reports that in this department with a supportive culture,

Faculty members expect students to work in groups, but they don’t leave this process to students. … a faculty member told me about working with a student who was dominating group work during a lab. He was controlling all the materials, so she told him he had to let other people have a chance, at which point he backed up and stood far away from his group. She told him he didn’t have to stand so far away and that he was either dominating the group or not participating. According to this faculty member, she said “You can’t only participate when you’re building, that’s not OK. It can’t be ‘I’m either in charge or I’m out of here, guys.’”... One faculty member told me about dealing explicitly with issues of gender and group work when giving students feedback. She was dealing with a situation in which two male students were in a lab group with a woman, and they almost entirely excluded her from participation …. After the lab ended, the faculty member talked with all three of them about it. ( Johnson, 2020 , pp. 53-80)

Furthermore, until racist and sexist systemic and cultural structures in STEM are dismantled, marginalized students will benefit from the availability of counterspaces (Ong et al., 2018 ). Counterspaces are safe spaces, where students can find support and a haven from hostile interactions. Ong offers a number of suggestions for types and ways these spaces can be nurtured.

The stories of the seven women we share here indicate that there are significant systemic forces that work to exclude Black women from STEM, despite their interest, passion and willingness to persevere through challenges. Using the Collins ( 2009 , 2015 , 2019 ) Domains of Power framework to identify structures that contribute to that underrepresentation of Black women, we are able to make specific recommendations aimed at tackling systemic racism and sexism at the college level, particularly after transfer to the university.

While both 2-year and 4-year institutions may experience similar academic challenges with preparedness and gate-keeping courses, the community college, with its smaller classes, focus on teaching, and greater student diversity, has the potential to offer a supportive environment for Black women, as our participants reported. In contrast, at the university we have highlighted structures that exclude Black women from STEM including: significant racism and sexism, lack of sufficient supportive relationships, and poor quality lecture-based teaching. We posit that each of these identified discouragements provide a mechanism for addressing inequity.

Availability of data and materials

The data sets generated and/or analyzed during the current study are not publicly available due to the terms of our data management plans with the National Science Foundation but are available from the corresponding author on reasonable request. They will be publicly available in the future.

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We thank Yolanda Kennedy, Alicia Patrick, Sabrina Brown, Tiffany Hollis, and Ricardo Bailey for their participation in research process as interviewers and Apriel Hodari for her extensive feedback.

This work was supported by the National Science Foundation under grant # NSF-DRL 1420363. It represents the design of the study, as well as data collection, analysis, and interpretation of the authors, not the National Science Foundation.

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Allen, D., Dancy, M., Stearns, E. et al. Racism, sexism and disconnection: contrasting experiences of Black women in STEM before and after transfer from community college. IJ STEM Ed 9 , 20 (2022). https://doi.org/10.1186/s40594-022-00334-2

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• Women and Men in STEM Often at Odds Over Workplace Equity

Perceived inequities are especially common among women in science, technology, engineering and math jobs who work mostly with men

Table of contents.

• 1. Diversity in the STEM workforce varies widely across jobs
• 2. Most Americans believe STEM jobs pay better, but few see them as offering more flexibility for family time
• 3. Women in STEM see more gender disparities at work, especially those in computer jobs, majority-male workplaces
• 4. Blacks in STEM jobs are especially concerned about diversity and discrimination in the workplace
• 5. Most Americans evaluate STEM education as middling compared with other developed nations
• 6. Many Americans say they liked math and science in school, thought about a STEM career
• Acknowledgments
• Methodology
• Appendix: Detailed tables and charts

For women working in science, technology, engineering or math (STEM) jobs, the workplace is a different, sometimes more hostile environment than the one their male coworkers experience. Discrimination and sexual harassment are seen as more frequent, and gender is perceived as more of an impediment than an advantage to career success. Three groups of women in STEM jobs stand out as more likely to see workplace inequities: women employed in STEM settings where men outnumber women, women working in computer jobs (only some of whom work in the technology industry), and women in STEM who hold postgraduate degrees. Indeed, a majority of each of these groups of STEM women have experienced gender discrimination at work, according to a nationally representative Pew Research Center survey with an oversample of people working in STEM jobs.

These findings come amid heightened public debate about underrepresentation and treatment of women – as well as racial and ethnic minorities – in the fast-growing technology industry and decades of concern about how best to promote diversity and inclusion in the STEM workforce. Conducted in the summer of 2017, prior to the recent outcry about sexual harassment by men in positions of public prominence, the Center’s new survey findings also speak to the broader issues facing women in the workplace across occupations and industries. 1

Compared with those in non-STEM jobs, women in STEM are more likely to say they have experienced discrimination in the workplace (50% vs. 41%). But in other respects, the challenges women in STEM face in the workplace echo those of all working women. Women in STEM and non-STEM jobs are equally likely to say they have experienced sexual harassment at work, and both groups of women are less inclined than men to think that women are “usually treated fairly” when it comes to promotions where they work.

Pew Research Center analysis of U.S. Census Bureau data since 1990 shows that while jobs in STEM have grown substantially, particularly in computer occupations, the share of women working in STEM jobs has remained at about half over time. But the share of women varies widely across the 74 standard occupations classified as STEM in this study – from under one-in-ten for sales engineers (7%) and mechanical engineers (8%) to 96% of speech language pathologists and 95% of dental hygienists. Women are a majority of those working in health-related occupations but just 14%, on average, of those in engineering jobs. In computer occupations, a job cluster which includes computer scientists, systems analysts, software developers, information systems managers and programmers – the STEM job cluster that has seen the most growth in recent decades – women’s representation has actually decreased from 32% in 1990 to 25% today.

Blacks and Hispanics are underrepresented in STEM occupations relative to their share in the U.S. workforce. The share of blacks working in STEM jobs has gone from 7% in 1990 to 9% today (blacks make up 11% of the total U.S. workforce today). And that for Hispanics has gone up from 4% to 7%, while their share of the U.S. workforce has grown from 7% in 1990 to 16% today.

The survey finds a higher share of blacks in STEM jobs report experiencing any of eight types of racial/ethnic discrimination (62%) than do others in STEM positions (44% of Asians, 42% of Hispanics and just 13% of whites in STEM jobs say this). They also tend to do so more than blacks in non-STEM jobs (50%), with many saying they have been treated as if they were not competent because of their race or ethnicity. 2 Blacks in STEM jobs are particularly likely to say there is too little attention to racial and ethnic diversity where they work (57%). And, when it comes to the way opportunities for advancement and promotion are handled in their own workplace, 37% of blacks in STEM jobs believe that blacks are usually treated fairly, while a similar share (36%) says this sometimes occurs and 24% believe that blacks are usually treated unfairly where they work. Among Hispanics, those in STEM and non-STEM jobs are equally likely to say they have experienced racial/ethnic workplace discrimination.

These are some of the findings from a Pew Research Center survey with a nationally representative sample of 4,914 adults (including 2,344 STEM workers), ages 18 and older, conducted July 11-Aug. 10, 2017 and a Pew Research Center analysis of U.S. Census Bureau data. The survey, conducted online in English and in Spanish, included an oversample of employed adults working in science, technology, engineering and math fields. See Methodology for details.

Most women in STEM jobs who work in majority-male workplaces, in computer jobs or who have a postgraduate degree have experienced gender discrimination at work

On average, women working in STEM jobs are more likely than men to say they have experienced workplace discrimination due to their gender. Half (50%) of women in STEM jobs say they have experienced any of eight forms of discrimination in the workplace because of their gender – more than women in non-STEM jobs (41%) and far more than men in STEM occupations (19%). The most common forms of gender discrimination experienced by women in STEM jobs include earning less than a man doing the same job (29%), having someone treat them as if they were not competent (29%), experiencing repeated, small slights in their workplace (20%) and receiving less support from senior leaders than a man who was doing the same job (18%).

In workplaces where most employees are men, about half of women in STEM say their gender has been an impediment to success on the job

Pioneering work from business school professor Rosabeth Moss Kanter in the late 1970s drew attention to how the structure of organizations – particularly the balance of minority and majority groups – can influence experiences in the workplace.

The majority of women in STEM positions work in majority-female workplaces (55%) or work with an even mix of both genders (25%). But the 19% of women in STEM who work in settings with mostly men stand out from others. Fully 78% of these women say they have experienced gender discrimination in the workplace – compared with 44% of STEM women in other settings. 3

About half (48%) of women in STEM jobs who work with mostly men say their gender has made it harder for them to succeed in their job, compared with just 14% of other women in STEM.

One respondent explained it this way:

“People automatically assume I am the secretary, or in a less technical role because I am female. This makes it difficult for me to build a technical network to get my work done. People will call on my male co-workers, but not call on me.” – White woman, technical consultant, 36

Gender balance in the workplace also tends to matter for women in non-STEM positions but those in STEM stand out especially when it comes to experiences with workplace discrimination, the feeling that they need to prove themselves in order to be respected by coworkers, and their belief that, overall, their gender has made it harder for them to succeed at work. By contrast, for male STEM workers, the gender balance in their workplace is largely unrelated to views about gender equity. 4

There are similar differences, though less pronounced, among women in STEM jobs by their level of education. Women with a postgraduate degree who work in STEM jobs are more likely than other women in STEM to have experienced gender discrimination at work (62%, compared with 41% of women with some college or less education). Roughly a third (35%) of women in STEM with a postgraduate degree believe their gender has made it harder to succeed on the job, compared with just 10% of women in STEM with some college or less education. And, women in STEM with more education are more skeptical that women where they work are usually treated fairly when it comes to opportunities for promotion (52% of those with a postgraduate degree say women are usually treated fairly vs. 76% of women with some college or less working in a STEM job).

Roughly three-quarters of women in computer jobs say they have experienced gender-related workplace discrimination

Some 74% of women in computer jobs, such as software development or data science, say they have experienced discrimination because of their gender, compared with 16% of men in these jobs. 5 (This group includes some who work in the tech industry and some who work in other sectors.) 6

Women in computer jobs are less likely than men in such jobs to believe that women are “usually” given a fair shake where they work when it comes to opportunities for promotion and advancement (43% of women in computer jobs say this usually occurs, compared with 77% of men).

About one-in-five women in STEM and non-STEM jobs say they have experienced sexual harassment at work

In the Pew Research Center survey – conducted before the string of prominent sexual harassment allegations and public discussion of these issues on social media outlets and elsewhere – some 22% of working women in the U.S. say they have experienced sexual harassment at work, compared with 7% of working men. The share of women who say they have experienced sexual harassment at work is the same among those in STEM and non-STEM jobs. 7

Women working in STEM are more likely than their male counterparts to regard sexual harassment as at least a small problem in their workplace (36% vs. 28%). As with experience with discrimination, women in STEM jobs who work in majority-male settings and women in computer jobs are particularly likely to say that sexual harassment is at least a small problem where they work. Nearly half (48%) of female STEM workers in majority-male workplaces say that sexual harassment is a problem where they work. About four-in-ten (42%) women in computer jobs consider workplace sexual harassment a problem where they work, compared with three-in-ten (30%) men in computer jobs.

Among those in non-STEM occupations, men and women are equally likely to consider sexual harassment a problem where they work.

About six-in-ten blacks working in STEM say they have experienced workplace discrimination because of their race

Concerns about the underrepresentation of blacks and other racial minorities – and particularly women of color – in the STEM workforce have been ongoing for at least four decades. 8  The Pew Research Center survey finds that, today, black STEM workers are especially likely to say they have experienced discrimination at work because of their race or ethnicity; 62% of blacks in STEM say this, compared with 44% of Asians, 42% of Hispanics and just 13% of whites in STEM jobs.

Blacks in STEM jobs tend to report experiences of workplace discrimination due to race more than blacks in non-STEM jobs (62% vs. 50%). 9 Hispanics in STEM and non-STEM jobs are equally likely to say they have experienced workplace discrimination because of their race or ethnicity (42% each). 10

And, blacks working in STEM jobs are less convinced than white STEM workers that black employees where they work are treated fairly when it comes to hiring and promotions. In all, 43% of blacks in STEM jobs believe that blacks where they work are usually treated fairly during recruitment; 37% say this is the case during promotion and advancement opportunities. By contrast most white STEM workers believe that blacks are usually treated fairly in these processes where they work (78% say this about hiring, 75% about advancement processes).

Other Pew Research Center analyses found that black Americans with at least some college experience are more likely to say they have experienced discrimination or been treated unfairly across a range of experiences because of their race or ethnicity, compared with those without any college experience. (There are not enough blacks in STEM jobs in this survey for analysis by levels of education.)

While the majority of STEM workers believe their race or ethnicity has made no difference in their ability to succeed in their job, blacks (40%) and Asians (31%) in STEM jobs, followed by Hispanics (19%), are more likely than white STEM workers (5%) to say it has been harder to find success in their job because of their race or ethnicity.

STEM workers who believe their race or ethnicity has made it harder to succeed provide a number of explanations, including concerns about the hiring process, promotions and pay equity, and stereotypical beliefs among their coworkers. Some respondents put it this way:

“People have preconceived ideas of what I am capable of doing.” – Black man, physical scientist, 39

“This ‘other-ness’ exists intentionally or unintentionally between those of a minority and those of a majority from lacking of common cultural background. Relationships at work appear polite on surface but reluctant tendency in willing to share limited opportunities the same way, which I felt in a previous job where whites and males were overwhelmingly a majority.” – Asian woman, engineer, 56

The STEM workforce has grown, especially among computer occupations

Analysis of the U.S. Census Bureau’s American Community Survey shows that employment in STEM occupations has grown 79% since 1990 (from 9.7 million to 17.3 million) with the largest growth occurring in computer occupations (338% growth since 1990).

The share of women working in such jobs varies widely both within and across job types (or clusters). Women account for a majority of healthcare practitioners and technicians but are underrepresented in other jobs, particularly computer and engineering positions. While there has been significant progress for women in the life and physical sciences since 1990, the share of women has been roughly stable in other STEM occupational clusters and has gone down 7 percentage points in computer occupations. 11

What’s a STEM job?

This analysis relies on a broad-based definition of the science, technology, engineering and math (STEM) workforce. STEM jobs are defined solely based on occupation and include: life sciences, physical and Earth sciences, engineering and architecture, computer and math occupations as well as health-related occupations including healthcare providers and technicians.

Educators specializing in STEM subjects could not be identified in the analysis of the American Community Survey, though they are included as holding STEM jobs in the analysis of the Pew Research Center survey.

While there is often considerable overlap across definitions, there is no commonly agreed definition of the STEM workforce. Thus, caution is warranted in any direct comparisons with other studies.

Gains in women’s representation in STEM jobs have been concentrated among women holding advanced degrees, although women still tend to be underrepresented among such workers. Women are roughly four-in-ten (41%) of all STEM workers with a professional or doctoral degree such as an M.D., D.D.S., or Ph.D.

Black and Hispanic workers continue to be underrepresented in the STEM workforce. Blacks make up 11% of the U.S. workforce overall but represent 9% of STEM workers, while Hispanics comprise 16% of the U.S. workforce but only 7% of all STEM workers.

Asians are overrepresented in the STEM workforce, relative to their overall share of the workforce, especially among college-educated workers: 17% of college-educated STEM workers are Asian, while 10% of all workers with a college degree are Asian.

The representation of women, blacks and Hispanics in STEM has implications for the average earnings of workers in these groups. STEM workers earn more, on average, than workers in non-STEM jobs, even when controlling for educational attainment.

One potential barrier for those wishing to enter the STEM workforce is the generally higher level of educational attainment required for many such positions. Among college-educated workers, one-in-three (33%) majored in a STEM field. But only about half (52%) of those with college training in a STEM field are currently employed in a STEM job. 12 The rest are working in other fields, with many benefiting from the financial bump in earnings that comes with a STEM degree.

The reasons why half of college-educated workers with STEM-related training turn to jobs elsewhere are likely complicated. Among college-educated workers, those who majored in a health professions field are more likely than those who majored in other STEM fields to be working in a job directly related to their degree. About seven-in-ten (69%) women who majored in a health professions field (such as nursing or pharmacy) are working in a health-related occupation, as are 61% of men who majored in health professions.

But among those who majored in computers or computer science, women are less likely than men to be working in a computer occupation (38% vs 53%). Similarly, women who majored in engineering during their undergraduate studies are less likely than men to be working in engineering jobs (24% vs. 30%). Thus, in two occupational areas with particularly low shares of women, retention of those who meet a key barrier for job entry appears to be lower for women than for men.

Other notable findings include the following:

The public image of STEM jobs includes higher pay and an advantage in attracting young talent compared with other industry sectors

In some ways, the public has a very positive view of STEM jobs, as they compare with jobs in other sectors. About seven-in-ten Americans (71%) see jobs in STEM as offering better compensation than jobs in other industries. And, a majority of Americans (58%) consider STEM jobs to attract more of the brightest, most qualified young people.

The public is closely divided over whether jobs in STEM make a more meaningful contribution to society or do so to about the same extent as other jobs (45% to 48%). But only a minority think of STEM jobs as being more focused on helping others (28%) than jobs in other industries.

About one-in-five Americans (18%) say STEM jobs have more flexibility to balance work and family needs than other jobs in other sectors, while about half (52%) say the flexibility in this regard is about the same as it is in other sectors and 28% say there is less flexibility in STEM jobs than there is elsewhere.

Men and women working in STEM say flexibility to balance work and family needs is important to them

Men and women in STEM jobs – and indeed those in non-STEM jobs as well – say that having the flexibility to balance their work and family obligations is an important factor to them in choosing a job. But men and women in STEM tend to diverge when it comes to other job characteristics. A somewhat higher share of men than women say that having higher pay and opportunities for promotion is important to them in choosing a job. Women in STEM jobs are more inclined to consider a job that focuses on helping others (59%) as important to them compared with men in STEM jobs (31%). 13

Americans see a range of explanations for the underrepresentation of women, blacks and Hispanics in STEM jobs

Many Americans attribute the limited diversity of the STEM workforce to a lack of encouragement for girls and blacks and Hispanics to pursue STEM from an early age; 39% of Americans consider this a major reason there are not more women in some STEM areas, and 41% say this is a major reason there are not more blacks and Hispanics in the STEM workforce.

In addition, 42% of Americans say limited access to quality education to prepare them for these fields is a major reason blacks and Hispanics are underrepresented in the STEM workforce; this view is held by a majority of those working in STEM who are black (73%) and about half of Hispanics (53%), Asians (52%) and whites (50%) in STEM jobs.

There are wide differences among STEM workers on the role of racial/ethnic discrimination in underrepresentation. Among blacks in STEM jobs, 72% say discrimination in recruitment, hiring and promotions is a major reason behind the underrepresentation of blacks and Hispanics in these jobs. By contrast, 27% of whites and 28% of Asians say this, while 43% of Hispanics think discrimination is a major reason behind the underrepresentation.

Similarly, there are wide differences between men and women working in STEM jobs on the role of gender discrimination. About half of women in STEM jobs (48%) say gender discrimination in recruitment, hiring and promotions is a major reason there are not more women in STEM jobs, compared with 29% of men in STEM jobs.

When women and those in racial and ethnic minority groups working in STEM were asked to say, in their own words, the best ways to attract more people like themselves to STEM, many emphasized the importance of quality schooling and an early start to encouraging people into the field with repeated support over time. A few examples:

“You must introduce those fields early in the elementary school years. Then continue to build on that by establishing STEM clubs and activities. Provide information to parents about local/community STEM events for continued interests. Most of all, make sure that any STEM student has the rigorous preparation that will be needed to get them accepted into college and able to handle the nature of the college level classes.” – Black woman, nurse, 49

“K-8 teaching needs to be designed to make these subjects more interesting and accessible to girls. Teachers need to be explicit about the need for more women in STEM jobs, and help girls feel that they have a reason to pursue these fields in spite of the somewhat intimidating gender breakdown of higher level classes.” – White woman, math teacher, 42

“Providing opportunities such as putting upgraded computers and/or science labs in inner-city schools, libraries and community centers. Black men currently in the STEM industries must be visible to the younger generation in order to show the value of those skills and the career implications.” – Black man, systems engineer, 30

Most Americans rate K-12 STEM education as average or worse compared with other developed nations, so, too, do those with an advanced degree in STEM

Americans are generally critical of the quality of STEM education in the nation’s K-12 schools. A quarter of Americans (25%) consider K-12 STEM education in the U.S. to be at least above average compared with other developed countries, while 30% say the U.S. is below average in this regard, and 43% say it is average. Parents with children in public schools give similar ratings of the nation’s K-12 STEM education.

Americans tend to see higher education in STEM more favorably, by comparison, but there too, fewer than half consider undergraduate education (35%) or graduate education (38%) in STEM as at least above average compared with other nations.

People who, themselves, have a postgraduate degree in a STEM field give positive ratings to the quality of postsecondary education in the U.S., but just 13% of this group considers K-12 STEM education to be at least above average.

Nonetheless, as Americans look back on their own K-12 experiences, three-quarters (75%) report that they generally liked science classes. Science labs and hands-on learning experiences stand out as a key appeal among those who liked science classes. Some 46% of those who disliked science classes in their youth say a reason for their view is that these classes were hard, while another 36% of this group found it hard to see how science classes would be useful to them in the future.

The data in this report come from two sources: 1) a Pew Research Center analysis of the U.S. Census Bureau’s 1990 and 2000 decennial censuses as well as aggregated 2014-2016 American Community Survey data and 2) a nationally representative survey of 4,914 U.S. adults, ages 18 and older, conducted July 11-Aug. 10, 2017. The survey, which was conducted online in English and Spanish through GfK’s Knowledge Panel, included an oversample of employed adults working in science, technology, engineering and math (STEM) jobs.

Analysis of the survey data compares those working in STEM jobs with those in non-STEM jobs based on self-identified occupation. STEM jobs include: computer and mathematical jobs, architecture and engineering, life sciences, physical sciences, healthcare practitioners and technicians, and teachers at the K-12 or postsecondary level with a specialty in teaching science, technology, engineering or math subjects.

A similar definition is used to identify the STEM workforce in the U.S. Census Bureau data based on the 2010 Standard Occupational Classification. However, no educators are included as having STEM jobs in that data because the dataset does not allow identification of educators with a subject matter expertise in STEM subjects.

References to the STEM workforce are based on those employed in a job classified as being in science, technology, engineering or math.

Some analysis of the U.S. Census Bureau data compares those with a college degree who majored in STEM and those who majored in other fields. A STEM major includes the following areas: computers, mathematics and statistics, biological, agricultural and environmental sciences, physical and earth sciences, engineering, architecture, health-related fields, such as nursing, and STEM education, like science or math teacher education. Some analysis of the survey data is based on those with a postgraduate degree in a STEM field, using the same definition as above.

References to whites, blacks and Asians include only those who are non-Hispanic and identify themselves as only one race. Hispanics are of any race.

Asians working in STEM jobs are based on those who self-identify as Asian or Asian American and work in occupations classified as STEM. There are too few Asians working in non-STEM jobs in the survey for separate analysis. Note that the survey was conducted in English and Spanish only; thus only Asians proficient in English/Spanish are likely to have completed the survey. For more on the characteristics of the Asian population in the U.S. see the Center’s fact sheets on Asian Americans.

References to college graduates or people with a college degree comprise those with a bachelor’s degree or more, unless otherwise noted. “Some college” includes those with an associate degree and those who attended college but did not obtain a degree. “High school or less” refers to those who have a high school diploma or its equivalent, such as a General Education Development (GED) certificate, or less education. References to those with advanced degrees and postgraduate degrees are used interchangeably; these terms refer to people who have a master’s degree or higher.

• These findings come on the heels of at least four decades of research about how to better foster diversity in the STEM workforce in the U.S. and globally. See Malcom, Shirley Mahaley, Paula Quick Hall, and Janet Welsh Brown. 1976. “ The Double Bind: The Price of Being a Minority Woman in Science .” American Association for the Advancement of Science.; Association for Women in Science. 2016. “ Broadening Participation in Science, Technology, Engineering, and Mathematics .” Open Science.; UNESCO. 2017. “ Cracking the code: Girls and women’s education in science, technology, engineering and mathematics (STEM) .”; Organization for Economic Cooperation and Development (OECD). 2017. “ Chapter 7: The under-representation of women in STEM fields .” “The Pursuit of Gender Equality: An uphill battle.” OECD Publishing.; National Science Foundation, National Center for Science and Engineering Statistics. 2017. “ Women, Minorities, and Persons with Disabilities in Science and Engineering .” ↩
• Differences in reported discrimination in the workplace due to race between blacks in STEM vs. non-STEM jobs should be interpreted with caution due to the smaller number of black respondents in the survey (320 in total). Taking into account the design effect for these subgroups, the difference of 62% of blacks in STEM vs. 50% of blacks in non-STEM jobs saying they have experienced racial discrimination at work – whether in their current or previous jobs – for a two-tailed test is p=.075. ↩
• Figures for women working with mostly women and women working with an even mix of genders are combined here but shown separately later in the report. Both of these groups of women in STEM work primarily in health-related jobs. For more on the characteristics of women working in these settings see Appendix . ↩
• One exception: 32% of men working in STEM jobs with mostly women say they have experienced gender-related discrimination at work compared with 15% of men in mostly male workplaces and 16% of men in workplaces with an even gender distribution. ↩
• The survey includes 150 female computer workers. Taking into account the design effect of the survey, the margin of error is +/- 10.6 percentage points. ↩
• A separate Pew Research Center analysis found female computer workers are more likely than their male counterparts to believe that gender discrimination is a major problem in the tech industry. ↩
• A new analysis of Equal Employment Opportunity Commission (EEOC) complaints from the Center for American Progress show that claims of sexual harassment have been filed by women (and some men) in a wide range of industries and occupational groups with somewhat larger shares coming from employees in food service, retail trade and manufacturing as well as healthcare and social assistance. ↩
• See Malcom, Shirley Mahaley, Paula Quick Hall, and Janet Welsh Brown. 1976. “ The Double Bind: The Price of Being a Minority Woman in Science .” American Association for the Advancement of Science. ↩
• There are not enough Asians working in non-STEM jobs in the survey sample for separate analysis. ↩
• Estimates of women’s representation in STEM jobs vary widely. A 2013 Census Bureau report estimated that 26% of the STEM workforce is female as of 2011 using a definition that omits healthcare practitioners and technicians. Including healthcare practitioners and technicians as part of the STEM workforce has a substantial effect on such estimates because healthcare practitioner and technician jobs make up a large share of the workforce and because such jobs are mostly held by women. Analysis of the “science- and engineering-related” workforce in the National Science Foundation’s Science and Engineering Indicators 2016 include health-related professions but is limited to those holding at least a bachelor’s degree. ↩
• Estimates of how many STEM-trained workers are “retained” in a STEM occupation vary widely across studies. These estimates depend on the definition of STEM occupations as well as what constitutes a STEM major and whether the retention estimates are based on training in a specific field and having a directly related job, as discussed here, or is more broadly defined as working in any STEM job. ↩
• About two-thirds (68%) of women in health-related jobs say that having a job that is focused on helping others is important to them. However, even excluding workers in health-related jobs, a higher share of women than men working in STEM say that this characteristic is important to them in choosing a job. ↩

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The STEM Gap: Women and Girls in Science, Technology, Engineering and Mathematics

• Download Solving the Equation Report
• Download Why So Few Report

 Girls and women are systematically tracked away from science and math throughout their education, limiting their access, preparation and opportunities to go into these fields as adults.

Women make up only 34% of the workforce in science, technology, engineering and math (STEM), and men vastly outnumber women majoring in most STEM fields in college. The gender gaps are particularly high in some of the fastest-growing and highest-paid jobs of the future , like computer science and engineering.

Why So Few? Women in Science, Technology, Engineering & Mathematics

Learn more about how we can change policies and practices to increase opportunities in STEM for girls and women.

Solving the Equation: The Variables for Women's Success in Engineering & Computing

Engineering and computer science — two of the most lucrative STEM fields — remain heavily male dominated. Only 21% of engineering majors and 19% of computer science majors are women. Read AAUW’s research report for ways we can stop steering girls away from math and science, and make these fields more welcoming for women.

Tracking Girls and Women Out of Higher-Paying STEM Areas

Giving women equal opportunities to pursue — and thrive in — STEM careers helps narrow the gender pay gap, enhances women’s economic security, ensures a diverse and talented STEM workforce and prevents biases in these fields and the products and services they produce.

A typical STEM worker earns two-thirds more than those employed in other fields, according to Pew Research Center. And some of the highest-earning STEM occupations, such as computer science and engineering, have the lowest percentages of women workers.

Key factors perpetuating gender STEM gaps:

• Gender Stereotypes: STEM fields are often viewed as masculine, and teachers and parents often underestimate girls’ math abilities starting as early as preschool.
• Male-Dominated Cultures: Because fewer women study and work in STEM, these fields tend to perpetuate inflexible, exclusionary, male-dominated cultures that are not supportive of or attractive to women and minorities.
• Fewer Role Models : girls have fewer role models to inspire their interest in these fields, seeing limited examples of female scientists and engineers in books, media and popular culture . There are even fewer Black women role models in math and science.
• Math Anxiety: Teachers, who are predominantly women, often have math anxiety they pass onto girls, and they often grade girls harder for the same work, and assume girls need to work harder to achieve the same level as boys.

The Confidence Gap

The myth of the math brain is one of the most self-destructive ideas in American education – research shows no innate cognitive biological differences between men and women in math.

Many girls lose confidence in math by third grade. Boys, on the other hand, are more likely to say they are strong in math by 2nd grade , before any performance differences are evident.

A gendered math gap exists in elementary school — but it is really only evident among boys from higher-income and predominantly white areas performing significantly higher in math, even compared to girls attending those same schools.

Girls score higher than boys in math in lower-income, predominantly Black areas (representing around one-quarter of school districts), but their scores are still disproportionately low compared to scores for white boys in high-income areas.

Women are Underrepresented in STEM Workforce

By the time students reach college, women are significantly underrepresented in STEM majors — for instance, only around 21% of engineering majors are women and only around 19% of computer and information science majors are women.

• Nearly 80% of the health care workforce are women, but only about 21% of health executives and board members are women, and only about a third of doctors. And, women are more highly represented in lower-paying fields, such as home health workers, nurses and the lower-paying specialties such as pediatricians.
• 38% of women who major in computers work in computer fields, and only 24% of those who majored in engineering work in the engineering field.
• Men in STEM annual salaries are nearly $15,000 higher per year than women ($85,000 compared to $60,828). And Latina and Black women in STEM earn around $33,000 less (at an average of around $52,000 a year).

Dell-AAUW Playbook on Best Practices: Gender Equity in Tech

A product of a partnership between AAUW and Dell, the Playbook on Best Practices: Gender Equity in Tech equips advocates and employers with data-driven strategies and actionable steps to increase the representation of women in engineering and computing fields – to accelerate the rate of change and break through barriers for women in the workplace.

Closing the STEM Gap

Give girls and women the skills and confidence to succeed in math and science..

• Raise awareness that girls and women are as capable as boys.
• Give girls equitable encouragement and educational opportunities.
• Promote public awareness to parents about how they can encourage daughters as much as sons in math and science — supporting learning opportunities and positive messages about their abilities.
• Teach girls, teachers and parents that math skills are learned and change over time — promoting a growth mindset that empowers girls to embrace challenges.
• Emphasize strong and visible role models of women and women of color in math and science fields.

Improve STEM education and support for girls starting in early education and through K-12.

• Provide professional development to teachers — addressing implicit and systemic biases to raise awareness about girls’ math abilities, avoid passing on math anxiety and ensure boys and girls are held to the same standards.
• Encourage girls and women to take math and science classes — including advanced classes.
• Reduce tracking and high-stakes assessment in early grades that reinforce biases and stereotypes.
• Ensure every student is exposed to engineering and computer science , and Next Generation Science Standards in K–12.
• Change how classes are taught by connecting STEM experiences to girls’ lives, promoting active, hands-on learning and emphasizing ways STEM is collaborative and community-oriented.
• Teach girls of color math through open-ended and co-created problem posing and discovery.
• Expand after-school and summer STEM opportunities for girls.
• Increase awareness of higher education and career opportunities, pathway opportunities, role models and mentoring programs with women — especially women of color — in STEM for girls.

Work to attract, recruit and retain women into STEM majors and fields in colleges and universities.

• Design courses and change environments and practices in STEM studies to be more welcoming for women.
• Prioritize diverse, inclusive and respectful environments, and strong, diverse leadership.
• Diffuse hierarchical and dependent relationships between trainees and faculty, changing power dynamics.
• Make the entire academic community responsible for reducing and preventing sexual harassment, ensure transparency and accountability, and support targets of sexual harassment.
• Campuses should fully enforce Title IX  in science, technology, engineering, and math.
• Promote mentorship, sponsorship networking and incorporate male ally programs.

Improve job hiring, retention and promotion pathways and intentionally inclusive cultures.

• Recruit more women and work to retain and promote women throughout their careers with strong advancement pipelines and continued professional development and leadership training.
• Promote welcoming work environments, including providing pay equity; flexibility; strong family and medical leave policies; inclusion and anti-bias training; mentorship, networking and ally-ship opportunities; and strong anti-discrimination and anti-harassment policies.

Break Biases

I still remember asking my high school guidance teacher to take a second year of algebra instead of a fifth year of Latin. She looked down her nose at me and sneered, ‘What lady would take mathematics instead of Latin?’

Fast Facts: Early Barriers to Girls & Women in STEM

Where We Stand: STEM Education

Nancy Grace Roman: The Life and Legacy of a NASA Star

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• Published: 19 April 2021

Potential solutions for discrimination in STEM

• Luisa Maria Diele-Viegas   ORCID: orcid.org/0000-0002-9225-4678 1 , 2 ,
• Tábata Elise Ferreira Cordeiro 1 , 3   na1 ,
• Tatiana Emmerich 4   na1 ,
• Juliana Hipólito   ORCID: orcid.org/0000-0002-0721-3143 1 , 5 , 6   na1 ,
• Caren Queiroz-Souza   ORCID: orcid.org/0000-0002-9692-3496 1 , 6 , 7   na1 ,
• Erilda Sousa   ORCID: orcid.org/0000-0002-0352-1181 1 , 8   na1 ,
• Alianna Cardoso Vançan   ORCID: orcid.org/0000-0001-8570-627X 9 , 10 , 11   na1 &
• Luciana Leite 1 , 7 , 12   na1  

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Acknowledgements

We thank L. P. Salles, B. Pascal, R. Santos-Silva, C. Birrer, and A. Campos for their comments and insights during the discussion that gave rise to this manuscript. This study was partially financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (Capes) - Finance Code 001.

Author information

These authors contributed equally: Tábata Cordeiro, Tatiana Emmerich, Juliana Hipólito, Caren Queiroz Souza, Erilda Sousa, Alianna Cardoso Vançan, Luciana Leite.

Authors and Affiliations

Kunhã Asé Network of Women in Science, Salvador, Brazil

Luisa Maria Diele-Viegas, Tábata Elise Ferreira Cordeiro, Juliana Hipólito, Caren Queiroz-Souza, Erilda Sousa & Luciana Leite

Biology Department, University of Maryland, College Park, Maryland, USA

Programa de Pós-Graduação em Biologia Comparada, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Ribeirão Preto, Brazil

Tábata Elise Ferreira Cordeiro

Programa de Pós graduação em Direito, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Brazil

Tatiana Emmerich

Coordenação de Biodiversidade, Instituto Nacional de Pesquisas da Amazônia, Manaus, Brazil

National Institute of Science and Technology in Inter and Transdisciplinary Studies in Ecology and Evolution - INCT IN- TREE, Salvador, Brazil

Juliana Hipólito & Caren Queiroz-Souza

Programa de Pós-Graduação em Ecologia, Universidade Federal da Bahia, Salvador, Brazil

Caren Queiroz-Souza & Luciana Leite

Universidade Federal do Pará, Altamira, Brazil

Erilda Sousa

Instituto de Ciências Humanas e Sociais, Programa de Pós-graduação em Filosofia, Universidade Federal de Pelotas, Pelotas, Brazil

Alianna Cardoso Vançan

Faculdade de Ciências Jurídicas, Programa de Pós-graduação em Direito, Universidade Federal do Mato Grosso, Cuiabá, Brazil

500 Mulheres Cientistas Cuiabá, 500 Women in Science, Cuiabá, Brazil

School of Psychological Science, Oregon State University, Corvallis, Oregon, USA

Luciana Leite

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L.M.D.-V. and L.L. were responsible for the conceptualization of the ideas. L.M.D.-V., T.C., T.E., J.H., C.Q.S., E.S., A.C.V., and L.L. were equally responsible for the validation and writing of the manuscript. L.M.D.-V. was responsible for the graphic visualization, supervision, and project administration.

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Diele-Viegas, L.M., Cordeiro, T.E.F., Emmerich, T. et al. Potential solutions for discrimination in STEM. Nat Hum Behav 5 , 672–674 (2021). https://doi.org/10.1038/s41562-021-01104-w

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Sexism Persists in STEM

• January 19, 2021
• Diversity and Inclusion

“STEM at OSU: Sexism Persists” was written by Cara Nixon and published by The Corvallis Advocate . You can read the original article here .

Nationwide, the science, technology, engineering, and math (STEM) sector is all about progress: improving upon past experiments and projects, advancing the world of invention, and developing new ways of life before our very eyes.     

But if the STEM industry is defined by growth, why are women being left behind?    

Arguably, this  exclusion of women  in STEM-related fields  begins from a young age, as stereotypes associated with different genders are enforced  in childhood .  Several studies , including  one  by the Journal of Applied Social Psychology,  have shown that when children  were  asked to draw a mathematician or scientist, girls  were twice as likely to draw men  over women , while boys almost exclusively drew men.     

Stereotypes, along with lack of opportunity due to  gender, race, and class, may explain why girls , according to a  study  by the American Association of University Women,  enter STEM fields at  alarmingly lower rates  than boys .

If they do choose to enter STEM, w omen are then outnumbered as they  pursue  higher education – for the 2017-2018 academic year,  according to  research  by the Society of Women Engineers,   females  represented  about  21%  of bachelor’s degree holders ,  29% of master’s degree holders ,  and 24% of doctoral degree holders in STEM fields.    

Upon entering the workforce, women continue to feel isolated in their fields:  data  from the National Science Foundation shows that  only  29%  of those employed in science and engineering were women in 2017.   In academia, women are generally  underrepresented  as well , according to  research  from the National Center for Education Statistics . In the United States in 2018, they held 49.7% of all tenure-track positions, but held only 39.3% of tenured positions. More specifically, women h e ld 57% of instructor positions; 52.9% of assistant professor positions; 46.4% of associate professor positions; and 34.3% of professor positi ons.  

According to data provided by Oregon State University (OSU) vice president of university relations and marketing Steve Clark, women at OSU represented 55.2% of instructor positions, but only held 37% of tenure-track and tenure positions in the fall of 2019.    

For these reasons and more, it’s not a surprise that female STEM faculty at Oregon State University have experienced their fair share of sexism in their fields.

The Women in STEM Experience

Male colleagues making assumptions about her commitment to her career because she is a mother; making assumptions about her capability to handle equipment; making unwanted sexual advances; and undermining her when she presents a problem are just a few examples of the sexism she has experienced at the university.    

In one  particularly strange and uncomfortable  instance, she recall ed  a department chair grabbing her skirt, intrigued by its shiny material,  and then continuing with the conversation as if nothing had happened.  

Doolen spent  over ten  years in industry before moving into academia. She , like Bruslind,  remembers often being the only woman in  meetings ,  and  she felt  especially isolated while pregnant. Though she doesn’t feel like she was discriminated against during the hiring or promotion process, she did experience subtle sexist behaviors, like being interrupted or  having h er ideas not be acknowledged .     

She had one extremely negative experience when a vendor told her manager that he  wouldn’t work with her because she was a woman and “didn’t know anything about engineering.”    

When she came to OSU, she served as the faculty member  representative  on an interview panel for MECOP, a paid engineering internship program. While on the panel, she had to  help clarify for one of the  male  interviewers that his question was inappropriate.   In   this case, the interviewer asked for  c andidates to   share childhood activities that involved taking apart things. This type of experience is not   necessarily something that all candidates have participated in and assumes particular   experiences, which are gender-based, are critical to develop good engineers.

More subtle behaviors include not being listened to in meetings, being left out of “boys’ clubs,” and  people being surprised when accomplishing tasks traditionally performed by men , all of which   Tumer sa id  she has experienced.     

“It’s very subtle, but it can have a lot of impact,” Tumer  said .     

Obvious behaviors can range from competency being outwardly questioned due to gender, like in Doolen’s experienc e , to sexual harassment, like  Bruslind  has endured. 

Bruslind, Doolen, and Tumer are a small sample size of the  experiences that  women  encounter  across STEM fields,  but  they all ha d   similar  answers as to why this marginalization persists.     

In Bruslind’s opinion, “ I think the primary reason that women in STEM still face marginalization in their fields in because of the impact that having a family typically has on their career. Often women are forced to choose between having  a  high-powered career in science and having a family. There is a reason that there is a higher proportion of STEM women in positions such as advisor, instructor, staff, or research associate, as opposed to professor.”    

In an  article  from the  Scientific American  by Cui Wang, she wrote, “The greatest challenge in the life of a mother-scientist, almost without exception, lies in refining the balance between the two rewarding roles.” This idea is reflected in the  statistics  – almost half of new mothers in STEM leave their jobs or go part-time, while only a quarter of new fathers do so.     

Doolen agree d  with Bruslind, “There are challenges associated with women who choose to take time off to either care for or have children, and so I think their career paths get disrupted….”    

She also attribute d  the problem to the numbers. Because women are underrepresented in STEM fields, they are often seen as outsiders and face  marginalization, or, in some cases, discrimination  because of their  gender.    

Another large issue that both Doolen and Tumer point ed  to is the  number  of women who leave STEM fields , but not because of parenthood.    

“Women get frustrated and they just leave,” Doolen said. She added that often they go on to other fields or to start their own businesses, exhausted by the structural barriers that exist in traditional STEM environments.    

These losses are felt within the fields and further contribute to underrepresentation. Tumer  said , “That’s a lot of brains that we’re leaving off of STEM fields.”    

Tumer also explained, however, that the marginalization comes from something deeper, “That marginalization is there because of a lack of understanding and a lack of advocacy and lack of allies for most women.”    

The discrimination and underrepresentation are even worse for women of color. According to another  study  from the National Center for Education Statistics, the percentages for women of color in STEM at higher education institutions for the 2017-2018 year are as follows: 5.3% for Asian women, 2.9% for Black women, 4.3% for Latinas, and .1% for American Indian/Alaska Native women. In total, only 11.5% of science and engineering employees in 2017 were women of color.

Doolen  said  that organizations are not only fundamentally masculine-supporting but racialized. Because these traits are ingrained in our systems, it can be difficult to find solutions. And because experiences vary among women, especially when they differ in race and class, people have different answers to how we can solve this universal problem.     

Is OSU Equipped to Handle Sexism?

In fact, when asked if OSU is well-equipped to handle issues like sexism, Bruslind, Doolen, and Tumer all ha d  different answers.     

Bruslind  sa id ,  “ Not really. Since so many of the administrative roles are held by men, it is difficult for th em to understand the issues that women face or to come up with realistic solutions.  Offering one more mandated workshop on sexism does not truly address the issues. ”    

Doolen, on the other hand, sa id  that the answer to this question is tricky. OSU has systems and processes in place to combat these issues,  but,   “ We still rely on basically the victim to move things forward . ” This is why   Doolen pursued a higher position  in her field.    

“ I was really clear in my mind as soon as I became a professor, that my number one goal was to get to be a full professor so that I had a position of power, similar to what I had in the industry as a manager, to actually   advocate, mentor, a nd help change things,” she explai ned . “Without that power, it just feels too risky.”    

Tumer feels that though  there are  policies and processes in place like in other universities, “There’s always room for education and doing better.”    

Alleviating the Problem

So, how can Oregon State University help alleviate this problem? The three women cite listening to women, educating both potential offenders and victims, and allyship as potential solutions.    

“ There needs to be an in-depth look at the barriers for women in STEM departments, starting with what the women think. I think there will also be improvement as some of the older members of the department retire. They tend to still use a n   ‘ old boys’ network ’  approach for getting things done ,” Bruslind explain ed . “ That mentality is not present with the newer members of the faculty – I see more respect, more awareness, more sensitivity.”    

“The most important thing is to listen and pay attention when a woman, whether it’s a student or an employee, talks about an experience they’ve had,” Tumer suggest ed . “Most of us don’t  want  to be in the spotlight – we would never talk about it if it wasn’t real.”

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Facing Racism and Sexism in Science by Fighting Against Social Implicit Bias: A Latina and Black Woman’s Perspective

Karin c. calaza.

1 Department of Neurobiology, Institute of Biology, Universidade Federal Fluminense, Niterói, Brazil

Fátima C. S. Erthal

2 Laboratory of Neurobiology, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil

Mirtes G. Pereira

3 Department of Physiology and Pharmacology, Biomedical Institute, Universidade Federal Fluminense, Niterói, Brazil

Kita C. D. Macario

4 Department of Physics, Institute of Physics, Universidade Federal Fluminense, Niterói, Brazil

Verônica T. Daflon

5 Department of Sociology and Methodology of Social Sciences, Institute of Human Sciences and Philosophy, Universidade Federal Fluminense, Niterói, Brazil

Isabel P. A. David

Helena c. castro.

6 Department of Cellular and Molecular Biology, Institute of Biology, Universidade Federal Fluminense, Niterói, Brazil

Maria D. Vargas

7 Chemistry Institute, Universidade Federal Fluminense, Niterói, Brazil

Laura B. Martins

8 Biomedical Institute, Universidade Federal Fluminense, Niterói, Brazil

Jasmin B. Stariolo

9 Institute of Biology, Universidade Federal Fluminense, Niterói, Brazil

Eliane Volchan

Leticia de oliveira.

The editors of several major journals have recently asserted the importance of combating racism and sexism in science. This is especially relevant now, as the COVID-19 pandemic may have led to a widening of the gender and racial/ethnicity gaps. Implicit bias is a crucial component in this fight. Negative stereotypes that are socially constructed in a given culture are frequently associated with implicit bias (which is unconscious or not perceived). In the present article, we point to scientific evidence that shows the presence of implicit bias in the academic community, contributing to strongly damaging unconscious evaluations and judgments of individuals or groups. Additionally, we suggest several actions aimed at (1) editors and reviewers of scientific journals (2) people in positions of power within funding agencies and research institutions, and (3) members of selection committees to mitigate this effect. These recommendations are based on the experience of a group of Latinx American scientists comprising Black and Latina women, teachers, and undergraduate students who participate in women in science working group at universities in the state of Rio de Janeiro, Brazil. With this article, we hope to contribute to reflections, actions, and the development of institutional policies that enable and consolidate diversity in science and reduce disparities based on gender and race/ethnicity.

Introduction

“Science has a racism problem,” claimed an editorial of the important journal “Cell” ( Edge, 2020 ). Editors from a variety of respected scientific journals, such as Nature and Science, have recently asserted the importance of combating racism and sexism in science. Especially after the COVID-19 pandemic, several pieces of evidence suggest that gender and racial gaps may be widened ( Collins et al., 2020 ; Myers et al., 2020 ; Staniscuaski et al., 2020 ). For instance, Staniscuaski et al. (2021) , analyzing academic productivity, showed that male academics—especially childless academics—were the group least affected by the pandemic. In contrast, female academics, especially Black women and mothers, were the most impacted group.

Although the fight against racism and sexism in science involves several aspects, socially constructed implicit bias is a key component in this fight. “Bias” is a concept that refers to analysis, judgments, or attitudes that do not adhere to the principles of impartiality. Bias against a person or group can lead to unfair assessments. This judgmental bias can be explicit or implicit (not perceived), and it can occur due to skin color, ethnicity, religion, gender, sexual orientation, weight, physical, or mental disability, among others ( Greenwald and Krieger, 2006 ; Staats et al., 2015 ). Implicit (unconscious or unperceived) negative judgment bias in the academic sphere is generally associated with social stereotypes of individuals who are stigmatized as intellectually limited or incapable. Importantly, a social stereotype is a mental association of a social group or category with a characteristic or trait that may or may not be favorable ( Greenwald and Krieger, 2006 ). In other words, stereotypes are socially constructed beliefs that do not necessarily reflect reality ( Allport, 1954 ; Ashmore and DelBoca, 1981 ; Greenwald and Banaji, 1995 ). Such social constructions, which are determined by culture and the unequal distribution of resources and power in a community, have substantial influence on the unconscious evaluations and judgments of individuals or groups ( Staats et al., 2015 ; Storage et al., 2016 ). Stereotypes that are repeatedly and imperceptibly transmitted through several information channels induce implicit beliefs that are used to organize and socially categorize the world and provide rationales for entrenched inequalities ( Gaucher et al., 2011 ; Kang, 2012 ; Gálvez et al., 2019 ; Rivera and Tilcsik, 2019 ). These implicit associations are more prevalent than explicit prejudice, which means that even people who consciously believe in and defend the principles of justice and non-discrimination can have their judgment affected by implicit bias, without their knowledge ( Staats et al., 2014 ). In fact, evidence suggests that implicit bias can be a better predictor of behavior than explicit bias ( Bargh and Chartrand, 1999 ; Ziegert and Hanges, 2005 ). While explicit biases are conscious attributions that are accessible through introspection, implicit biases are more difficult to become conscious of. Nevertheless, implicit bias can be assessed through experimental paradigms using a diversity of approaches and research tools (see below).

Implicit Gender Bias

Negative implicit stereotypes are shaped by experience and are based on implicit learned associations between the culturally constructed putative characteristics of members of social categorical groups, including those based on race, gender, and socioeconomic status. The presence of these stereotypes leads to implicit bias in judgments of stigmatized individuals or groups ( Greenwald and Banaji, 1995 ). The formation of implicit gender stereotypes, which associate characteristics of exceptional brilliance and intelligence to the male gender, seems to start early in life ( Bian et al., 2017 ) and is reinforced by daily experiences in which members of a categorical group appear to be associated with economic precariousness and a lack of power ( Tilly, 1998 ). In the study of Bian et al. (2017) , children from 5 to 7 years old listened to a text that described a brilliant person. Then, children viewed pictures of women’s and men’s faces and were asked to indicate which person was the character in the story. Among the five-year-old children, both boys and girls chose photographs of people of their own gender. However, among children aged 6 and older, only boys continued to indicate the pictures of people of their own gender as the brilliant character in the story, while girls became less likely to choose photographs of women. Considering that children at this age generally show positive biases toward their own in-groups (e.g., those of the same gender), this result suggests that the consequences of the stereotype that brilliance is a male characteristic occur very early and that this stereotype already begins to impact girls between 5 and 6 years old ( Bian et al., 2017 ). Interestingly, a study showed that national gender differences in science and math success are associated with national differences in implicit gender-science stereotypes. Specifically, the stronger the nation’s citizens’ implicit association of men with science and women with the liberal arts, the greater the gap between female and male adolescents’ eighth-grade science achievement in that nation ( Nosek et al., 2009 ). There is evidence that implicit bias acts incisively in adulthood, harming women. One study showed that when university faculty (both men and women) analyzed an identical curriculum for a laboratory manager position with either a male or a female name, the faculties evaluated the curriculum with a male name as more competent and deserving a higher salary ( Moss-Racusin et al., 2012 ). In the same vein, Reuben et al. (2014) carried out a study in which participants (men and women) who were volunteers in laboratory research were rewarded for “hiring” a good candidate to perform mathematical tests. Women were systematically less chosen than men in all three experimental conditions tested as: (1) a condition in which no skill information and only information about the physical appearance of the candidates was provided (2) a condition in which the candidates could give a speech to talk about their mathematical skills, and (3) a condition in which information about the candidates’ performance on a previous math test was provided. Interestingly, in this last experimental condition, the power of the effect of implicit bias was clearly demonstrated, as the “employers” preferred to choose men with low performance in mathematics over women with good performance. The authors also reported that in condition (2), when the candidates were allowed to talk about their skills, the male candidates overestimated their math skills, while the female candidates did the opposite.

The presence of this implicit bias against women causes considerable damage to the development of their scientific careers. Only 18.1% of articles published in high-impact journals (Nature research journals) have women as senior authors (last authorship), and the higher the journal’s impact index is the smaller the number of women listed as the principal author ( Bendels et al., 2018 ). In addition, articles with women as the principal author are less cited than those with men as the principal author ( Larivière et al., 2013 ). Recently, Dworkin et al. (2020) analyzed high-impact neuroscience journals and found that papers with men listed as the first or last author were cited 11.6% more than expected given the proportion of such articles in the field, and papers with women listed as the first or last author were cited 30.2% less than expected. Importantly, however, when articles are reviewed anonymously (double-blind review), the number of articles published with women listed as the first author increases ( Budden et al., 2008 ), highlighting the impact of implicit bias in this process. Women who have authored the same number of publications with the same publication impact as men are less likely to become research leaders ( Van Dijk et al., 2014 ). Additionally, letters of recommendation written for women use significantly fewer adjectives that represent intelligence and brilliance ( Dutt et al., 2016 ; Kuo, 2016 ).

In terms of research funding, the effects of implicit bias against women are also significant. A study based on data from a Swedish funding agency reported that women need to author twice as many publications to obtain the same scientific competence score as men ( Wenneras and Wold, 1997 ). Recently, a study based on funding provided by the NIH (a US research funding agency and one of the largest such agencies in the world) revealed that men obtain more funding renewal than women ( Pohlhaus et al., 2011 ). A Dutch study showed no difference between men and women in the quality of the research proposal/project submitted for funding. However, in their sample, women received less funding due to lower scores in the “quality of the researcher” ( Van der Lee and Ellemers, 2015 ). In the same vein, a Canadian study showed that the funding gap is generated by an unfavorable view of women as scientific leaders and not based on the quality of their studies ( Witteman et al., 2019 ). Importantly, when evaluation committees of funding agencies are aware of gender bias against women, the unequal distribution of funding between men and women is less likely to occur ( Régner et al., 2019 ).

Implicit Racial/Ethnicity Bias

Although the studies discussed above focus on gender stereotypes, the literature also describes implicit judgment bias based on skin color and ethnicity. For example, in one study, fictitious resumes with white-sounding names received 50% more callbacks for interviews than resumes with African-American-sounding names ( Bertrand and Mullainathan, 2004 ). Jaxon et al. (2019) demonstrated in children that the association of brilliance with male gender might depend on the race of the person being evaluated. This intersectional study showed that children associated brilliance with White men but not with Black men ( Jaxon et al., 2019 ). Storage et al. (2016) evaluated the frequency with which college students commented whether their professors were “brilliant” or a “genius” in course reviews on a popular Web site. 1 They showed that fields in which “brilliant” and “genius” appeared more often were also less likely to be pursued by African–American PhDs, predicting less diversity at the PhD level. This evidence indicates a strong racial bias that helps explain, for instance, the extremely low percentage of faculty positions and PhDs earned by African Americans in STEM ( National Science Foundation, 2015 ; U.S. Department of Education, 2017 ; Bernard and Cooperdock, 2018 ). Baron et al. (2006) used an adaptation of the implicit association test (IAT; Greenwald et al., 1998 ) to assess racial bias in children. Reaction time paradigms, on which the IAT is based, have been long used in studies of attention and motivation. Faster or slower response can indicate preset congruent or incongruent association in brain processing, respectively. Baron et al. (2006) tested for associations between the stereotyped group (race: Black and White) and stereotyped domain (evaluation: words with positive connotations and words with negative connotations) and showed that negative implicit race bias was already present in white children aged 6–10 years. The authors also observed that explicit beliefs about race became more egalitarian over time, but implicit race bias remained unchanged.

In a very recent interesting study, Eaton et al. (2020) probed the implicit bias for gender and its association with race/ethnicity. The authors developed an experimental design in which physics and biology professors from United States Research Universities were asked to evaluate identical curriculum vitae (CV) depicting a hypothetical doctoral graduate applying for a postdoctoral position in their field. The reviewers were asked to rate the candidate on competence, hireability, and likeability. The candidate’s name on the CV was used to manipulate race/ethnicity (Asian, Black, Latinx, and White) and gender (female or male), with all other aspects of the CV being the same across conditions. The authors found for physics reviewers an interaction between candidate gender and race/ethnicity. Black women and Latinx candidates were rated the lowest in hireability. This result suggested the robust combined effect of gender and racial/ethnicity biases.

The stereotype of being incompetent/unreliable ( Fiske et al., 1999 ; Jimeno-Ingrum et al., 2009 ; Pérez, 2010 ) creates unfair disadvantages for Latinx scientists, especially in the context of leadership roles or to gain recognition for their studies. The persistent lack of Latinx and African representation on editorial boards is an example of the consequences of racism in the academic world ( Espin et al., 2017 ). Latinx exclusion is so problematic that even the widely applied test used to detect/study automatic attitudes and implicit bias for putative stereotype groups, IAT, did not originally include this topic. The first study to adapt an IAT to detect implicit bias toward Latinx individuals was developed much later than the original studies ( Pérez, 2010 ). Thus, discussions about implicit bias and stereotypes and their harmful effects are imperative in science and should consider the intersections between gender and race/ethnicity.

Stereotype Threat

Another harmful consequence of unfounded cultural stigma is low performance on cognitive tasks generated by the threat of stereotypes. Stereotype threat is a psychological phenomenon that involves people feeling at risk of conforming to negative stereotypes about their social group ( Steele and Aronson, 1995 ; see also the review by Spencer et al., 2016 ). Stereotype threat makes an individual feel a sense of exclusion and lack of belonging that generates psychological stress or anxiety and impairs performance in different situations. Social bonds are necessary for survival and are extremely salient in human beings ( Tomasello, 2014 ), which was highlighted by the COVID-19 pandemic ( Bzdok and Dunbar, 2020 ). Human beings have a constant motivation to form and maintain lasting, positive, and significant interpersonal relationships, even in only a minimal number of these relationships ( Baumeister and Leary, 1995 ). Likewise, perceived social isolation is one of the most pervasive threats to human wellbeing ( Cacioppo and Cacioppo, 2014 ). Humans react to cues of social rejection or exclusion by triggering the autonomic, endocrine and immune systems similarly to when confronting physical attacks or life-threatening events ( Eisenberger, 2012 ), leading authors to tie the word “pain” to both physical and social wounds (see Eisenberger et al., 2003 ). In fact, neuroimaging studies have shown an overlap of neural representations for social and physical pain ( Kross et al., 2011 ; Eisenberger, 2012 ). Indeed, in the most efficient experimental protocol to study stress, participants perform speech and cognitive tasks while being ostensively evaluated by a board of trained researchers ( Kudielka et al., 2007 ). The potentially negative evaluation and the fear of failure trigger the reactions of social pain, focusing attentional resources on the threat and weakening performance ( Gruenewald et al., 2004 ; Angelidis et al., 2019 ).

Belonging to a group stigmatized by negative stereotypes in academic domains exacerbates the pain of social isolation, causing an upward spiral of physiological and mental stress and harmful impairments to performance ( Blascovich et al., 2001 ; Croizet et al., 2004 ; Allen and Friedman, 2015 ). Stereotype threat also reduces working memory capacity ( Schmader and Johns, 2003 ; Rydell et al., 2009 ), which is extremely important to perform well in tasks. Working memory is diverted to address the survival-related threat of social exclusion through intrusive thoughts, anxiety, and stress that are imposed by stereotype threat ( Schmader and Johns, 2003 ). Thus, unsurprisingly, even subtle situational cues for the stress due to stereotype threat can lead to a reduction in performance. In the seminal studies by Steele and Aronson (1995) , the authors showed that African American college students performed worse than European American college students on a verbal task under an experimental condition of stereotype threat, in which the task was described as a “diagnostic of intellectual ability.” In the non-stereotype threat condition, in which the task was described as “a laboratory problem-solving task that was non-diagnostic of ability,” Black and white participants performed equally ( Steele and Aronson, 1995 ). Employing a similar paradigm in France, Croizet and Claire (1998) showed that students with low socioeconomic status performed significantly worse than those with high socioeconomic status in the diagnostic condition but equally well in the non-diagnostic condition. Désert et al., 2009 observed that children with low socioeconomic status (6–9 years old) are already vulnerable to stereotype threat. Low-status children performed significantly worse under a diagnostic condition than under a non-diagnostic condition in a test of intellectual ability, whereas high-status children were unaffected. Other experimental approaches showed undermining of women’s performance in mathematical tests by inducing subtle cues of gender stereotype threat (e.g., Spencer et al., 1999 ; Dar-Nimrod and Heine, 2006 ). Indeed, math-gender cultural stereotypes seem to already affect girls, both implicitly and explicitly, at 6–10 years old ( Cvencek et al., 2011 ).

Furthermore, Johns et al. (2005) performed a study in which men and women completed difficult math problems that were described as a problem-solving task “for a study of general aspects of cognitive processes” or a math test “for a study of gender differences in mathematics performance.” As expected, the results showed that women performed worse than men when the problems were described as a math test because of the stereotype threat created by the association between women and poor performance in math. Interestingly, when the participants were informed about the stereotype threat phenomenon, the differences in performance between women and men disappeared, indicating that “knowing is half the battle,” as the authors suggested in the paper title. Despite all the evidence showing that the stereotype threat is a robust phenomenon, some experimental paradigms have failed to replicate these data or generalize from the laboratory to real-world testing situations ( Cullen et al., 2004 , 2006 ; Sackett et al., 2004 ). However, as pointed out by Spencer et al. (2016) , there is converging evidence that indicates that the stereotype threat is, in fact, responsible for decreases in performance in real tests. In addition, as suggested by Spencer et al. (2016) , the experimental design must be carefully planned to capture the phenomenon of stereotype threat.

Considering these data, individual and institutional actions to disseminate this knowledge about stereotype threat are fundamental to reduce it among stereotyped groups. We believe these actions would be a powerful approach to fight racism, gender disparity, and the false belief of low intellectual ability of those from disadvantaged socioeconomic environments.

In sum, there is ample evidence indicating the presence of unseen forces that work to prevent the progression of women, Latinx, and Black people to positions of greater prominence and leadership, including in the academic world. In Figures 1 – 3 , we suggest several actions aimed at (1) editors and reviewers of scientific journals (2) people in positions of power within funding agencies and research institutions, and (3) to members of selection committees to mitigate this effect. These recommendations are based on the experience of a group of Latinx American scientists comprising Black and Latinx women, teachers, and undergraduate students who participate in women in science working group at universities in the state of Rio de Janeiro, Brazil.

Suggestions for people in positions of power within scientific journals.

Suggestions for people in positions of power within selection committees.

Suggestions for people in positions of power within funding agencies and research institutions.

Why is Diversity Important for Science?

Diversity in science can promote new discoveries, as it expands the points of view, issues, and areas addressed by researchers ( Nielsen et al., 2017 ). Scientists from different backgrounds may choose to investigate different questions, and more importantly, they may approach the same question in different ways. For instance, historically, bird song has been associated with males seeking to attract females. However, a deeper look at this question performed by women researchers showed that female song is common and that both sexes probably sang in the common ancestor of modern songbirds ( Riebel et al., 2019 ). Hong and Page (2004) showed that when participants try to solve complex problems, the ability to see the problem differently, not simply “being smart,” often is the key to discovery. Indeed, when groups of different individuals are working to solve difficult problems, the diversity of the problem-solvers matters more than their individual ability. Another important example of the importance of diversity in the coordination of scientific research concerns the understanding of physiological differences related to health problems. There is evidence that diversity among doctors and health professionals improves access to care for underprivileged groups, develops culturally informed care, and expands the health research agenda ( Cohen et al., 2002 ; Jackson and Gracia, 2014 ; Valantine and Collins, 2015 ). Then, diversity promotes perspectives from different angles, contributing to a more complete understanding of the topic.

Despite the importance of diversity in science, research conducted by underrepresented groups is frequently underestimated. Hofstra et al. (2020) showed that underrepresented groups produce higher rates of scientific novelty. Surprisingly, this study showed that the innovative and disruptive contributions made by underrepresented groups are undervalued and are less accepted by other scholars than are new contributions by gender and racial majorities. In addition, they showed that equally impactful contributions from gender and racial minorities are less likely to result in successful scientific careers. This evidence shows the inequality and injustice that is perpetuated in science. For the building of a fair and truly excellent scientific community, we need efficient policies that promote gender and racial/ethnicity equity.

Converging evidence in the literature suggests that explicit and implicit biases related to gender and race/ethnicity are powerful forces that foster the disparities and inequalities found in our society. Cognitive control can allow individuals to more easily refute explicit bias as they consciously perceive it. However, implicit bias is more prevalent than explicit bias. Therefore, it is crucial to increase awareness of the commonly ignored implicit biases so that each of us can cognitively resignify them. Additionally, institutions must submit proposals to mitigate this problem. With this article, we hope to contribute to reflections, actions, and the development of institutional policies that enable and consolidate diversity in science and reduce disparities in gender, race/ethnicity, which is essential to improve innovation and, therefore, the progress of inclusive science. If we want to combat racism and sexism in science, we need to combat socially constructed implicit bias. This issue is especially important now, as the COVID-19 pandemic may widen the gender and racial gap. Implicit bias is an unseen force that prevents us from moving toward the construction of a more inclusive and diverse science.

Author Contributions

KC, LO, FE, and EV conceived the presented idea of writing a manuscript on this subject. All authors contributed to the literature review and discussion of recommendations. All authors contributed to the final version of the manuscript.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to especially thank all the members of the “Women in Science” working group at Universidade Federal Fluminense.

Funding. This work was supported in part by federal and state Brazilian research agencies (CNPq; CAPES 614 001; CAPES/PRINT; FAPERJ; CNPQ/Institutos Nacionais de ciência e tecnologia/ Instituto Nacional de Neurociência Translacional CNPq/INCT/ INNT; FINEP). KCC, LO, MPG, and EV thank CNPQ and FAPERJ for individual research fellowship.

1 http://RateMyProfessors.com

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The debate about Sonia Sotomayor is not about sexism. It’s more dire.

Some want the supreme court justice to retire so that president biden can name a replacement before... before what happens, exactly.

For the past few months there has been a stealth political campaign going on, the subject of which feels so unseemly that nearly every person publicly participating in the debate insists they would rather not be participating in it, and would, in fact, prefer the debate not be happening at all.

The question: Should Supreme Court Justice Sonia Sotomayor voluntarily retire before the next presidential election?

And, if your answer is yes, are you sexist?

And, if your answer is no, and you support liberal jurisprudence, are you a fool?

If you haven’t been following, the arguments — which have been laid forth by Josh Barro in the Atlantic , Nate Silver , Mehdi Hassan in the Guardian , Sen. Richard Blumenthal (D-Conn.) , and others — amount to this:

1) Sotomayor, at 69, is already several years older than the median American retirement age;

2) The justice’s Type 1 diabetes might indicate a more complicated health map than that of a typical septuagenarian;

3) In the not-unlikely event that Donald Trump wins the presidential election, and Sotomayor has to leave the court during his next term, we can presume that his replacement nominee will turn the Supreme Court into a 7-2 conservative supermajority with repercussions for decades to come.

In other words, Democrats might feel great about Sotomayor’s health and stamina now. But how much are they willing to bet that they’ll feel great about it in four or more years? (For what it’s worth, Barro et al. also make the case that a Democrat in the White House doesn’t ensure the safe passage of Sotomayor’s replacement to the high court, either: a flip of the Senate could result in a Merrick Garland redux, wherein a Republican majority refuses to confirm a Joe Biden nominee).

The counterarguments: That Sotomayor is far from the oldest judge on the court; Clarence Thomas and Samuel Alito are six and five years older. That she is below the average retirement age — which is north of 75 — of Supreme Court justices over the past century. That the diabetes argument is ableist and ill-informed. That justices are freed from term limits for a reason: They are supposed to be immune to political pressure and decide for themselves when to retire.

And finally: Would we be having this discussion if Sotomayor were a man?

“Virtually every person ... pushing is male,” observed Slate writer Dahlia Lithwick on a recent podcast, “and the people defending her are female.”

This is the third draft I have tried to write of a column tackling this subject. The first time, I got bogged down in actuarial tables before accepting that I am not medically trained and I have no idea how long Sonia Sotomayor is going to live. The second time, I went deep on sociology, trying to unpack the gender-based and racial overtones (Sotomayor is the first Latina justice) that make this discussion so fraught, before accepting that I’m writing a column, not a dissertation.

The third time, I realized that I’d been examining the wrong questions. When you ask the right one — and there is only one — then answering it for yourself becomes easy:

Do you think the republic holds?

That is the only question that you need to answer for yourself when figuring out whether, if you are a liberal, you think Sonia Sotomayor should retire.

It’s a loaded question, though, so maybe the best way to answer it is to envision what you see as the most plausible shape American politics will take one or five years from now.

Would another Trump defeat cause his party to become more obstinate and conspiracy-minded, or less? Would his acolytes in Congress become more accepting of a Democratic president’s authority to issue orders and make appointments, or less? If Trump wins, what would “democratic norms” look like?

Do you picture a normal-feeling presidential inauguration in 2025, in which a mass-market pop star sings the national anthem? Or do you picture the Capitol police donning riot gear in preparation for a possible attack on the White House? Do you think the odds of an attack on the White House are actually better than zero?

The functioning of American government is based on a series of codes and agreements. The agreement that the transfer of power will be peaceful. The agreement that presidents should be allowed to appoint qualified justices to fill any Supreme Court vacancy that occurs during their presidency (i.e. the argument that Senate GOP leader Mitch McConnell made when Donald Trump nominated Amy Coney Barrett) rather than Supreme Court vacancies being held open until the Senate likes the commander in chief (i.e. the argument that McConnell essentially made when Barack Obama nominated Garland).

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If you believe we are living in a reality in which the codes and agreements that support American governance will, though taxed, continue to support American governance, then you are fine with Sonia Sotomayor staying on the bench. You can trust that, actuarily speaking, she’ll likely feel great for another decade, and her eventual replacement will be chosen in a manner that is orderly and fair.

If you are a liberal who believes that the next election might fundamentally cripple American democracy, then you don’t want to rely on actuarial tables. You want a spry 49-year-old, right now, who will dedicate the next quarter century to protecting marriage equality and reinstating Roe.

Do you believe the republic holds?

It’s the question that already underpins this debate about Sotomayor. It is the grand, psychic fear that is running subconsciously through everyone’s mind as they get lost in oddly specific discussions about whether — and this was a real debate — the “medic” that Sotomayor has traveled with, according to U.S. Marshals Service records, referred to a human medical professional or merely to medical equipment.

What I appreciate about this question is that it is unsentimental and unsparing. Answering it for yourself does not require you to unpack all of your feelings about Sotomayor as an individual. It also does not require you to solve sexism, although I frankly think Would you be asking this if she were a man? is not the gotcha question people present it as. I don’t think people would be asking this question if Sotomayor were a man; I think people would be demanding it. I think it would be the “Retire, Breyer” movement we saw back in 2022, but dialed up to 11.

Do you think the republic holds does not require you to get philosophical about what the founders intended, or what is just, or what is optimal. It requires you to get practical about what is . Not: Is it fair that some people are laying the entire broken burden of American jurisprudence on the shoulders of one woman? But rather: Where is the Band-Aid? Does someone have a Band-Aid?

If you feel optimistic about the future of the country and are liberal-minded about the law, then I encourage you to feel confident and reassured by Sotomayor’s presence on the Supreme Court. If you end up thinking that she should retire, then you can, and should, insist that her replacement be another brilliant and eminently qualified woman, and you should make sure Joe Manchin III is ready and willing to vote for that replacement.

But this isn’t about Sotomayor. This is about what people think America will look like when Sotomayor eventually does shuffle off this mortal coil. Which I sincerely hope happens when she is in the middle of writing another delightful children’s book, or going dancing, or cycling leisurely around Washington at the age of 112.

• The debate about Sonia Sotomayor is not about sexism. It’s more dire. April 24, 2024 The debate about Sonia Sotomayor is not about sexism. It’s more dire. April 24, 2024
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In a Manhattan Court, a Jury Is Picked to Judge a President

Justice Juan M. Merchan warned against identifying the people who might judge Donald J. Trump, who regularly attacks the justice system.

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By Ben Protess ,  Jonah E. Bromwich ,  Jesse McKinley and Kate Christobek

• Published April 18, 2024 Updated April 25, 2024

Follow our live coverage of Trump’s hush money trial in Manhattan.

At 4:34 p.m. on Thursday, a jury of 12 citizens was selected to determine the fate of an indicted former president for the first time in American history, a moment that could shape the nation’s political and legal landscapes for generations to come.

The dozen New Yorkers will sit in judgment of Donald J. Trump, the 45th president turned criminal defendant, who has been accused of falsifying records to cover up a sex scandal. If the jurors convict Mr. Trump, he could face up to four years in prison, even as he seeks to reclaim the White House as the presumptive Republican nominee.

“We have our jury,” Justice Juan M. Merchan proclaimed as the 12th juror was added.

He then swore the seven men and five women to an oath that they would render a fair and impartial verdict, which they accepted with sober expressions as Mr. Trump stared from the defense table. The jurors could hear opening arguments as soon as Monday.

The selection of the 12 capped a seesaw day in which the judge first excused two people who had been seated earlier in the week, and then hours later replaced them with two new faces and more.

The moment was both routine and never before seen, an act performed every day in courthouses around the country, but never for a former president, a symbol and source of the nation’s political divide.

Mr. Trump, under the Constitution, is entitled to a fair trial by a jury of his peers. And yet he is peerless, a singular force in American politics who was twice impeached and brought democracy to the brink when he refused to accept his election defeat.

Who Are Key Players in the Trump Manhattan Criminal Trial?

The first criminal trial of former President Donald J. Trump is underway. Take a closer look at central figures related to the case.

Now, just as he bent the political world to his will, Mr. Trump is testing the limits of the American justice system, assailing the integrity of jury and judge alike. His attacks have emboldened his base, and might well resonate more broadly on the campaign trial.

But it will be the 12 men and women of the jury — in Mr. Trump’s hometown — who will first decide his fate, before millions more do so at the polls.

The jury’s makeup and the security of its members will be central to the landmark case. Mr. Trump claims he cannot receive a fair trial in one of the nation’s most Democratic counties, a place where he is deeply unpopular, though some of the jurors who ultimately landed on the panel praised him.

One man said during the selection that he believed the former president had done some good for the country, adding, “it goes both ways.” Another juror, in a possible first for the country, said he didn’t have an opinion on Mr. Trump.

The final 12 were a collection of Manhattanites as eclectic as the city itself. They are Black, Asian, white, male, female, middle-aged and young, including one woman in her first job out of college. They work in finance, education, health care and the law. And they live, among other places, in Harlem, Chelsea, the Upper East Side and Murray Hill.

One alternate was also picked before court adjourned. The judge plans to conclude jury selection on Friday, when the lawyers will select the remaining five alternates.

The long day got off to an inauspicious start as Justice Merchan excused the two jurors, including a woman who had developed concerns about her identity being revealed. That fear, she added, might compromise her fairness and “decision-making in the courtroom,” prompting the judge to excuse her.

The precise reason the judge dismissed the other juror was not clear, but prosecutors had raised concerns about the credibility of answers he had given to questions about himself. Asked outside the courthouse whether he believed he should have been dismissed, the man, who declined to give his name, replied, “Nope.”

The dismissals underscored the intense pressure of serving on this particular panel. Jurors are risking their safety and their privacy to sit in judgment of a former commander in chief who is now their fellow citizen, a heavy responsibility that could unnerve even the most seen-it-all New Yorkers.

During jury selection, prospective members are routinely excused by the dozens. And once a trial formally begins, it is not unheard-of to lose a juror for reasons such as illness or violating a judge’s order not to read about the proceeding. But losing two in one day, before opening arguments even began, was unusual — one of many small ways in which this trial will stand apart.

The ousters appeared to rankle the judge, who has striven to keep the trial on schedule. He said he thought the woman who declined to serve would have “been a very good juror.”

Although the judge has kept prospective jurors’ names private, they disclosed their employers and other identifying information in open court. But Justice Merchan instructed reporters to no longer divulge prospective jurors’ current or past employers, a decision that some media law experts questioned.

Inside a chilly courtroom on Thursday, as lawyers on both sides scrutinized a new round of prospective jurors, Mr. Trump stared intently at the jury box and prodded his lawyers, prompting one, Todd Blanche, to shake his head in response.

Already this week, the judge has admonished Mr. Trump for his comments about jurors, warning him not to intimidate anyone in the courtroom.

And the Manhattan district attorney’s office, which accused Mr. Trump of falsifying the records to hide a hush-money deal with a porn star, on Thursday renewed a request that Justice Merchan hold Mr. Trump in contempt of court after he recently reposted attacks on prospective jurors on social media.

The prosecutors have argued that Mr. Trump violated a gag order in the case 10 times, and the judge said he would consider the request next week, when he weighs a related effort to penalize the former president for attacks on witnesses in the case.

Mr. Trump constantly tests the boundaries of the gag order. His political allies, who are not covered by the order, routinely attack the judge and his family. And now, they are attacking the impartiality of the jury.

In early March, Justice Merchan issued an order prohibiting the public disclosure of jurors’ names, while allowing legal teams and the defendant to know their identities.

But before the trial, Mr. Trump’s lawyers requested that potential jurors not be told that the jury would be anonymous unless they expressed concerns. Justice Merchan said that he would “make every effort to not unnecessarily alert the jurors” to this secrecy, merely telling jurors that they would be identified in court by a number.

After the two jurors were excused Thursday, selection continued as lawyers on both sides vetted potential replacements in a courtroom so drafty that even the former president was compelled to acknowledge it, asking reporters, “Cold enough for you?”

Some prospective jurors opted out, acknowledging they might not be fair to Mr. Trump.

One potential juror who was dismissed said he was from Italy and noted that the Italian media had pushed comparisons between Mr. Trump and Silvio Berlusconi, the country’s former prime minister, a media magnate caught up in sex scandals.

“It would be a little hard for me to retain my impartiality and fairness,” he said.

The potential jurors were all questioned about their politics, media diets and views on Mr. Trump. The lawyers were then expected to scrutinize them for any signs of bias, including old social media posts about the former president.

One prospective juror, who had a long career in law enforcement, seemed unlikely to have made any problematic posts. He disclosed that he only had a flip phone.

“And therefore I do not watch any podcasts,” he says, eliciting laughter from the courtroom on an otherwise tense day.

The prosecution used one of its challenges to oust that juror, who “as a wannabe hockey player” had also complimented Mr. Trump on the skating rink his company used to operate in Central Park. It used another to dismiss a man who said he had been “impressed” with the path the former president forged.

The defense ousted several additional potential jurors, including a woman who once stayed overnight at the home of one of Mr. Trump’s lawyers. Justice Merchan had declined to remove her himself at the request of that lawyer, Susan Necheles, even though Ms. Necheles said the woman’s presence was “awkward.”

The judge removed a woman who had assailed Mr. Trump on social media as a “racist sexist narcissist.” When she reread the posts in court on Thursday, the potential juror added, “Oops. That sounds bad.” She later apologized for the tone of her posts.

One woman who expressed skepticism about Mr. Trump made it onto the jury. She said that she didn’t have strong opinions about Mr. Trump, but added, “I don’t like his persona. How he presents himself in public.”

She then went on, though, “I don’t like some of my co-workers, but I don’t try to sabotage their work,” drawing laughter from the jury box.

Nate Schweber , Maggie Haberman , Wesley Parnell and Matthew Haag contributed reporting.

Ben Protess is an investigative reporter at The Times, writing about public corruption. He has been covering the various criminal investigations into former President Trump and his allies. More about Ben Protess

Jonah E. Bromwich covers criminal justice in New York, with a focus on the Manhattan district attorney’s office and state criminal courts in Manhattan. More about Jonah E. Bromwich

Jesse McKinley is a Times reporter covering upstate New York, courts and politics. More about Jesse McKinley

Kate Christobek is a reporter covering the civil and criminal cases against former president Donald J. Trump for The Times. More about Kate Christobek

Our Coverage of the Trump Hush-Money Trial

News and Analysis

Prosecutors accused Donald Trump of violating a gag order four additional times , saying that he continues to defy the judge’s directions  not to attack witnesses , prosecutors and jurors in his hush-money trial.

Trump’s criminal trial in Manhattan is off to an ominous start for the former president, and it might not get any easier  in the days ahead. Here’s why.

The National Enquirer  was more than a friendly media outlet  for Trump’s presidential campaign in 2016. It was a powerful, national political weapon that was thrust into the service of a single candidate , in violation of campaign finance law.

More on Trump’s Legal Troubles

Key Inquiries: Trump faces several investigations  at both the state and the federal levels, into matters related to his business and political careers.

Case Tracker:  Keep track of the developments in the criminal cases  involving the former president.

What if Trump Is Convicted?: Could he go to prison ? And will any of the proceedings hinder Trump’s presidential campaign? Here is what we know , and what we don’t know .

Trump on Trial Newsletter: Sign up here  to get the latest news and analysis  on the cases in New York, Florida, Georgia and Washington, D.C.