case study of gender bias

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Research: How Bias Against Women Persists in Female-Dominated Workplaces

• Amber L. Stephenson,
• Leanne M. Dzubinski

A look inside the ongoing barriers women face in law, health care, faith-based nonprofits, and higher education.

New research examines gender bias within four industries with more female than male workers — law, higher education, faith-based nonprofits, and health care. Having balanced or even greater numbers of women in an organization is not, by itself, changing women’s experiences of bias. Bias is built into the system and continues to operate even when more women than men are present. Leaders can use these findings to create gender-equitable practices and environments which reduce bias. First, replace competition with cooperation. Second, measure success by goals, not by time spent in the office or online. Third, implement equitable reward structures, and provide remote and flexible work with autonomy. Finally, increase transparency in decision making.

It’s been thought that once industries achieve gender balance, bias will decrease and gender gaps will close. Sometimes called the “ add women and stir ” approach, people tend to think that having more women present is all that’s needed to promote change. But simply adding women into a workplace does not change the organizational structures and systems that benefit men more than women . Our new research (to be published in a forthcoming issue of Personnel Review ) shows gender bias is still prevalent in gender-balanced and female-dominated industries.

• Amy Diehl , PhD is chief information officer at Wilson College and a gender equity researcher and speaker. She is coauthor of Glass Walls: Shattering the Six Gender Bias Barriers Still Holding Women Back at Work (Rowman & Littlefield). Find her on LinkedIn at Amy-Diehl , Twitter @amydiehl , and visit her website at amy-diehl.com
• AS Amber L. Stephenson , PhD is an associate professor of management and director of healthcare management programs in the David D. Reh School of Business at Clarkson University. Her research focuses on the healthcare workforce, how professional identity influences attitudes and behaviors, and how women leaders experience gender bias.
• LD Leanne M. Dzubinski , PhD is acting dean of the Cook School of Intercultural Studies and associate professor of intercultural education at Biola University, and a prominent researcher on women in leadership. She is coauthor of Glass Walls: Shattering the Six Gender Bias Barriers Still Holding Women Back at Work (Rowman & Littlefield).

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Gender bias in academia: a lifetime problem that needs solutions

Anaïs llorens.

1. Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA.

Athina Tzovara

2. Institute for Computer Science, University of Bern, Switzerland.

3. Sleep Wake Epilepsy Center ∣ NeuroTec, Department of Neurology, Inselspital, Bern University Hospital, University Bern, Bern, Switzerland

Ludovic Bellier

Ilina bhaya-grossman.

4. Department of Bioengineering, University of California Berkeley, Berkeley, CA, USA.

Aurélie Bidet-Caulet

5. Brain Dynamics and Cognition Team, Lyon Neuroscience Research Center, CRNL, INSERM U1028, CNRS UMR 5292, University of Lyon, Lyon, France.

William K. Chang

Zachariah r. cross.

6. Cognitive and Systems Neuroscience Research Hub, University of South Australia, Adelaide, Australia.

Rosa Dominguez-Faus

7. STEPS Program, University of California, Davis, CA, USA.

Adeen Flinker

8. NYU School of Medicine, New York, USA.

Yvonne Fonken

9. Department of Psychiatry, University of Oxford, Oxford, UK.

Mark A. Gorenstein

10. Department of Psychology, University of California, Berkeley, Berkeley, CA, USA.

Chris Holdgraf

11. The Berkeley Institute for Data Science, Berkeley, CA, USA.

Colin W. Hoy

Maria v. ivanova, richard t. jimenez.

12. Department of Brain and Cognitive Science College of Natural Sciences, Seoul National University, Seoul, Korea.

Julia WY. Kam

13. Department of Psychology, University of Calgary, Calgary, Canada.

Celeste Kidd

Enitan marcelle, deborah marciano.

14. Haas School of Business, University of California Berkeley, Berkeley, CA, USA.

Stephanie Martin

15. Department of Cognitive Science, University of California San Diego, San Diego, CA, USA.

Nicholas E. Myers

16. Department of Experimental Psychology and Oxford Centre for Human Brain Activity, Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom.

Karita Ojala

17. Institute of Systems Neuroscience, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

18. Department of Psychology, the Hebrew University of Jerusalem, Jerusalem, Israel.

Pedro Pinheiro-Chagas

19. Laboratory of Behavioral and Cognitive Neuroscience, Stanford Human, Stanford University, Stanford, CA, USA.

Stephanie K. Riès

20. School of Speech, Language, and Hearing Sciences and Center for Clinical and Cognitive Neuroscience, San Diego State University, San Diego, CA, USA.

Ignacio Saez

21. Department of Neurosurgery, University of California Davis, Sacramento, CA, USA.

Ivan Skelin

22. Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, USA.

Katarina Slama

Brooke staveland, danielle s. bassett.

23. Departments of Bioengineering, Electrical & Systems Engineering, Physics & Astronomy,Psychiatry, and Neurology, University of Pennsylvania, Philadelphia, PA, USA.

24. Santa Fe Institute, Santa Fe, NM 87501 USA.

Elizabeth A. Buffalo

25. Department of Physiology and Biophysics and School of Medicine, Washington National Primate Research Center, University of Washington, Seattle, WA, USA.

Adrienne L. Fairhall

26. Department of Physiology and Biophysics and Computational Neuroscience Center, University of Washington, Seattle, WA 98195, USA.

Nancy J. Kopell

27. Department of Mathematics & Statistics, Boston University, Boston, MA, USA.

Jack J. Lin

28. Comprehensive Epilepsy Program, Department of Neurology, University of University of California Irvine, Irvine, CA, USA.

29. Department of Biomedical Engineering, Henry Samueli School of Engineering, Irvine, CA, USA.

Anna C. Nobre

Dylan riley.

30. Department of Sociology, University of California Berkeley, Berkeley, CA, 94720-1980, USA.

Anne-Kristin Solbakk

31. Department of Psychology, Oslo University Hospital-Rikshospitalet, Oslo, Norway.

32. Department of Neurosurgery, Oslo University Hospital - Rikshospitalet, Oslo, Norway.

33. RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway.

34. Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway.

Joni D. Wallis

Xiao-jing wang.

35. Center for Neural Science, New York University, 4 Washington Place, New York, NY 10003, USA.

Shlomit Yuval-Greenberg

36. School of Psychological Sciences and Sagol School of Neuroscience, Tel-Aviv University, Ramat Aviv, 6997801, Tel Aviv-Yafo, Israel.

Sabine Kastner

37. Princeton Neuroscience Institute, and Department of Psychology, Princeton University, Princeton, NJ 08544, USA.

Robert T. Knight

Nina f. dronkers.

38. Department of Neurology, University of California, Davis.

Despite increased awareness of the lack of gender equity in academia and a growing number of initiatives to address issues of diversity, change is slow and inequalities remain. A major source of inequity is gender bias, which has a substantial negative impact on the careers, work-life balance, and mental health of underrepresented groups in science. Here, we argue that gender bias is not a single problem but manifests as a collection of distinct issues that impact researchers' lives. We disentangle these facets and propose concrete solutions that can be adopted by individuals, academic institutions, and society.

Despite increased awareness of the lack of gender equity in academia, change is slow and inequalities remain. We disentangle the different aspects of gender bias impacting woman researchers throughout their lives. We expose the different issues and discuss potential solutions that can be adopted by individuals, academic institutions, and society.

2. Introduction

The past decades have seen tremendous scientific progress and astonishing technological advances that not long ago seemed like science fiction. Yet, such scientific progress stands in stark contrast to progress in improving the participation of underrepresented groups in academia, particularly in the fields of science, technology, engineering and mathematics, known as STEM. A report from the National Institutes of Health (NIH) published in 2017 highlights the gender disparities encountered in science: Out of 16 NIH directors, only 1 was a woman; in the top 10 research institutes in the USA, the percentage of women with tenure among all professors was at most 26%, and in some cases even below 20%. Women occupied 37% of the NIH intramural research program tenure-track body, but only 21% attained tenured status, with women of color occupying only 5% of tenured positions (addressing gender inequality in the NIH intramural research program). The numbers show similar trends for PhD programs in the US. According to the Society for Neuroscience, the percentage of women applicants in PhD programs has increased in the recent years, from 38 % in 2000-2001 to 57 % in 2016-2017, with a matriculation rate of 48% for women in 2016-2017. By contrast, women represented only 30% of all faculty for PhD programs.

The statistics are similar in Europe. The European Research Council (ERC-Equality of opportunity in ERC Competitions) reported that only 32% of its panel members and 27% of its grantees in the Horizon 2020 program were women. In the Netherlands, 44% of PhDs were awarded to women in 2018, yet only 22% of the tenured faculty were women. A similar trend is reported in Switzerland, where close to 40% of fixed term professorships in 2017 were held by women, but for tenured positions the fraction of women dropped to 25%.

These statistics confirm the gender disparity that exists in higher academic positions, despite an almost equal representation across disciplines at earlier career stages (see Gruber et al., 2020 for a thorough investigation of gender disparities in psychological science). A putative cause of this phenomenon is gender bias, i.e., prejudice based on gender (encompassing the identity and the expression of that gender). Gender bias can be explicit or implicit. Explicit bias is a conscious and intentional evaluation of a particular entity with some degree of favor or disfavor ( Eagly and Chaiken, 1998 ). Implicit bias reflects the automatic judgment of the entity without the awareness of the individual ( Greenwald and Banaji, 1995 ). These types of bias emerge from different sources such as stereotypes, prejudice, and discrimination ( Fiske, 1998 ), which reflect general expectations about members of a given social group. Gender stereotypes are broadly shared and reflect differences between women and men in their perspective and manner of behavior. Importantly, gender stereotypes also impact the way men and women define themselves and are treated by others, which in turn contributes and perpetuates such stereotypes (see Ellemers, 2018 for review). Gender bias impacts all women, with even more impact on women whose gender intersects with other identities that are often discriminated against, including but not limited to race and ethnicity (see Quick Take: Women in Academia), socio-economic status, religion, gender expression, gender identity, sexual orientation, or disabilities ( Armstrong and Jovanovic, 2015 ). Moreover, it has been shown that gender stereotypes influence the enrollment of women in STEM in many countries ( Miller et al., 2015 ; Hanson et al. 2017 ). As such, properly tackling this issue requires both structural and cultural change. Many of the biases and solutions presented in this article can apply to and be amplified in other minority groups (see our discussion of intersectionality), but a comprehensive assessment of those issues is beyond the scope of this paper. Indeed, pervasive gender biases do not start at the academic level, but they are deeply rooted in many societies and even appear early in life, impacting young girls’ career aspirations and lifetime educational achievements ( Makarova et al., 2019 ). For instance, in many cultures, it is a long-standing stereotype that boys are better at math than girls ( Else-Quest et al., 2010 ), which, in turn, impacts young girls’ performance on math tests ( Spencer et al., 1999 ) despite no intrinsic or biological difference ( Kersey et al., 2019 ; Shapiro and Williams, 2012 ). Parents’ and teachers’ expectations can also show biases that influence children’s attitudes and performance in math ( Gunderson et al., 2012 ). This gender stereotyping through interactions with parents, educators, peers, and the media has a negative effect on girls’ interest and confidence in their performance in STEM subjects, potentially reducing interest in research careers in STEM later in life ( Cheryan et al., 2015 , 2017 ).

Here, we will focus on gender bias at the university level, which forms a further bottleneck for gender equity in STEM. The women-to-men ratio progressively decreases with advancing degrees and career stages. Despite remarkable progress made over the last three decades to mitigate gender bias ( Eagly, 2018 ), equity is still far from being reached in academia. Multiple studies have systematically documented bias in every aspect of academia ( Fernandes et al., 2020 ), including journal article and innovation citations ( Dworkin et al., 2020b ; Hofstra et al., 2020 ), publication rates ( West et al., 2013 ), patent applications ( Jensen et al., 2018 ), hiring decisions ( Nielsen, 2016 ), research grant applications ( Burns et al., 2019 ), evaluations of conference abstracts ( Knobloch-Westerwick et al., 2013 ), symposia speaker invitations ( Schroeder et al., 2013 ), postdoctoral employment ( Sheltzer and Smith, 2014 ), prestigious science awards ( Lunnemann et al., 2019 ), and tenure decisions ( Weisshaar, 2017 ). These forms of bias are intertwined, and evolve and accumulate along the career path (see Figure 1 ). Their combination can lead to a gradual abandonment of scientific careers by many women, the numbers of which decrease as career stages progress.

Expression of the accumulation of the different facets of gender bias throughout a woman researcher’s career organized according to when they begin to have an impact. Each line represents one aspect of the gender bias and covers the career stages it is prevalent in. The dot represents the peak in time of a given aspect.

Given the prevalent and deep-rooted nature of gender bias in academia, we aim to unravel different forms of bias, evaluate their manifestation over the career-span, and provide suggestions towards resolving gender disparity. We explain how pervasive gender bias affects different components, dimensions and roles of academics, and how these barriers to women’s advancement differ across each stage of career development. Our goal is to assemble information regarding the different facets of gender bias in a digestible format for the neuroscientific community. We aim to launch a discussion around the multifaceted and deeply rooted issues surrounding gender bias in academia and, in particular, in the field of neuroscience. We discuss problems faced by women in science, which are often taking place behind closed doors, providing information and increased awareness of central issues to academics and institutions seeking a balanced and fair environment. We also recommend both tested and untested concrete solutions to help mitigate the negative consequences of bias along three axes: at the individual (i.e., actions we can take as colleagues, friends, or mentors), institutional (i.e., policies and regulations), and societal levels (i.e., legislative action concerning society at large).

Changes in society and culture are often slow and difficult to implement, but without ongoing awareness, gender equality cannot be achieved. Solutions to the problem of gender bias have been difficult to achieve for many reasons, and some may be more tenable in certain circumstances than others. Here, we present exemplary policies from progressive institutions that have been effective in alleviating gender bias mostly in STEM, and specifically in neuroscience. We also describe quantitative tracking tools ( Table 1 ) that contribute to identifying and mitigating bias. As several manifestations of bias do not yet have concrete solutions with demonstrated results, we also propose some untested suggestions that may prove useful, and which future research could address ( Table 2 ). It is our hope that this article will continue the conversation toward resolving gender bias and bring us closer to tangible results.

Tools and Resources for Addressing Gender Bias in Academia

Summary of the different actions suggested throughout the manuscript to mitigate gender bias by section and level of responsibility. Each action is classified by its current status (tested/recommended, tested/debated or implemented) and supported by some examples of highlighted advocates. Note that many solutions for the individual are difficult to quantify, and so are left blank.

3. Gender biases are amplified through career stages

Though gender stereotypes are already strongly shaped in childhood ( Makarova et al., 2019 ), college or university study is a further bottleneck to gender equity. Even in their first year beyond high-school, women are 1.5 times more likely than men to leave the STEM higher education pipeline ( Ellis et al., 2016 ). In more advanced university degrees and career stages, the women-to-men ratio progressively decreases, referred to as the “scissors effect.” In most countries, the point where the effect begins is at the start of the university years with equal numbers of women and men enrolled. The gap widens (like an open pair of scissors) by the end of the postdoctoral career stage (European commission report 2015, GARCIA Project). In the United States, the gender gap continues to grow between the postdoctoral and associate professor years with women transitioning to principal investigator positions at about a 20% lower rate than men ( Lerchenmueller and Sorenson, 2018 ). Similar data have been reported for other agencies and countries, highlighting the widening gender gap across the career stages ( Burns et al., 2019 ; McAllister et al., 2016 ; Pohlhaus et al., 2011 ). Although the percentage of women among undergraduates, graduate students, and postdoctoral researchers has increased in the past few decades, women remain largely underrepresented in STEM faculty positions ( Beede et al., 2011 ; Field of degree: Women-NSF). Possible factors contributing to the increasing gender gap as careers progress will be reviewed in the following sections, where we will disentangle the various aspects contributing to each factor and propose concrete solutions to close the gender gap.

4. Gender bias hinders scientific productivity, authorship and peer-review

Women are systematically underrepresented as first and last authors in peer-reviewed publications relative to the proportion of women scientists in the field ( Dworkin et al., 2020b ; West et al., 2013 ). The discrepancy is particularly evident for senior author positions, as well as single-authored papers and commissioned editorials, i.e., positions typically reflective of senior roles ( Holman et al., 2018 ; Schrouff et al., 2019 ; West et al., 2013 ). Moreover, an overall increase in gender differences in productivity has accompanied the steady increase of women in STEM over the past decades. This difference in productivity between men and women is mostly explained by a higher female than male dropout rate while the yearly difference in productivity between genders is relatively small ( Huang et al., 2020 ). Furthermore, a study of peer review based on 145 journals in various fields reported that women submit fewer papers than men ( Squazzoni et al., 2021 ). The underrepresentation of women increases with the impact factor of the journal ( Bendels et al., 2018 ). Neuroscience is no exception, as women authors are less likely to submit to high-profile journals, including senior women. In 2016, only around 20% of neuroscience papers sent to Nature had a woman as corresponding author (Promoting diversity in neuroscience, 2018). But even when women do submit to such journals they face gender bias. Indeed, several studies where the identity of the authors was experimentally manipulated demonstrated that conference abstracts, papers, and fellowship applications were rated as having higher merit when they were supposedly written by men. These effects were even stronger in scientific fields viewed as more “masculine” ( Knobloch-Westerwick et al., 2013 ; Krawczyk and Smyk, 2016 ). Furthermore, a recent study of 9,000 editors and 43,000 reviewers from Frontiers journals demonstrated that women are underrepresented as editors and peer reviewers ( Helmer et al., 2017 ). Additionally, all editors, regardless of whether they are men or women, display a same-gender preference (homophily), which at the moment favors men in part because there are more men in the field ( Murray et al., 2019 ).

In addition to publications, a screening of approximately 2.7 million US patent applications indicated that there was also discrimination in the patent review process, leading to relatively few approved patent applications registered by women inventors ( Jensen et al., 2018 ). Many of these effects were larger in fields with a generally higher representation of women, such as life sciences, than in technology areas ( Hunt et al., 2013 ; Sugimoto et al., 2015 ; Whittington and Smith-Doerr, 2008 ). Though gender bias in authorship has been explicitly acknowledged for years (Women in neuroscience: a numbers game, 2006), it has changed minimally over the last decade ( Bendels et al., 2018 ; Holman et al., 2018 ; 2018 ). Although the publication gap is decreasing, it is wrong to assume that there will be a proportional representation anytime soon without further active interventions ( Bendels et al., 2018 ). In some disciplines, such as math, computer science, and surgery, gender parity in publications is unlikely to be reached in this century due to the current slow rates of increased representation of women ( Holman et al., 2018 ). Other fields, such as psychology, have seen relatively greater increases in publications by men authors over time, further widening the gender gap ( Ceci et al., 2014 ). Given that publishing, particularly in high-profile journals, is critical for hiring decisions and career advancement, this inequality in authorship will continue to contribute to the increasing gender disparity across academic ranks ( Fairhall and Marder, 2020 ).

Suggestions for decreasing gender bias at an individual level:

Increasing awareness for all scientists, editors and reviewers regarding gender bias in authorship could help mitigate this issue. All scientists could seek out education in gender bias, and proactively consider how to adjust their own behavior to ensure equity in their reviews.

Suggestions for decreasing gender bias at the institutional level:

Finding alternatives to single-blind review is needed to increase the transparency of the peer review process ( Barroga, 2020 ; Lee et al., 2013 ). One proposed solution to mitigate gender bias in the review process is adoption of double-blind review, hiding the authors’ name ( Rodgers, 2017 ). Double-blind review has been introduced in several fields, such as ecology and computational sciences, and has been successful in reducing biases due to geographic location or university reputation ( Bernard, 2018 ; Budden et al., 2008 ; Mulligan et al., 2013 ; Snodgrass, 2006 ; Tomkins et al., 2017 ). It is also standard usage in the top journals in sociology, political science, and history and was introduced in some neuroscientific journals such as eNeuro. However, the efficacy of double-blind review in reducing gender bias is still unclear. An early study found that introducing double-blind peer review significantly increased the number of first-authored papers by women ( Budden et al., 2008 ), whereas later studies found no effect on review gender bias ( Cox and Montgomerie, 2019 ; Tomkins et al., 2017 ). It is possible that more recent blind reviews were compromised by the use of preprint servers that list authors’ full names. Another proposed solution is an open peer review as currently implemented in Frontiers journals where the names of the authors and the editor and reviewers are made public upon publications. One last alternative would be a hybrid peer review system combining open discussion between scientists and peers while preserving the anonymity of the latter ( Bravo et al., 2019 ; Lee et al., 2013 ). Such a system could consist of a pre- or post- publication discussion platform that allows referees, editors, and authors to interact providing feedback on a paper.

Importantly, academic journals need to pay attention to potential sources of gender bias in order to be able to identify ways to mitigate them. One way to encourage review and editorial panels to improve accountability and transparency is to make demographic information regarding authors and reviewers publicly accessible ( Murray et al., 2019 ). This is already implemented by PEERE, an European protocol designed to be an equitable way to get more data on the peer review process ( Table 1 ; Squazzoni et al., 2017 ). Moreover, an increasing number of publishing groups are publicly releasing statements in support of diversity in authors, citations, and/or referees ( Sweet, 2021 ; 2018). As a recent example, Cell Press is encouraging authors to evaluate their citation lists for biases, as well as to ensure diversity in their research participants, authors and collaborators ( Sweet, 2021 ). It is also the case of eLife which sets a twice-yearly report about actions taken to improve transparency, promote equity, diversity and inclusion in the publishing process as well as in their editorial board. Such initiatives are setting a positive example that could be followed by more publishers across all academic fields.

5. Gender differences in the number of citations

Citation metrics have emerged as a critical index of productivity in the biological and cognitive sciences. Citation counts influence hiring and tenure decisions, grant awards, speaker invitations, and career recognition. As an example, a study in the field of astronomy showed that in 149,000 publications, a paper whose lead-author was a woman received 10% fewer citations on average than similar papers with a man as leading author ( Caplar et al., 2017 ). In top neuroscience journals, that number is even greater; papers with women as first and last author receive 30% fewer citations than expected given the number of such papers in the field ( Dworkin et al., 2020b ).

Furthermore, recent research reveals that contemporary citation practices skew these metrics in favor of men, undervaluing woman-led research of equivalent quality and potential impact. In particular, men undercite women scientists relative to men scientists, and their rates of self-citation are higher than those of women ( Dworkin et al., 2020b ; King et al., 2017 ). Additionally, men are more likely to use promotional language, such as positive words (e.g. “unprecedented” or “excellent”) in the title or abstract, which in turn leads to more citations and an inflation of the h-index ( Cameron et al., 2016 ; Kelly and Jennions, 2006 ; Lerchenmueller et al., 2019 ; Woolston, 2020 ). It is also possible that citation bias is exacerbated by the use of social media platforms such as Twitter. A recent randomized controlled trial demonstrates that papers that were tweeted received more citations at the end of one year than papers that were not tweeted ( Luc et al., 2021 ). Women academics have disproportionately fewer Twitter followers, “likes”, and re-tweets than men academics, controlling for their social media activity levels and professional rank ( Zhu et al., 2019 ).

Suggestions at the individual level:

At the individual level, all authors should be more aware of which articles they cite in their work. In particular, articles that already have a high number of citations are seen as “seminal” thus exacerbating biases that may not reflect quality. In the case of multiple possible citations, they should seek to balance the number of citations between genders according to a chosen model of research ethics. In the distributional model, citations would be distributed in a manner that is proportional to the percentages in their field, while in a diversity model, citations would be distributed in a manner that seeks to proactively counteract a history of inequality ( Dworkin et al., 2020a , 2020b ). Practically, efforts to diversify one’s reference list can be supported by algorithmic tools that now exist to predict the gender of the first and last author of each reference by using databases that store the probability of a name being carried by a woman ( Zhou et al., 2020 ). This tool already exists in neuroscience ( Table 1 ) and we recommend wide implementation across academic fields.

Suggestions at the institutional level:

One proposed solution is to increase diversity in review and editorial panels ( Murray et al., 2019 ) as implemented by Progress in Neurobiology and Elife among other journals. As a notable example, Progress in Neurobiology, has an editorial board with 80% women associate editors. This can help mitigate bias, but may not be sufficient, as even women might be biased against other women. One option is to develop alternative citation metrics that account for the influence of self-citation and gender bias. One example of these metrics are the m-index, which is the h-index adjusted for career age, or the m(Q)-index, which adjusts for career age and excludes self-citations ( Cameron et al., 2016 ).

We also suggest that journal editors incorporate existing quantitative tools that analyze the gender ratio of a reference list by probabilistically inferring the gender of authors in a list of citations (see Table 1 ). Journals could then require authors to either eliminate any possible bias or provide a detailed justification for their deviation from the expected distribution. We also recommend the implementation of additional algorithmic tools in scientific journal submission websites to identify under-cited articles by women authors in a subfield, or to notify authors of citation biases in their submissions. Lastly, journal editors could consider increasing limits on the number of citations to accelerate the diversification of reference lists. As an example, Neuron modified their guidelines to exclude reference sections from the maximum character limit in research article submissions.

6. Scientific funding and awards are heavily biased

Funding is crucial to a researcher’s scientific progression and career advancement, including gaining tenure and broad professional recognition ( Charlesworth and Banaji, 2019 ; Duch et al., 2012 ). While the funding landscape is slowly evolving towards gender parity, women still face substantial challenges as they compete for limited resources. Some funding agencies collect data on the distribution of funding across genders. For instance, the percentage of NIH research grants awarded to women has been steadily growing over the past two decades: increasing from 23% in 1998 to 34% in 2019 (NIH Data Book—Data by Gender, 2020), with similar patterns observed for the National Science Foundation (NSF), the United States Department of Agriculture, and the European Research Council (ERC) ( Charlesworth and Banaji, 2019 ; ERC consolidator grants 2019 - statistics, 2019). However, despite this positive trend, progress still needs to be made as women scientists typically hold fewer grants and receive smaller awards compared to men scientists (National Institutes of Health, 2020; 2019).

Interestingly, while women receive more NIH research career grants at an early career stage than men (54%), the percentage of grants awarded to women progressively drops for grants associated with later career stages (research project grants: 34%; research center grants: 26%; NIH, 2020). Similar data have been reported for other agencies and countries, highlighting the widening gender gap across career stages: women are awarded fewer larger grants and are less likely to have them renewed than men ( Burns et al., 2019 ; McAllister et al., 2016 ). Possible factors contributing to this increasing gender gap might be publication and citation practices, family circumstances, and other barriers resulting from implicit and explicit gender stereotypes ( Pohlhaus et al., 2011 ). Moreover, the percentage of women submitting research grant proposals as a PI is less than expected relative to their representation in all fields but engineering ( Rissler et al., 2020 ).

The funding gap is also apparent in the amount awarded, with men typically asking for more funds ( Waisbren et al., 2008 ) and obtaining larger grants than women (National Institutes of Health, 2020). A recent study found a median gender disparity in NIH funding of $39K per year awarded to first-time principal investigators, while no significant differences by gender were found in the performance measures (i.e., median number of articles published per year, median number of citations per article, and the number of areas of research expertise in published articles prior to their first NIH grant; ( Oliveira et al., 2019 ). The differences were even more pronounced for funding acquired by investigators at prominent U.S. universities (median gender difference of $82k). Although the gender gap is smaller regarding R01 awards (median difference $16k), men receive more of them (after controlling for other performance measures; (National Institutes of Health, 2020; Pohlhaus et al., 2011 ). Furthermore, data from the NIH also show that the most dramatic differences in funding amounts were observed for research center grants (average difference of $476k), again highlighting increasing disparity at later career stages.

Although the proportion of women who receive career awards for their scientific contributions has steadily increased over the past decades, women still receive substantially fewer prizes than men, and less money ( Ma et al., 2019 ). Across 13 major STEM disciplines, only 17% of professional award winners were women ( Lincoln et al., 2012 ). This number is lower than expected based on overall representation by women in the STEM fields (38% for junior faculty and 27% for senior), likely indicating review bias with professional efforts and accomplishments of women not receiving the same recognition. Gender disparity is even more dramatic for more prestigious awards. For instance, women represent only 21% of Kavli Prize winners, 14% of recipients for the National Medal of Science, 3% for the Nobel Prize in Chemistry, 3% for the Fields Medal in Mathematics, and 1% for the Nobel Prize in Physics ( Charlesworth and Banaji, 2019 ; RAISE Project 2018).The year 2020 was a unique year in Nobel Prizes, with two women winning the prize for Chemistry and one woman the prize for Physics. Despite this positive step, gender equity is still lacking, and active efforts need to be continued to ensure that women will keep being represented in prestigious awards in the years to come. Gender bias in distinguished recognition perpetuates the falsehood that only men can aspire to the highest levels of academic achievement, thus sending a harmful message to younger generations of aspiring scientists. Furthermore, disparities in funding and recognition tend to have a subsequent snowball effect. Indeed, grant funding drives scientific productivity, which in turn drives promotions; promotions drive increases in salaries and stature; stature drives recognition. Gender bias at each of these collective steps serves to further hamper the advancement of women in their academic careers.

Suggestions at the Individual level:

The process of applying for certain career transition awards across scientific disciplines, such as NIH K awards or the Burroughs-Wellcome career award, forces both the applicant and the mentor to envision the candidate in the role of a faculty member, something that can have a profound effect on the candidate’s internal model of self and the attitude of the mentor.

Suggestions at the Institutional level:

Solutions could emerge directly from funding agencies in all scientific disciplines if they commit to actively monitoring for gender differences and ensuring gender equity in grant application rates, success rates and amounts awarded. To ensure fairer funding, we suggest that agencies introduce a gender target for grant applicants, success rates and amounts awarded. This could consist of a defined percentage of women researchers or amount of funding allocated to them at different career stages. Crucially, funding agencies should hold themselves accountable for attracting more female applicants, by changing the procedures used in their competitions to create more equitable outcomes ( Niederle, 2017 ; Niederle and Vesterlund, 2011 ). Further, it has been shown that having a target representation among women leads to increased numbers of applications by women; this brings stronger candidates to the competition, with little reverse discrimination -i.e. discrimination in favour of women- ( Niederle et al., 2013 ). Importantly, in contrast to some affirmative action approaches, this approach preserves the performance and the quality of the competition ( Balafoutas and Sutter, 2012 ).

This step could be enhanced by alerting the committee to potential gender bias (that both male and female reviewers are susceptible to) and even prefacing grant reviews with bias training. In addition, women are particularly underrepresented as leaders on large projects and/or international collaborations, and adjusting this imbalance could help establish overall gender equity in research funding. Finally, the Canadian Institutes of Health Research have successfully increased the number of female grant recipients by creating funding mechanisms that dispense awards focusing on the merit of the scientific proposal instead of the merit of the principal investigator ( Witteman et al., 2019 ).

Moreover, monitoring implicit bias by making the demographics information of former grantees accessible to funding committees could help pinpoint the disparities and distribute the resources more equitably ( Choudhury and Aggarwal, 2020 ). To reduce bias in the amount of requested funding, we suggest that submission portals implement artificial intelligence tools to provide researchers with recommendations on amounts of funding given their career stage and type of research. This suggestion follows the findings of Bowles and colleagues, who have shown that women ask for as much as men when ambiguity about bargaining range is reduced ( Bowles et al., 2005 ).

Importantly, department chairs and deans must commit to an equitable distribution of institutional resources across genders. Additionally (but not as an alternative), department chairs could actively encourage, support and provide the means (for example through release time, workshops, etc.) to all faculty members to pursue applications for career awards and large grants such as program projects and center grant funding (see Gender Equity Guidelines for Department Chairs).

7. Teaching evaluations reflect biases and gender-role expectations

Gender biases are ubiquitous in the classroom, affecting both the students and their professors ( Fan et al., 2019 ). At the student level, what professors integrate in their course syllabi shapes students’ knowledge and perception of academia. Women are under-cited as well as under-assigned in syllabi: 82% of assigned readings in graduate training in international relations across 42 U.S. universities are written by all-men authors ( Colgan, 2017 ), and only 15 of the 200 most frequently assigned works in the section “politics” of the Open Syllabus Project are authored by at least one woman ( Sumner, 2018 ).

At the professor level, large-scale studies have found that women instructors receive lower than average scores on their student evaluations in comparison to men and that gender bias can be so substantial that more effective instructors are rated lower than less effective ones ( Mengel et al., 2018 ). These findings have been substantiated in experimental studies, where the gender identity of the instructor in online courses was manipulated, with the instructors receiving lower ratings from both male and female students when they were believed to be women ( Khazan et al., 2019 ; MacNell et al., 2015 ). Men are perceived by all genders to be more knowledgeable and to have stronger leadership skills than their women counterparts ( Boring, 2017 ), even when there are no actual differences in what students have learned. This bias towards masculine traits during student evaluations of teaching (SETs) can have an important impact on the career of women scientists, as it is commonly used as a measurement of teaching effectiveness for promotion and tenure decisions. Apart from bias in the perception of women as teachers, women also tend to have higher teaching loads compared to men, and less time for research ( Misra et al., 2011 ), which can negatively impact their research productivity.

We propose the use of existing tools ( Reinholz and Shah, 2018 , see Table 1 ) that can help faculty to build their syllabi and bibliographies in a more gender-balanced way ( Sumner, 2018 ). In particular, faculty could provide historical examples of successful women scientists to reinforce female role models, ensure that the resources they give to their students are gender balanced ( Table 1 ), and use more inclusive language (i.e. ‘folks’ instead of ‘guys’, ( Bigler and Leaper, 2015 ).

The necessity to improve fairness and objectivity in teaching evaluations is critical to balance the odds for promotion across genders. A study conducted at the University of California, Berkeley, suggested abandoning the SETs as the principal measure of teaching effectiveness, and implementing instead other types of assessment, such as observing the teaching and examining teaching materials and portfolios ( Stark and Freishtat, 2014 ). Moreover, improvement in the phrasing of the SETs is also required. Simple changes to the language used (e.g., explicitly asking students to be aware of their biases) had a positive impact on the assessment of women professors ( Peterson et al., 2019 ). Prefacing SETs with counter-stereotype content could further decrease bias that is evident during the evaluation itself ( Blair et al., 2001 ).

8. Academic hiring, tenure decisions and promotions favor men

Evaluation criteria for hiring and promotion commonly used in academia are also susceptible to gender inequality. These biases are common across all hiring stages, encompassing lab manager positions ( Moss-Racusin et al., 2012 ), postdoctoral fellowships ( Sheltzer and Smith, 2014 ), as well as tenure track positions ( Steinpreis et al., 1999 ).

Strikingly, despite experimental and observable data in STEM fields reporting favorability toward women in hiring decisions compared to equally qualified men, women remain heavily underrepresented in tenure track positions (National Research Council et al., 2010; Williams and Ceci, 2015 ). This discrepancy has multiple potential sources related to different dimensions of gender bias. Gender biases in recruitment can occur even before applicants are evaluated ( Nielsen, 2016 ). In neuroscience and STEM in general, most departmental or unit leaders are men ( Gupta et al., 2005 ; McCullough, 2019 ). Consequently, men are more likely than women to define the unit’s strategic research foci and/or teaching needs, draft the job profile, and outline the announcement, thereby determining the focus of the search. Defining a profile in a broad or narrow manner directly impacts the number and quality of eligible candidates. Narrow profiles can be used to legitimize the selection of a specific candidate ( van den Brink, 2010 ) and often penalize women, as men’s social networks benefit from a higher proportion of scientific leaders ( Greguletz et al., 2019 ; James et al., 2019 ). The practice of some academic institutions limiting open recruitments presents an added barrier for women. A study in Denmark showed that, at the University of Aarhus, about 20% of associate and full professor positions were filled via a closed recruitment procedure ( Nielsen, 2015 ); such procedures are likely to propagate bias, as closed recruitment frequently results in a single applicant ( Nielsen, 2015 ).

The evaluation and selection phase of the hiring process contributes to the persistence of gender imbalance ( Rivera, 2017 ). Since men continue to be overrepresented among tenured/tenure-track faculty, evaluation committees and interview panels tend to have skewed gender composition ( Sheltzer and Smith, 2014 ). Gender bias during hiring is amplified by the role of “elite” male faculty, who employ fewer women in their labs and have a disproportionate effect on training the next generation of faculty; these processes in turn, affect hiring at high-ranking research universities ( Sheltzer and Smith, 2014 ). Moreover, studies performed in Italian and Spanish academic institutions across several scientific fields show that when promotion committees are composed exclusively of men, women are less likely to get promoted ( De Paola and Scoppa, 2015 ). Each additional woman on a 7-member promotion committee increased the number of women promoted to full professor by 14% ( Zinovyeva and Bagues, 2011 ). Another important factor in reducing gender bias in committee decisions is committee member awareness of implicit bias. Indeed, as shown in a recent study in France conducted across scientific disciplines, committee members who believe that women face external barriers in their performance and evaluation are less biased towards selecting men ( Régner et al., 2019 ).

The biases that affect search criteria also influence the evaluation of the applicant’s curriculum vitae. When faculty believe the applicant to be a man, they tend to evaluate the CV more favorably and are more likely to hire the applicant ( Moss-Racusin et al., 2012 ; Steinpreis et al., 1999 ) than when faculty believe the applicant to be a woman. Consequently, only women with extraordinary applications tend to be considered, narrowing the pool of potential women candidates to be interviewed.

Another source of bias during hiring comes from recommendation letters. Their content and quality significantly differ based on the gender of the applicant ( Dutt et al., 2016 ; Madera et al., 2009 ; Schmader et al., 2007 ). For example, letters in support of women are typically shorter, raise more doubts, include fewer ‘standout’ adjectives (e.g., superb, brilliant) and more ‘endeavor’ adjectives (e.g., hardworking and diligent), regardless of the gender of the recommender. Altogether, subtle gender biases throughout the academic hiring process, from job posting to evaluation, increase the risk of creating self-reinforcing cycles of gender inequality ( van den Brink et al., 2010 ; Nielsen, 2015 ).

We recommend that individuals writing job announcements be made aware concerning gender bias issues both explicit and implicit. Individuals evaluating applications should also be trained on topics relevant to gender equity, gender bias, and bias mitigation ( Bergman et al., 2013 ).

Bias awareness workshops could help scientists to improve job advertisements, and assess applications more objectively ( Carnes et al., 2015 ; Schrouff et al., 2019 ). This approach is already in place in some academic institutions (e.g., in the University of California system) and could be more widely adopted and made mandatory for all academic members. The University of Wisconsin-Madison has successfully increased diversity by implementing workshops for faculty search committees that raise awareness about unconscious bias and provide evidence-based solutions to counter the problem ( Fine et al., 2014 ). These types of workshops can be broadly implemented across institutions and fields. Finally, numerous studies show that reminding evaluators of their internal biases at the evaluation stage of the hiring process reduces the impact of bias ( Carnes et al., 2015 ; Devine et al., 2017 ; Smith et al., 2015 ; Valantine et al., 2014 ).

Efforts should also be made to increase diversity in search committees. Increasing representation of women is necessary for reducing bias ( Schrouff et al., 2019 ; Smith et al., 2004 ), despite not being sufficient on its own (see Discussion ). At the same time, institutions should ensure that women in underrepresented departments are not overloaded with administrative obligations, time-consuming committees, or any other assignment tasks that do not enhance promotion prospects ( Babcock et al., 2017 ). To increase diversity in search committees while not overworking women, we propose that members of search committees be compensated by reducing their teaching or other administrative duties. Importantly, we highlight the strong need for male allies as part of search committees (see Discussion ).

Some academic institutions have already introduced mediators from equity committees in the hiring/promotion procedure. For example in Switzerland such mediators are required to actively provide input in faculty hiring and monitor gender balance (Gender Monitoring_Egalité_EPFL). Although non-academic advisors cannot judge the quality of scientific work, their input on the fairness of the hiring process can be valuable.

Each institution must commit to policies and action plans that set quantifiable goals for women in different position categories. Ideally, the number of women reaching the interview stages should match the gender ratio of a given academic field. Concrete recruitment strategies to achieve these goals could be developed, for example, by adopting mandatory submission of regular reports on gender ratio with quantifiable measures ( Bergman et al., 2013 ). As an example, if no women candidates apply, the University of California at Berkeley requires the position to be re-announced more broadly. Institutions can be required to be more explicit and transparent about how merit is evaluated. All of the above measures can be enforced with central incentives, such as funding allocations, to motivate departments to implement the necessary steps and hire more women ( Bergman et al., 2013 ). Another solution to help reach a larger and more diverse pool of potential candidates would be the development of a curated and regularly updated list of underrepresented minority mentees that could become targets for job searches and awards (as it is already the case for conference speakers, Table 1 ).

Importantly, we believe that hiring committees need to recognize forms of scientific contribution to the STEM community not directly tied to scientific productivity. Such contributions include outreach, knowledge dissemination, and faculty service; these are contributions which women make on average significantly more than men, taking time from more traditional forms of research ( Guarino and Borden, 2017 ). The practice of science is evolving, and additional qualification criteria for hiring decisions should be adopted to acknowledge the broader range of roles and responsibilities of contemporary scientists ( Moher et al., 2018 ). In addition to building towards gender equity, recognizing and incentivizing these contributions to our academic communities will benefit all scientists regardless of gender.

Suggestions at the societal level:

When legally possible (as in Sweden, Germany, and Switzerland), any organization, including academic institutions can set policies on gender equity, set goals for gender ratios in different position categories, and develop recruitment strategies to achieve these goals ( Nielsen et al., 2017 ; Schrouff et al., 2019 ; Exploring quotas in academia; Des quotas pour promouvoir l’égalité des chances dans la recherche).

9. Gender bias in negotiation outcomes

Negotiations are important for building a successful career, as they can lead to better starting salaries and start-up packages, salary increases, better work conditions, and increased allocation of personnel, lab space, and other resources. On average, men tend to initiate negotiations more often than women ( Babcock et al., 2006 ; Small et al., 2007 ). Additionally, when they do, women still get less out of negotiations; are less likely than men to be successful in receiving the raise they asked for, and may incur a social cost for standing up for themselves ( Bowles et al., 2007 ; Mazei et al., 2015 ).

Importantly, negotiations might be affected by perceived gender stereotypes as gender roles influence both parties of the negotiations regardless of their gender ( Kray et al., 2001 , 2014 ). In accordance with Role Congruity Theory ( Eagly and Karau, 2002 ), women are often reluctant to negotiate because initiating negotiations is perceived as stereotypically male behavior. Moreover, expressions of emotions commonly associated with leadership characteristics, such as anger and pride ( Brescoll, 2016 ), are more widely tolerated and even appreciated when they emanate from men compared to women ( Brescoll and Uhlmann, 2008 ). The expression of gender roles is a complex phenomenon though. On the one hand, women may lose social capital (i.e the work connections that have productive benefits) when voicing their opinions, especially when they go against the group’s opinion. On the other hand, it has been reported that women who described themselves as displaying so-called "masculine" personality traits (i.e., a competitive mindset and willingness to take risks) had a 4.3% greater chance of getting positions and were more likely to take up positions that offered 10% higher wages than those displaying so-called "feminine" personality traits (i.e., gentle, friendly, and affectionate)( Drydakis et al., 2018 ). This deep-seated implicit bias, held by all genders, has non-trivial consequences over women’s career in academia.

Transparency is a key element for equity during negotiations. We propose that institutions provide access to everyone's salary and also to a range of possible salaries per academic level. Gender differences in economic outcomes tend to be smaller when negotiators first receive information about the bargaining range in a negotiation ( Mazei et al., 2015 ). Such an approach could be complemented by providing information to faculty about ranges of research budgets, or salaries and construct a rational -rather than ad-hoc- process for determining how resources are allocated.

Removing stereotypes in both parties of the negotiations can improve women’s performance ( Kray and Kennedy, 2017 ). It has been shown that having supportive academic supervisors plays an important role in improving negotiational effectiveness for women ( Fiset and Saffie-Robertson, 2020 ). Also, for mentees eager to develop their negotiation skills, institutions could offer courses on this topic. For instance, several online services, highlighted on Table 1 , offer training materials on negotiation strategies, as well as materials targeted for companies wanting to improve their gender representation. These workshops provide techniques for negotiation and conflict resolution.

10. Gender inequalities are present in conferences

Conferences and meetings are crucial avenues for scientists to communicate new discoveries, form research collaborations, communicate with funding agencies, and attract new members to their labs and programs ( Calisi and a Working Group of Mothers in Science, 2018 ). For instance, invitations to seminars at different institutions increase scientists’ visibility and expand their academic networks. However, equally qualified women scientists are often given fewer opportunities to speak at conferences and seminars than men. For instance, nearly half of the conferences in neuroscience have fewer women speakers than the base rate of women working in the field of the conference (Conference Watch at a glance ∣ biaswatchneuro, How scientists are fighting against gender bias in conference speaker lineups). Given that conference presentations are an important indicator of the impact and significance of one’s research, this form of gender bias has negative implications for women during hiring and promotion. Inviting women speakers and providing them with resources that allow them to attend the conference contributes to their professional development and increases their visibility. This action also contributes to the perception of women researchers as leaders for young scientists in the audience. This visibility is especially important for boosting the confidence of young women researchers. Moreover, women in the conference audience generally remain less visible, as they ask fewer questions than men. This is due to both internal (e.g., being unsure whether their question is appropriate) and structural factors (e.g., when the first question is asked by a man, women are less likely to follow up) ( Carter et al., 2018 ).

Another important point that undermines the experience of women at conferences is unprofessional and inappropriate behavior ( Parsons, 2015 ) (see the below section 11 on sexual harassment). This may cause some scientists to avoid conferences due to feeling unsafe ( Richey et al., 2015 ). Specifically, sexual and gender harassment and micro-aggressions target primarily women, and are a common form of reported harassment at conferences ( Marts, 2017 ). Finally, disrespectful and unprofessional questions and feedback during poster sessions and talks may discourage women from presenting their work ( Biggs et al., 2018 ).

We recommend that invited participants take proactive actions to promote gender equity. They could ask the organizers what measures are taken to ensure that the symposium and/or conference will not be a man-dominated event, and could also decline to speak at conferences with an imbalanced speaker lineup. For instance, attendees can monitor progress in a conference’s history of gender balance in speaker selection and see the base rates of women in relevant subfields, as is already possible in neuroscience ( Table 1 ). We believe that scientists of all genders and levels of seniority should take personal responsibility to ensure professional conduct by speaking out against harassment and other biased behaviors.

Conferences can strive to ensure that symposia include gender-balanced speakers and chairs, at least in a ratio that matches the demographics of the field. Conference, seminar, and symposium organizers should have a list of women speakers that they can invite. They can search outside their personal and professional networks by consulting resources such as the directory compiled by Jennifer Glass and Minda Monteagudo which lists searchable databases of highly qualified women by subfield ( Table 1 ). As a notable example, proposals for symposia at the Federation of European Neuroscience Societies (FENS) Forum are required to include men and women speakers or provide a justification for single-gender symposia.

We also propose that organizers consider existing tools to mitigate their own bias. Gender balance at neuroscience conferences has been publicly monitored through the website BiasWatchNeuro ( Table 1 ). Such measures could be implemented in many academic fields. In the context of conferences, unlike that for citations, diversity must come from the top: the organizations hosting a conference should strive for a committee that is well trained regarding bias. The Organization for Human Brain Mapping (OHBM) has introduced an ‘Affirmative Attention’ approach, by which new Council members are elected through a ballot, so that the candidates for at least some open positions may only include women, to ensure that the gender distribution in the council remains equitable, no matter which candidates get elected ( Tzovara et al., 2021 ). Conference organizers can also offer programs that raise awareness of the issue of gender bias. For example, the annual meetings of several major conferences, such as the Society for Neuroscience, OHBM, or FENS, include educational courses, workshops and informational sessions on gender bias (Seeds of Change within OHBM: Three Years of Work Addressing Inclusivity and Diversity). Another example is the ‘power hour’ institutionalized by The Gordon Research Conferences which consists of a forum for conversations about diversity, inclusivity and related topics (The GRC Power Hour™).

However, in workshops about gender bias, often only highly successful women are represented on panels discussing bias and women’s careers in academia. In these instances, we believe that it is important to avoid promoting survivorship bias, which emphasizes positive outcomes without addressing the barriers and challenges that must be overcome to achieve that success more broadly among women scientists. Moreover, men are not usually invited as speakers in these events and are also usually absent from the audience, which renders them less aware of the issues around gender bias, and therefore less effective allies. We suggest that the way that the speakers and topics of panels are chosen must be improved to be more inclusive and represent the full spectrum of diversity in the community.

An inclusive code of conduct has been proposed as mandatory for each conference, stating what is and what is not appropriate behavior for conference attendees ( Favaro et al., 2016 ). Conference organizers should have clear plans of action in place in case harassment occurs, including anonymous reporting and removing confirmed harassers from the conference ( Marts, 2017 ; Parsons, 2015 ). The suggested code of conduct should also include respectful ways to provide constructive scientific feedback ( Favaro et al., 2016 ), a practice that should be implemented across all contexts within academia. Lastly, all attendees should feel concerned about and responsible for maintaining a respectable environment during conferences. Since it can sometimes be hard to intervene as things unfold in real-time, we suggest that conference organizers provide a specific contact where members can report unethical or inappropriate incidents.

11. Sexual harassment is a major obstacle encompassing all career stages

A recent exhaustive report on sexual assault led by the National Academies of Science, Engineering, and Medicine, and funded by the NIH, reported that rates of sexual harassment are as high as 58% for academic faculty and staff and between 20 to 50% for students. The majority of the sexual harassment experienced by women in academia consists of sexist hostility. These unacceptable rates are higher than any other work environment except for the military ( Johnson and Smith, 2018 ). The consequences of harassment are far-reaching and require widespread efforts to reduce these high rates if we are to see gender parity in a scientific workplace.

Sexual harassment falls into four main categories: micro-aggression (i.e., comments or actions that express prejudiced attitudes), sexual coercion, unwanted sexual attention, and gender harassment (see National Academies of Sciences, Engineering, and Medicine, 2018 for detailed review). Harassment consists of actions that create a hostile and inequitable environment for members of a specific group. Harassment is not limited to the extreme form of physical assault; it also includes endorsing beliefs that someone’s intelligence is inferior to another’s, or making demeaning jokes that target one gender group.

Unfortunately, all types of sexual harassment are common and lead to negative outcomes for the people who experience them. In addition to the 58% of academic faculty or staff who experienced sexual harassment, 38% of women trainees and 23% of men trainees experienced sexual harassment from faculty ( Johnson and Smith, 2018 ). More egregious numbers are found in specific fields; a recent study reports that 75% of undergraduate women majoring in physics experienced sexual harassment ( Aycock et al., 2019 ). While peer-to-peer harassment is also prevalent, trainees experience worse professional outcomes when faculty at their university conducted the harassment. These numbers may underestimate the problem, as trainees might not feel comfortable speaking up when their career development, and sometimes even legal status in a country, depends on the person harassing them. In another study of 474 scientists, 30% of women reported feeling unsafe at work, compared to 2% of men ( Clancy et al., 2017 ). The rates were even higher for women of color, where almost 50% of women scientists of color reported feeling unsafe at work ( Clancy et al., 2017 ). These experiences are chronically stressful and have been linked to higher levels of depression, anxiety, and generally impaired psychological well-being ( Lim and Cortina, 2005 ; Parker and Griffin, 2002 ). People who have experienced sexual harassment report higher rates of absenteeism, tardiness, and use of sick leave (measured on scales where respondents indicated desirability, frequency, likelihood, and ease of engaging in these behaviors) and unfavorable job behaviors (e.g., making excuses to get out of work, neglecting tasks not evaluated on performance appraisal) ( Schneider et al., 1997 ). Finally, and not surprisingly, individuals who experience sexual harassment are more likely to leave their jobs. All of these statistics demonstrate that sexual harassment is both alarmingly common and reduces the scientific productivity and well-being of the people who have been harmed. Yet, when this behavior is reported, the whistle-blowers may be either retaliated against or there may be no repercussions for the perpetrators. Moreover, even the policies that aim to ‘protect’ victims of harassment have substantial negative consequences, which are more likely to occur to women than men. These include reluctance to have one-to-one meetings with women or to include them in social events, or reluctance to hire women for positions that require close contact with them ( Atwater et al., 2019 ).

Collegial behavior, that does not propagate harassment and micro-aggressions should be the bare minimum expectation in any lab or academic institution. Individuals of all levels should consider their personal responsibility to promote a respectful and professional environment, avoid and denounce unwelcome behavior when witnessed. Besides everyone’s own responsibility, it is essential that organizational leaders display an unequivocal anti-harassment message ( Buchanan et al., 2014 ).

Sexual harassment cannot be tolerated and must be severely reprehended by institutions. Although some initiatives for combating harassment exist, there is to date no evidence that current policies have succeeded in reducing harassment (ACD Working Group on Changing the Culture to End Sexual Harassment). To counter this ineffectiveness, the NIH has recently recommended that sexual harassment needs to be equated to scientific misconduct, including similar mechanisms for reporting, investigation, and adjudication.

Researchers found guilty of sexual harassment could be barred from applying for new grants over a period of years deemed appropriate by the various regulatory entities similar to the penalty for scientific misconduct. Examples of such entities in the USA would be the Department of Health and Human Services (HHS), their Office of Research Integrity (ORI), and the NIH. Importantly, the committees involved in investigating and adjudicating harassment should be independent from the institution leaders ( Greider et al. 2019 ).

One solution often proposed to combat sexual harassment is anti-harassment training. This consists of requiring students and staff to participate in workshops detailing sexual harassment policies and what constitutes unwelcome behavior. This approach has been widely suggested, and is currently implemented in several institutions despite its debatable effectiveness in reducing harassment. Indeed, it has been shown that some approaches could have the opposite effect, with men being less likely to judge a situation as harassment after receiving training, and leading to gender stereotype reinforcement ( Roehling and Huang, 2018 ). Moreover, empirical studies have shown that training employees to recognize what constitutes harassment can be followed by decreases in women managers ( Dobbin and Kalev, 2019 ). By contrast, training managers to recognize signs of harassment and intervene, results in increases in women managers ( Dobbin and Kalev, 2019 ). This seeming discrepancy may be due to gender differences in perception of harassment, so that women are more likely to believe victims of harassment. Departments need to carefully design their sexual harassment training as studies have reported that the designs of such training are essential and need to be adapted to the targeted populations ( Dobbin and Kalev, 2019 ). Interventions that place trainees as allies, such as bystander intervention training (Bringing in the Bystander®), showed positive effects on sexual harassment prevention in academia and military sectors ( Buchanan et al., 2014 ; Cares et al., 2015 ; Katz and Moore, 2013 ; Potter and Moynihan, 2011 ). For instance, Potter et al. (2019) are developing videogames to educate college students bystander intervention skills in situations of sexual harassment and stalking.

One example of a novel, yet untested approach is the ‘Respect is Part of Research’ initiative by graduate students in the University of California Berkeley Physics Department. During these trainings, participants discuss case studies in small groups together with a facilitator, addressing what is wrong about the behavior of the actors in the example, separating intent from impact, and methods to resolve the situation. Providing trainees with the tools to handle difficult situations and creating a supportive community has the potential to significantly shift the culture towards more respectful behavior in academia. However, its effectiveness for combating harassment in the long-term still remains to be tested.

Another factor that can assist in reducing harassment is adopting clear anti-harassment policies in codes of conduct (Why and How to Develop an Event Code of Conduct), both at conferences, and in individual labs. Enforcing a code of conduct is a challenging task, and future efforts should focus on drafting clear policies for different scenarios.

To lower the rates of sexual harassment, all members of the scientific community, and the community at large, need to make widespread changes. Learning to recognize sexual harassment should be an ongoing goal for any nation, starting with education in schools. We recommend that all organizations develop programs charged with reducing the prevalence of sexual violence, sexual harassment, and stalking through prevention, advocacy, training, and healing (for example see the Path to Care center from University of California Berkeley). This approach is distinct from and complementary to the purpose of official university legal procedures (e.g., Title IX in the USA): while such officers legally arbitrate gender discrimination disputes, the University Program we envision would be dedicated to serving the survivors of sexual harassment, preventing new cases, and training the university-wide community.

12. Encompassing all sectors: family planning in academia

Gender inequity exists in the division of household labor. Women typically shoulder most of the burden in childcare and in maintenance of the household, even among dual career partners ( Chopra and Zambelli, 2017 ). Women have increasingly joined the paid labor force, increasing their total work time, but men have not increased the amount of time they spend in unpaid household work. The COVID-19 pandemic is the most recent evidence of the impact of gender inequality in the labor market ( Alon et al., 2020 ). During the lockdown, women scientists submitted fewer manuscripts and started fewer research projects than men ( Viglione, 2020 ), consistent with an additional and disproportionate burden of childcare. While the majority of studies consider households composed of one man and one woman, further work is needed to evaluate the relations between gender and labor in single-parent homes or same-gender parent homes.

Although academia has its perks for the single parent, same-gender parent, and different-gender parent families, such as flexible hours and additional time to tenure, other working conditions can become barriers for family planning. Career stages where funding and mobility are critical, such as transitions between graduate school, postgraduate training, and tenure positions, often correspond to a time when researchers may wish to start a family (see Figure 1 ). However, pregnancy, childbirth, nursing, parental leave, and early childcare take a considerable amount of time, physical and mental resources, and money that constitute a competitive disadvantage in a scientific career. Indeed, parental leave negatively impacts metrics of productivity of early career scientists who are parents ( Chapman et al., 2019 ), yet with a stronger effect for women ( Morgan et al., 2021 ); which in turn impacts the possibility to obtain grant funding (i.e., several calls are limited to a certain amount of years post-degree according to funding agency policies).

Women with children are reluctant to attend conferences due to the lack of childcare support ( Calisi and a Working Group of Mothers in Science, 2018 ). Conferences in distant locations add another layer of complexity, as transoceanic flights often mean a longer stay away from home. Adequate facilities such as lactation rooms are rarely provided, nor are support for a traveling caretaker to assist in the care of their infant as the scientist attends the meeting. This limited mobility reduces parents’ opportunities for international collaborations and funding, which are common criteria used for promotion and evaluations.

Importantly, women face even stronger discrimination when they are part of non-traditional family formations: single mothers experience a stronger work-family strain than partnered ones ( Baxter and Alexander, 2008 ). Studies of single mother doctoral students have shown that they fear being judged in their departments, and that they often feel excluded by university life and academic schedules ( AmiriRad, 2016 ). Although LGBTQ+ parents face similar challenges as cisgender and heterosexual parents ( King et al., 2013 ), LGBTQ+ individuals might have fewer health or retirement benefits, and face unequal treatment in academia ( Cech and Waidzunas, 2021 ; Thompson and Parry, 2017 ). Future studies should address the particular challenges and biases faced by single parent and LGBTQ+ families and their potential impact on academic achievements.

Apart from the academic aspect, most societies are not built to assist families where both parents pursue a demanding career path. For instance, public schools in some countries like Germany often stop in the early afternoon, and it can be hard to find public preschool or after school childcare. Moreover, working mothers often feel stigmatized as they risk being looked down upon by citizens of more “traditional” societies for their choices to work instead of staying at home with their children.

Parents should not have to choose between having a family and an academic career. Evaluation of academic progress should take into consideration delays caused by parenthood and childcare responsibilities. Individuals should also assess their own possible tendencies to judge or exclude academics with young children, and become prepared to support initiatives that would encourage their participation in gatherings, conferences, and other professional activities.

Institutions need to adopt official extensions of graduate, postdoctoral, and tenure timelines due to childbirth and parenthood. To address the financial difficulties for academic families, we suggest a number of measures. First, job security can be improved by creating longer-term contracts where possible, and by providing bridge funds at the department or university level to support trainees during gaps in funding ( Stewart and Valian, 2018 ). Both universities and funding institutions should put measures in place to prevent a gap in funding during parental leave ( Powell 2019 ). Special provisions for parenthood can be made in calls for proposals and funding mechanisms. A few funding organizations include childbirth in their policies as a valid reason to extend the eligibility window (from one year for NIH K awards to 18 months for ERC grants, or a 2 year extension to post-PhD limits per child for the Emmy Noether Program of the German Research Foundation), or subtract time for parental leave (“Research Project for Young Talent” proposed by the Research Council of Norway, 2–7 years post-PhD). Finally, efforts should be made to reduce the difficulty in returning to work after maternity leave, such as providing lactation rooms.

Solutions can be found to support couples in which both partners are in academia ( Schiebinger et al., 2008 ). By enabling couple hiring for tenure track positions, institutions can help women pursue their academic career. Critically, universities should ensure access to affordable, on-site childcare, as this both improves outcomes for children enrolled in such programs and increases women’s participation in the workforce ( Morrissey, 2017 ; Gault 2016).

Specific funding should be allocated for parents to travel for conferences and sabbaticals. Conferences, universities, and funding agencies can reserve a part of their budget to create travel funds for parents. Compared to a decade ago, more conferences are offering nursing rooms ( Cardel et al., 2020 ; Hope et al., 2019 ; Langin, 2018 ) and other types of on-site childcare, which should be accessible to all parents ( Cardel et al., 2020 ; Langin, 2018 ). However, unfamiliar caregivers are not always a viable option, and parents will likely feel most comfortable knowing their child is cared for by a primary caregiver. To address these issues, some conferences, such as FENS or OHBM, are offering childcare grants, which can either cover travel expense for a trusted caregiver (spouse, partner, or nanny) to accompany the parent and child, or pay for expenses involved in leaving the child at home ( Calisi and a Working Group of Mothers in Science, 2018 ; Langin, 2018 ; Tzovara et al., 2021 ).

These issues require a broad reshaping of society, which still relies on parental roles or family patterns that are increasingly obsolete. Law in all countries needs to enforce official extension of timelines to accommodate pregnancy, childbirth, and parenthood, as increases in parental leave result in fewer women leaving the workforce ( Jones and Wilcher, 2019 ). For instance, the total paid period of parental leave in Norway is between 46 and 59 weeks, with maternal and paternal quotas of 15 weeks each and a joint period of 16 weeks. The downside of providing parental leave to both parents is that previous research has shown that giving the same extensions to both parents puts mothers at a disadvantage as fathers are more likely to increase their productivity during this period ( Antecol et al., 2016 ). It is therefore important for parents to have an equal split of child caring duties, and profit from allocated time to bond with their child.

13. Not all gender biases are the same: Intersectionality

Discussions surrounding plans to combat gender bias in academia are incomplete without attention to the unique struggles of women who hold additional identities are subject to discrimination. Barriers faced by all women in academia are compounded for those who are members of additional underrepresented groups (e.g., based on, but not limited to race, ethnicity, first-generation status, religion, socioeconomic status, gender expression, gender identity, sexual orientation, and disability) that interact with and increase gender bias ( Armstrong and Jovanovic, 2015 ). For instance, the gender wage gap has been shown to be wider for transgender women ( Schilt and Wiswall, 2008 ) and also for black women (Guillory, 2001). Women of color faculty are the least likely to receive tenure of all demographic groups despite comparable productivity ( Armstrong and Jovanovic, 2017 ). As such, successful interventions must consider these supra-additive effects, and take an intersectional approach.

Across all career stages and aspects of academia, institutions could develop interventions and programs that take into account the specific needs of overlapping identities. For instance, Flores ( Flores, 2011 ) proposed that financial awards, or targeted mentoring programs could help underrepresented women to overcome practical and psychological burdens associated with intersecting identities. Policies to increase the Latino community in STEM propose mentoring and educational programs in different languages, for women whose native language is not English ( Flores, 2011 ). A first step in developing such programming can be interviews and focus groups with underrepresented minority women in order to receive feedback on structural inequalities that can be addressed at the institutional level. Intersectional approaches can include targeted networking events, mentorship pipelines, and funding initiatives, as well as rigorous data collection to assess efficacy of these approaches. As with any intervention, special care needs to be taken to not overburden the individuals experiencing discrimination with additional tasks and administrative overload.

14. Discussion

In this article, we review empirical evidence demonstrating pervasive gender bias throughout all stages and venues of academic life. Studies have shown that women are less likely to be hired or to receive tenure than men, despite equal performance. They receive less grant funding and fewer prestigious awards. The rates of accepted publications, presentations, and patents are lower for women, and women are less likely to be first or last author on publications or to submit to high impact journals. Studies are documenting a prevailing notion that work by men has higher merit than that of women, a perception that is reflected in the discrepant number of citations of men versus women authors in research papers or in assigned classroom readings. Positions on review panels with the power to hire, promote, approve funding, or decide policy are still largely offered to men, whose own biases (unconscious or otherwise) may impede the advancement of women academics. Women’s salaries are lower than men’s, and women take on the greater burden of childcare, restricting their opportunities to conduct research or attend conferences. Finally, women continue to experience sexual harassment and hostility at an alarming rate, not only in their work environment, but also at conferences and other academic venues.

Apart from the ethical issues this evidence raises, a large proportion of the highly trained and talented individuals who are essential for advancing research and educational practice are not progressing in their academic careers, largely due to the rectifiable issue of gender bias. Here, we gather, explore, and suggest actions at the individual, institutional and societal levels, aimed to mitigate the effects of gender bias. Implementing some of the proposed recommendations will not be trivial as new regulations and controls might themselves require monitoring for bias. We cannot predict the outcomes of the proposed suggestions. However, openly and explicitly acknowledging gender bias (that all genders are susceptible to) is an essential starting point to restore the unbalanced academic environment. In considering such complexities, institutions should engage the advice and guidance of social science experts and the affected groups to ensure optimal solutions.

Diversity is essential to delivering excellence in science as it increases cognitive diversity, which in turn leads to novel solutions ( Page, 2008 )and innovations ( Hofstra et al., 2020 ), as well as increased problem-solving ( Hong and Page, 2004 ) and scientific discovery ( Nielsen et al., 2018 ). Besides the invaluable contribution to science, it will also help reduce stereotypes ( Miller et al., 2015 ). To ensure successful changes, mindsets must change, and our proposed solutions provide a step in that direction. However, many challenges first need to be understood and overcome. Thus, a few important aspects of gender bias must be addressed.

The fight for gender equity needs diverse role models and strong allies

First, we need to amplify the voices of under-represented scientists and mentors as role models in order to encourage diversity. One of the main reasons for leaving science is a lack of mentoring, which affects more women than men trainees, as women are less likely to be mentored ( Preston, 2004 ). In line with this reported gender bias in mentoring in academia, experimental evidence showed that women and men science faculty were less likely to offer mentoring to a trainee when their application materials were assigned a female rather than a male name ( Moss-Racusin et al., 2012 ). In order to overcome this bias against women trainees, mentors have to make an intentional effort to offer mentoring to women trainees to ensure that mentoring is provided equally to women and men trainees. This study also found that female applicants were rated as less competent than the male applicants with the identical application. Awareness of implicit bias is an important first step to overcome these barriers and enable mentors to improve equal support of women mentees. For instance, they could actively encourage them to submit to higher impact factor journals, apply for funding opportunities and large grants, nominate them to awards, invite them to speak in conferences and seminars, and meet potential collaborators. All scientists should consider gender equity when building a team of principal investigators for collaborative work, particularly on larger or more prestigious projects. Having encouraging mentors and role models with whom students and scientists can identify will positively shift their perception of themselves ( Morgenroth et al., 2015 ) and mitigate imposter syndrome ( Abdelaal, 2020 ). This type of support can make the academic career path more inclusive and accessible, irrespective of race, ethnicity, sex, sexual orientation, or gender.

Second, everyone needs to be on board, irrespective of gender or career stage. This is particularly critical as men still hold most positions of power in STEM, and can use their positions to change the system from within. This can be challenging as there are several persistent misbeliefs about preventing progress ( Johnson and Smith, 2018 ). One might argue that giving more opportunities to women necessarily comes with a loss of privileges for men. However, the situation in some STEM domains is not a zero-sum game. Many countries suffer from an overall STEM worker shortage; thus adding women to the workforce would improve overall industry performance. In addition, gender equity comes with many benefits: organizations with more female leaders offer employees more generous policies ( Ingram and Simons, 1995 ) producing better business results ( Berdahl, 2007 ). Some men might feel that gender equity “is not their fight”. The answer to this concern is two-fold. First, gender equity is a moral imperative, and the voices and actions of all are needed. Second, gender equity is a man’s fight. Gendered roles impact not only women, but men as well: many still believe that “child caregiving/domestic work is not a male job”, and that “a man needs to be the family breadwinner”, a belief that can have a strong impact on mental health ( King et al., 2020 ). This position reflects a “fixed mindset” about gender roles, which leads men to rationalize the status quo, i.e. engage in system justification about gender inequality ( Kray et al., 2017 ). A more fundamental antidote in combating gender bias is to promote growth mindsets (e.g. “things can change, there is no reason why men and women can’t occupy the same social roles”; Dweck 2016 ).

Notably, the concern and interest around the topic of women's underrepresentation in STEM has not been matched by a similar concern about men's underrepresentation in healthcare, early education and domestic roles ( Block et al., 2019 ; Croft et al., 2015 ; Meeussen et al., 2020 ). However, gender experts are now pointing at men and men’s representation as a key component to advance women’s place in society ( Block et al., 2019 ; Croft et al., 2021 ). Gender equity will benefit men by freeing them from societal biases. In turn, a change in the aspirations and careers of men will likely benefit overall gender equality: men who take on non-traditional roles can enable women and girls to envision themselves in less traditional, complementary roles ( Block et al., 2018 ; Croft et al., 2014 ). When more men turn to roles in health care, education, and domestic work, there will be more STEM roles that can be occupied by women. To quote one of our reviewers: “As long as there is stagnation in men's roles, there will be an upper limit on the amount of change that can be achieved for women's roles as well”.

Importantly, as soon as the fight for gender equity becomes a universal cause, the overload of academic work weighing on women should be alleviated. The approach of several institutes or funding agencies for improving equity is to task women with taking part in administrative obligations during hiring processes, panels in conferences etc. However, being fewer in number, the same women find themselves having to manage substantial extra work. Besides these administrative burdens, they are also often asked to participate in initiatives aimed for promoting diversity. This work additionally affects women disproportionately, and even more so women of color ( Nair, 2014 ). It may seem natural that individuals facing discrimination would have the strongest interest and possibly knowledge on how to resolve it. However, leaving the work that promotes diversity to those directly affected by the lack of diversity/inclusivity can contribute to further injustices. This work thus needs to be shared with advocates from the non-minority category.

When implementing some of the proposed solutions, it is important to consider complexities that might emerge from “positive discrimination”, where the “best” candidate might be overlooked in favor of a candidate who meets another requirement (e.g., ethnicity, first-generation status, religion, socioeconomic status, gender expression, gender identity, sexual orientation, and disability; STEM Women, 2019). Not dismantling structural conditions of inequality, means that existing disadvantages triumph. Institutions should carefully consider these complexities and include affected minorities in policy development to ensure optimal solutions.

Challenges and major open questions in addressing gender bias

Improving gender equity in science represents challenges at several levels. First of all, despite an abundance of research, there is a lack of systematic and validated metrics to assess gender bias and evaluate the efficacy of various initiatives in improving gender equity. Without standardized data collection and metrics to objectively measure gender bias, it is often impossible to draw solid conclusions on the degree of its presence and/or origin. However, for appropriate measures to be deployed the source of bias needs to be properly established so that proposed actions can differentially target the real cause. One reason for this is that despite its far-fetched consequences, evaluating the existence of bias can be very subtle and challenging. Measuring presence and then reductions in implicit bias in a controlled setting does not necessarily translate to changes in real life situations (Forscher et al., 2019). It is crucial that advocacy goals do not bias the presentation of scientific evidence for and against different interventions and policy changes ( Eagly, 2016 , 2018 ). Moreover, there is a lack of systematic gathering and reporting of gender data from various organizations such as universities, conferences, funding agencies, or award and hiring committees. Moving forward, we encourage institutions to gather and report data about gender representation in their membership and to collaborate with social scientists who can provide valuable expertise. Importantly, we encourage all scientific bodies to increase transparency about the successes and failures of interventions that they have used in the past to address bias.

Notably, for many of the issues raised in this article, no straightforward solutions exist. Despite an increasing number of actions taken to mitigate gender bias in the workplace over the past decades, a thorough assessment and evaluation of their impact on diversity are often lacking as their short- and long-term impacts are hard to quantify in the real world ( Paluck and Green, 2009 ; Paluck et al., 2021 ). Long term impacts are vital to quantify especially as some evidence suggests that gender bias persists even after gender representation becomes balanced, paradoxically perpetuated by members who believe that gender bias has been overcome ( Begeny et al., 2020 ). Not all of the potential solutions presented here are destined to work, but several of them are certainly worth consideration (see Table 2 for an overview of tested vs. proposed actions).

For instance, diversity training is oftentimes recommended as one potential tool to mitigate gender bias. The admirable goal is to raise awareness on implicit and explicit biases that every human being carries. Although it is an intuitive way to tackle bias, the efficiency of diversity training is currently debated. Some studies, especially in the corporate sector, have reported modest to no effect of trainings with potential adverse effects for certain minority groups ( Dobbin and Kalev, 2013 ; Dobbin et al., 2011 ; Kalev et al., 2006 ), while other studies have shown encouraging results (in corporate sectors: Anand and Winters, 2008 and in academia: Carnes et al., 2015 ). Multiple factors influence the effectiveness of diversity training ( Roberson et al., 2013 ). Among them, the design of the training itself; such as the format, the length, and most importantly the way men are depicted (as allies and not oppressors); and the way to assign training (i.e. voluntarily, in person) may positively influence the outcome of these initiatives ( Bezrukova et al., 2016 ; Kalev and Dobbin, 2020 ). Genuine motivation, support and commitment from superiors, social accountability, and transparency play important roles ( Chang et al., 2019 ; Dobbin and Kalev, 2020 ). Lastly, as diversity training is not effective to change behavior in isolation ( Kalev et al., 2006 ), other actions and concrete changes at the institutional and societal levels are needed ( Dobbin and Kalev, 2020 ; Paluck et al., 2021 ).

Combining several actions is required for successful outcomes. For instance, increasing the representation of women across scientific bodies (i.e. hiring committees, review panels, in mentorship) and career stages can be helpful in reducing bias, but on its own it is not enough. Extensive research in hundreds of thousands of participants and across multiple countries has shown that increasing the enrollment of women students in higher education can reduce gender stereotypes. However, increasing the employment of women as researchers reduces only explicit, but not implicit stereotypes ( Miller et al., 2015 ). The perseverance of explicit gender stereotypes is stronger in disciplines that are male-dominated, but implicit stereotypes remain even in disciplines where women are well represented ( Smyth and Nosek, 2015 ). Gender stereotypes are also prevalent in women, who can be biased against women. It is important to highlight that increasing the representation of women is a necessary but not sufficient condition for addressing gender bias.

A second major challenge in improving gender equity is that not all scientific fields have the same gender imbalances across career stages. Several fields like psychology typically achieve a more balanced gender ratio than other men-dominated fields such as engineering. Future attempts should implement initiatives that cater to the needs of each sub-field and should also test the generalizability of initiatives across fields.

Last, one major open question is that of governance. To date there is a lack of governance models for monitoring gender bias, and for deciding whether a given solution is sufficient, or well implemented. Importantly, the decision about whether a solution is successful often relies on arbitrary metrics and does not take into account the experiences of women who are targets of bias. We invite scholars to develop better governance models and oversight committees for monitoring gender bias in an inclusive and objective way.

Conclusions

Gender bias is a complex assortment of problems, encompassing all career stages. Concrete actions are required to address each of the facets of gender bias, and need to be initiated by every academic entity, from individuals to departments to conferences and professional organizations. These actions, in combination with strong role models and a diverse pool of allies, will make it possible to shift the culture and bring positive change. The time for action is now.

Acknowledgements

We thank Susan Fiske, Vinitha Rangarajan, Kristina R. Olson, and Sapna Cheryan for their help in editing and improving the manuscript and Luisa Reis Castro for valuable discussions. A.T. is supported by the Interfaculty Research Cooperation “Decoding Sleep: From Neurons to Health and Mind” of the University of Bern, and the Swiss National Science Foundation (#320030_188737 and P300PA_174451). E.A.B is supported by NIH grant OD-010425, A.L.F. by the Simons Collaboration for the Global Brain, S.K. by NIH (RO1MH64043, RO1EY017699, 21560-685 Silvio O. Conte Center), the James S. McDonnell Foundation and the Overdeck Family Foundation. C.K. is supported by the Jacobs foundation; N.J.K. by NIH/NIGMS P01-GM118629 and NIH/NIMH P50-MH109429; J.J.L. by U19NS107609-01. A.C.N is funded by a Wellcome Trust Senior Investigator Award (ACN) 104571/Z/14/Z; James S. McDonnell Foundation Understanding Human Cognition Collaborative Award 220020448; and by the NIHR Oxford Health Biomedical Research Centre. The Wellcome Centre for Integrative Neuroimaging is supported by core funding from the Wellcome Trust (203139/Z/16/Z). S.K.R. is supported by NIH/NIDCD 1R21DC016985. A.K.S. is supported by a research grant from the Research Council of Norway (RCN; project number 240389) and through the RCNs Centres of Excellence scheme (project number 262762 RITMO). J.D.W. is supported by NIMH R01-MH121448 and NIMH R01-MH117763, W.-J.W. by the US Office of Naval Research (ONR) grant N00014-17-1-2041, US National Institutes of Health (NIH) grant 062349, and the Simons Collaboration on the Global Brain program grant 543057SPI. M.V.I. and N.F.D. contributions are supported by NIH/NIDCD R01-DC016345; DSB is supported by NSF CAREER PHY-1554488. R.T.K. is supported by NINDS NS21135, NIMH CONTE Center PO-MH109429, Brain Initiative U19 NS1076, and Brain Initiative U01 NS108916

References * :

* The gender proportions in the references list of this manuscript have been checked with cleanBib ( https://github.com/dalejn/cleanBib ) to evaluate gender ratio. Our reference list contains 42.4% woman(first)/woman(last), 12.2% man/woman, 22% woman/man, 18.5% man/man, and 4.88% unknown categorization. The remaining percentage is unknown. It is important to note the limits of classifying gender identity using names, pronouns, other signifiers scraped from online databases, and that this methodology cannot account for intersex, non-binary, or transgender people.

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Harvard Business School Case Study: Gender Equity

By Jodi Kantor

• Sept. 7, 2013

BOSTON — When the members of the Harvard Business School class of 2013 gathered in May to celebrate the end of their studies, there was little visible evidence of the experiment they had undergone for the last two years. As they stood amid the brick buildings named after businessmen from Morgan to Bloomberg, black-and-crimson caps and gowns united the 905 graduates into one genderless mass.

But during that week’s festivities, the Class Day speaker, a standout female student, alluded to “the frustrations of a group of people who feel ignored.” Others grumbled that another speechmaker, a former chief executive of a company in steep decline, was invited only because she was a woman. At a reception, a male student in tennis whites blurted out, as his friends laughed, that much of what had occurred at the school had “been a painful experience.”

He and his classmates had been unwitting guinea pigs in what would have once sounded like a far-fetched feminist fantasy: What if Harvard Business School gave itself a gender makeover, changing its curriculum, rules and social rituals to foster female success?

The country’s premier business training ground was trying to solve a seemingly intractable problem. Year after year, women who had arrived with the same test scores and grades as men fell behind. Attracting and retaining female professors was a losing battle; from 2006 to 2007, a third of the female junior faculty left.

Some students, like Sheryl Sandberg, class of ’95, the Facebook executive and author of “Lean In,” sailed through. Yet many Wall Street-hardened women confided that Harvard was worse than any trading floor, with first-year students divided into sections that took all their classes together and often developed the overheated dynamics of reality shows. Some male students, many with finance backgrounds, commandeered classroom discussions and hazed female students and younger faculty members, and openly ruminated on whom they would “kill, sleep with or marry” (in cruder terms). Alcohol-soaked social events could be worse.

“You weren’t supposed to talk about it in open company,” said Kathleen L. McGinn, a professor who supervised a student study that revealed the grade gap. “It was a dirty secret that wasn’t discussed.”

But in 2010, Drew Gilpin Faust, Harvard’s first female president, appointed a new dean who pledged to do far more than his predecessors to remake gender relations at the business school. He and his team tried to change how students spoke, studied and socialized. The administrators installed stenographers in the classroom to guard against biased grading, provided private coaching — for some, after every class — for untenured female professors, and even departed from the hallowed case-study method.

The dean’s ambitions extended far beyond campus, to what Dr. Faust called in an interview an “obligation to articulate values.” The school saw itself as the standard-bearer for American business. Turning around its record on women, the new administrators assured themselves, could have an untold impact at other business schools, at companies populated by Harvard alumni and in the Fortune 500, where only 21 chief executives are women. The institution would become a laboratory for studying how women speak in group settings, the links between romantic relationships and professional status, and the use of everyday measurement tools to reduce bias.

“We have to lead the way, and then lead the world in doing it,” said Frances Frei, her words suggesting the school’s sense of mission but also its self-regard. Ms. Frei, a popular professor turned administrator who had become a target of student ire, was known for the word “unapologetic,” as in: we are unapologetic about the changes we are making.

By graduation, the school had become a markedly better place for female students, according to interviews with more than 70 professors, administrators and students, who cited more women participating in class, record numbers of women winning academic awards and a much-improved environment, down to the male students drifting through the cafeteria wearing T-shirts celebrating the 50th anniversary of the admission of women. Women at the school finally felt like, “ ‘Hey, people like me are an equal part of this institution,’ ” said Rosabeth Moss Kanter, a longtime professor.

And yet even the deans pointed out that the experiment had brought unintended consequences and brand new issues. The grade gap had vaporized so fast that no one could quite say how it had happened. The interventions had prompted some students to revolt, wearing “Unapologetic” T-shirts to lacerate Ms. Frei for what they called intrusive social engineering. Twenty-seven-year-olds felt like they were “back in kindergarten or first grade,” said Sri Batchu, one of the graduating men.

Students were demanding more women on the faculty, a request the deans were struggling to fulfill. And they did not know what to do about developments like female students dressing as Playboy bunnies for parties and taking up the same sexual rating games as men. “At each turn, questions come up that we’ve never thought about before,” Nitin Nohria, the new dean, said in an interview.

The administrators had no sense of whether their lessons would last once their charges left campus. As faculty members pointed out, the more exquisitely gender-sensitive the school environment became, the less resemblance it bore to the real business world. “Are we trying to change the world 900 students at a time, or are we preparing students for the world in which they are about to go?” a female professor asked.

The Beginning

Nearly two years earlier, in the fall of 2011, Neda Navab sat in a class participation workshop, incredulous. The daughter of Iranian immigrants, Ms. Navab had been the president of her class at Columbia, advised chief executives as a McKinsey & Company consultant and trained women as entrepreneurs in Rwanda. Yet now that she had arrived at the business school at age 25, she was being taught how to raise her hand.

A second-year student, a former member of the military, stood in the front of the classroom issuing commands: Reach up assertively! No apologetic little half-waves! Ms. Navab exchanged amused glances with new friends. She had no idea that she was witnessing an assault on the school’s most urgent gender-related challenge.

Women at Harvard did fine on tests. But they lagged badly in class participation, a highly subjective measure that made up 50 percent of each final mark. Every year the same hierarchy emerged early on: investment bank and hedge fund veterans, often men, sliced through equations while others — including many women — sat frozen or spoke tentatively. The deans did not want to publicly dwell on the problem: that might make the women more self-conscious. But they lectured about respect and civility, expanded efforts like the hand-raising coaching and added stenographers in every class so professors would no longer rely on possibly biased memories of who had said what.

They rounded out the case-study method, in which professors cold-called students about a business’s predicament, with a new course called Field, which grouped students into problem-solving teams. (Gender was not the sole rationale for the course, but the deans thought the format would help.) New grading software tools let professors instantly check their calling and marking patterns by gender. One professor, Mikolaj Piskorski, summarized Mr. Nohria’s message later: “We’re going to solve it at the school level, but each of you is responsible to identify what you are doing that gets you to this point.”

Mr. Nohria, Ms. Frei and others involved in the project saw themselves as outsiders who had succeeded at the school and wanted to help others do the same. Ms. Frei, the chairwoman of the first-year curriculum, was the most vocal, with her mop of silver-brown hair and the drive of the college basketball player she had once been. “Someone says ‘no’ to me, and I just hear ‘not yet,’ ” she said.

After years of observation, administrators and professors agreed that one particular factor was torpedoing female class participation grades: women, especially single women, often felt they had to choose between academic and social success.

One night that fall, Ms. Navab, who had laughed off the hand-raising seminar, sat at an Ethiopian restaurant wondering if she had made a bad choice. Her marketing midterm exam was the next day, but she had been invited on a very business-school kind of date: a new online dating service that paired small groups of singles for drinks was testing its product. Did Ms. Navab want to come? “If I were in college, I would have said let’s do this after the midterm,” she said later.

But she wanted to meet someone soon, maybe at Harvard, which she and other students feared could be their “last chance among cream-of-the-crop-type people,” as she put it. Like other students, she had quickly discerned that her classmates tended to look at their social lives in market terms, implicitly ranking one another. And like others, she slipped into economic jargon to describe their status.

The men at the top of the heap worked in finance, drove luxury cars and advertised lavish weekend getaways on Instagram, many students observed in interviews. Some belonged to the so-called Section X, an on-again-off-again secret society of ultrawealthy, mostly male, mostly international students known for decadent parties and travel.

Women were more likely to be sized up on how they looked, Ms. Navab and others found. Many of them dressed as if Marc Jacobs were staging a photo shoot in a Technology and Operations Management class. Judging from comments from male friends about other women (“She’s kind of hot, but she’s so assertive”), Ms. Navab feared that seeming too ambitious could hurt what she half-jokingly called her “social cap,” referring to capitalization.

“I had no idea who, as a single woman, I was meant to be on campus,” she said later. Were her priorities “purely professional, were they academic, were they to start dating someone?”

As she scooped bread at the product-trial-slash-date at the Ethiopian restaurant, she realized that she had not caught the names of the men at the table. The group drank more and more. The next day she took the test hung over, her performance a “disaster,” she joked.

The deans did not know how to stop women from bartering away their academic promise in the dating marketplace, but they wanted to nudge the school in a more studious, less alcohol-drenched direction. “We cannot have it both ways,” said Youngme Moon, the dean of the M.B.A. program. “We cannot be a place that claims to be about leadership and then say we don’t care what goes on outside the classroom.”

But Harvard Business students were unusually powerful, the school’s products and also its customers, paying more than $50,000 in tuition per year. They were professionals, not undergraduates. One member of the class had played professional football; others had served in Afghanistan or had last names like Blankfein ( Alexander , son of Lloyd, chief executive of Goldman Sachs). They had little knowledge of the institutional history; the deans talked less about the depressing record on women than vague concepts like “culture” and “community” and “inclusion.”

As the semester went on, many students felt increasingly baffled about the deans’ seeming desire to be involved in their lives. They resented the additional work of the Field courses, which many saw as superfluous or even a scheme to keep them too busy for partying. Students used to form their own study groups, but now the deans did it for them.

As Halloween approached, some students planned to wear costumes to class, but at the last minute Ms. Frei, who wanted to set a serious tone and head off the potential for sexy pirate costumes, sent a note out prohibiting it, provoking more eye rolls. “How much responsibility does H.B.S. have?” Laura Merritt, a co-president of the class, asked later. “Do we have school uniforms? Where do you stop?”

A few days before the end of the fall semester, Amanda Upton, an investment banking veteran, stood before most of her classmates, lecturing and quizzing them about finance. Every term just before finals, the Women’s Student Association organized a review session for each subject, led by a student who blitzed classmates through reams of material in an hour. Some of the first-years had not had a single female professor. Now Ms. Upton delivered a bravura performance, clearing up confusion about discounted cash flow and how to price bonds, tossing out Christmas candy as rewards.

Like many other women, Kate Lewis, the school newspaper editor, believed in the deans’ efforts. But she thought Ms. Upton’s turn did more to fortify the image of women than anything administrators had done. “It’s the most powerful message: this girl knows it better than all of you,” she said.

Breaking the Ice

One day in April 2012, the entire first-year class, including Brooke Boyarsky, a Texan known for cracking up her classmates with a mock PowerPoint presentation, reported to classrooms for a mandatory discussion about sexual harassment. As students soon learned, one woman had confided to faculty members that a male student she would not identify had groped her in an off-campus bar months before. Rather than dismissing the episode, the deans decided to exploit it: this was their chance to discuss the drinking scene and its consequences. “They could not have gone any more front-page than this,” Ms. Boyarsky said later.

Everyone in Ms. Boyarsky’s classes knew she was incisive and funny, but within the campus social taxonomy, she was overlooked — she was overweight and almost never drank much, stayed out late or dated. After a few minutes of listening to the stumbling conversation about sexual harassment, she raised her hand to make a different point, about the way the school’s social life revolved around appearance and money.

“Someone made the decision for me that I’m not pretty or wealthy enough to be in Section X,” she told her classmates, her voice breaking.

The room jumped to life. The students said they felt overwhelmed by the wealth that coursed through the school, the way it seemed to shape every aspect of social life — who joined activities that cost hundreds of dollars, who was invited to the parties hosted by the student living in a penthouse apartment at the Mandarin Oriental hotel in Boston. Some students would never have to seek work at all — they were at Harvard to learn to invest their families’ fortunes — and others were borrowing thousands of dollars a year just to keep up socially.

The discussion broke the ice, just not on the topic the deans had intended. “Until then, no one else had publicly said ‘Section X,’ ” Mr. Batchu said. Maybe it was because class was easier to talk about than gender, or maybe it was because class was the bigger divide — at the school and in the country.

That was only one out of 10 sessions. At most of the others, the men contributed little. Some of them, and even a few women, had grown to openly resent the deans’ emphasis on gender, using phrases like “ad nauseam” and “shoved down our throats,” protesting that this was not what they had paid to learn.

Patrick Erker was not among the naysayers — he considered himself a feminist and a fan of the deans. As an undergraduate at Duke, he had managed the women’s basketball team, wiping their sweat from the floor and picking up their dirty jerseys.

But as he silently listened to the discussion, he decided the setup was all wrong: a discussion of a sex-related episode they knew little about, with “89 other people judging every word,” led by professors who would be grading them later that semester.

“I’d like to be candid, but I paid half a million dollars to come here,” another man said in an interview, counting his lost wages. “I could blow up my network with one wrong comment.” The men were not insensitive, they said; they just considered the discussion a poor investment of their carefully hoarded social capital. Mr. Erker used the same words as many other students had to describe the mandatory meetings: “forced” and “patronizing.”

That week, Andrew Levine, the director of the annual spoof show, was notified by administrators that he was on academic and social probation because other students had consumed alcohol in the auditorium after a performance. (His crime: dining with visiting family instead of staying as he had promised in a contract.) He was barred from social events and put on academic probation as well.

That was just what students needed to believe their worst suspicions about the administration. Ms. Frei had not made the decision about Mr. Levine and worked to cancel his academic probation, he said later, but students called her a hypocrite, a leadership expert who led badly. Hundreds of students soon wore T-shirts that said “Free Andy” or “Unapologetic.”

“Daddy, why are the students hating on you?” Mr. Nohria’s teenage daughters asked him, he told students later.

A few days before commencement, Nathan Bihlmaier , a second-year student, disappeared while celebrating with classmates in Portland, Me. He had last been seen so inebriated that a bartender had asked him to leave a pub. When the authorities told students that Mr. Bihlmaier’s body had been dredged from the harbor, apparently after a fall, Mr. Nohria and Ms. Moon were standing beside them.

The first year of their experiment was ending with a catastrophe that brought home how little sway they really had over students’ actions. Mr. Bihlmaier had not even been the drinking type. In the spirit of feminist celebration, Ms. Sandberg gave a graduation address at the deans’ invitation, but during the festivities all eyes were on Mr. Bihlmaier’s widow, visibly pregnant with their first child.

Amid all the turmoil, though, the deans saw cause for hope. The cruel classroom jokes, along with other forms of intimidation, were far rarer. Students were telling them about vigorous private conversations that had flowed from the halting public ones. Women’s grades were rising — and despite the open resentment toward the deans, overall student satisfaction ratings were higher than they had been for years.

A Lopsided Situation

Even on the coldest nights of early 2013, Ms. Frei walked home from campus, clutching her iPhone and listening to a set of recordings made earlier in the day. Once her two small sons were in bed, she settled at her dining table, wearing pajamas and nursing a glass of wine, and fired up the digital files on her laptop. “Really? Again?” her wife, Anne Morriss, would ask.

Ms. Frei been promoted to dean of faculty recruiting, and she was on a quest to bolster the number of female professors, who made up a fifth of the tenured faculty. Female teachers, especially untenured ones, had faced various troubles over the years: uncertainty over maternity leave, a lack of opportunities to write papers with senior professors, and students who destroyed their confidence by pelting them with math questions they could not answer on the spot or commenting on what they wore.

“As a female faculty member, you are in an incredibly hostile teaching environment, and they do nothing to protect you,” said one woman who left without tenure. A current teacher said she was so afraid of a “wardrobe malfunction” that she wore only custom suits in class, her tops invisibly secured to her skin with double-sided tape.

Now Ms. Frei, the guardian of the female junior faculty, was watching virtually every minute of every class some of them taught, delivering tips on how to do better in the next class. She barred other professors from giving them advice, lest they get confused. But even some of Ms. Frei’s allies were dubious.

At the end of every semester, students gave professors teaching scores from a low of 1 to a high of 7, and some of the female junior faculty scores looked beyond redemption. More of the male professors arrived at Harvard after long careers, regaling students with real-life experiences. Because the pool of businesswomen was smaller, female professors were more likely to be academics, and students saw female stars as exceptions.

“The female profs I had were clearly weaker than the male ones,” said Halle Tecco, a 2011 graduate. “They weren’t able to really run the classroom the way the male ones could.”

Take the popular second-year courses team-taught by Richard S. Ruback, a top finance professor, and Royce G. Yudkoff, a co-founder of a private equity firm that managed billions of dollars. The men taught students, among other lessons, how to start a “search fund,” a pool of money to finance them while they found and acquired a company. In recent years, search funds had become one of the hottest, riskiest and most potentially lucrative pursuits for graduates of top business schools — shortcuts to becoming owners and chief executives.

The two professors were blunt and funny, pushing a student one moment, ribbing another one the next. They embodied the financial promise of a Harvard business degree: if the professors liked you, students knew, they might advise and even back you.

As Ms. Frei reviewed her tapes at night, making notes as she went along, she looked for ways to instill that confidence. The women, who plainly wanted to be liked, sometimes failed to assert their authority — say, by not calling out a student who arrived late. But when they were challenged, they turned too tough, responding defensively (“Where did you get that?”).

Ms. Frei urged them to project warmth and high expectations at the same time, to avoid trying to bolster their credibility with soliloquies about their own research. “I think the class might be a little too much about you, and not enough about the students,” she would tell them the next day.

By the end of the semester, the teaching scores of the women had improved so much that she thought they were a mistake. One professor had shot to a 6 from a 4. Yet all the attention, along with other efforts to support female faculty, made no immediate impact on the numbers of female teachers. So few women were coming to teach at the school that evening out the numbers seemed almost impossible.

As their final semester drew to a close, the students were preoccupied with the looming question of their own employment. Like graduates before them, the class of 2013 would to some degree part by gender after graduation, with more men going into higher-paying areas like finance and more women going into lower-paying ones like marketing.

Ms. Navab, who had started dating one of the men — with an M.D. and an M.B.A. — from the Ethiopian dinner, had felt freer to focus on her career once she was paired off. She was happy with her job at a California start-up, but she pointed out that she and some other women never heard about many of the most lucrative jobs because the men traded contacts and tips among themselves.

This was the lopsided situation that women in business school were facing: in intellectual prestige, they were pulling even with or outpacing male peers, but they were not “ touching the money ,” as Nori Gerardo Lietz, a real estate private equity investor and faculty member, put it. A few alumnae had founded promising start-ups like Rent the Runway , an evening wear rental service, but when it came to reaping big financial rewards, most women were barely in the game.

At an extracurricular presentation the year before, a female student asked William Boyce, a co-founder of Highland Capital Partners, a venture capital firm , for advice for women who wanted to go into his field. “Don’t,” he laughed, according to several students present.   Male partners did not want them there, he continued, and he was doing them a favor by warning them.

Some women protested or walked out, but others said they believed he was telling the truth. (In interviews, Mr. Boyce denied saying women should not go into venture capital, but an administrator said student complaints prompted the school to contact the firm, which he had left decades before.)

The deans had not focused on career choice, earning power or staying in the work force; they felt they first needed to address campus issues. Besides, the earning gap posed a dilemma: they were hoping fewer students would default to finance as a career. “Have the courage to make the choices early in your life that are determined by your passions,” Mr. Nohria told students.

Plenty of women had taken Mr. Ruback and Mr. Yudkoff’s classes on acquiring and running businesses, including Ms. Upton, who had delivered the crackerjack finance presentation. She counted 30 to 40 classmates planning search funds, all men except for a no-nonsense engineer named Jennifer Braus. The professors eventually decided to finance and advise Ms. Braus, hoping other Harvard women would follow.“Nothing succeeds like success,” Mr. Ruback said.

Ms. Upton decided to take a far lower-risk job managing a wealthy family’s investments in Pittsburgh, where her fiancé lived. “You can either be a frontier charger or have an easier, happier life,” she said.

Looking Ahead

Of all the ceremonies and receptions during graduation week, the most venerated was the George F. Baker Scholar Luncheon, for the top 5 percent of the class, held in a sunny dining room crowded with parents who looked alternately thrilled and intimidated by what their offspring had achieved.

In recent years, the glory of the luncheon had been dimmed by discomfort at the low number of female honorees. But this year, almost 40 percent of the Baker scholars were women. It was a remarkable rise that no one could precisely explain. Had the professors rid themselves of unconscious biases? Were the women performing better because of the improved environment? Or was the faculty easing up in grading women because they knew the desired outcome?

“To my head, all three happened,” Professor Piskorski said. But Mr. Nohria said he had no cause to think the professors had used the new software, and the subjective participation scores, to avoid gender gaps. “Sunshine is the best disinfectant,” he said, a phrase that he said had guided him throughout his project.

One of the Baker scholars was Ms. Boyarsky, the classroom truth-teller. Two hours after the luncheon, she stepped up to a lectern to address thousands of graduates, faculty members and parents . Of the two dozen or so men and only 2 women who had tried out before a student committee, she had beaten them all, with a witty, self-deprecating speech unlike any in the school’s memory.

“I entered H.B.S. as a truly ‘untraditional applicant’: morbidly obese,” she said.

The theme of her speech was finding the courage to make necessary but painful changes. “Courage is a brand new H.B.S. professor, younger than some of her students, teaching her very first class on her very first day,” she said. “Courage is one woman” — the one who reported the groping episode — “who wakes the entire school up to the fact that gender relations still have a long way to go at H.B.S.”

And, Ms. Boyarsky continued, she had lost more than 100 pounds during her final year at Harvard. “Courage was then me battling the urge to be defensive — something I believe I had been for a long time about this particular issue — and taking a hard, honest look within myself to figure out what had prevented change,” she said.

Even before she finished, her phone was buzzing with e-mails and texts from classmates. She was the girl everyone wished they had gotten to know better, the graduation-week equivalent of the person whose obituary made you wish you had followed her work. She had closed the two-year experiment by making the best possible case for it. “This is the student they chose to show off to the world,” Ms. Moon said. For the next academic year, she was arranging for second-year students to lead many of the trickiest conversations, realizing students were the most potent advocates.

The administrators and the class of 2013 were parting ways, their experiment continuing. The deans vowed to carry on but could not say how aggressively: whether they were willing to revise the tenure process to attract more female contenders, or allow only firms that hired and promoted female candidates to recruit on campus. “We made progress on the first-level things, but what it’s permitting us to do is see, holy cow, how deep-seated the rest of this is,” Ms. Frei said.

The students were fanning out to their new jobs, full of suspense about their fates. Because of the unique nature of what they had experienced, they knew, every class alumni magazine update and reunion would be a referendum on how high the women could climb and what values the graduates instilled — the true verdict on the experiment in which they had taken part.

As Ms. Boyarsky glanced around her new job as a consultant at McKinsey in Dallas, she often noticed that she was outnumbered by men, but she spoke up anyway. She was dating more than she had at school, she added with shy enthusiasm.

“I am super excited to go to my 30th reunion,” she said.

Brent McDonald and Hannah Fairfield contributed reporting.

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A case study of gender bias in science reporting

An analysis reveals a persistent gender disparity in the sources quoted in Nature ’s news and feature articles, although the gap is shrinking.

Gender disparities in science have attracted a lot of attention in the last decade or so, but the biases against women in media coverage of science haven’t received nearly as much focus. A recent study of Nature ’s news and feature articles sheds light on how often women are quoted in science news. The study finds that women continue to be quoted less often than men in the high-profile journal, although the gap seems to be narrowing.

Conducted by Natalie Davidson and Casey Greene of the University of Colorado School of Medicine, the study , posted in June on bioRxiv, analyzed more than 22 000 journalist-written news and feature articles that were published in the front half of Nature from 2005 to 2020. The researchers used software to approximately identify the genders and ethnicities of authors and sources. The software had a few limitations: It had a slight male bias, didn’t include a nonbinary gender assignment, and couldn’t identify all names. The researchers compared the software-assessed demographics of sources quoted in Nature ’s news section with that of the authors of the more than 13 000 research papers published in the back half of Nature during that period.

Davidson and Greene found a significant decrease in the proportion of men quoted in Nature ’s pages over those 15 years. The analysis found that in 2005, 87% of quotes were deemed to have come from men, whereas male researchers were the first authors of 73% of research papers in the study sample. By 2020 the likelihood that quotes came from men was down to about 69%. Articles about career-related topics were the only ones to achieve gender parity, the study found.

Although Nature publishes research from several disciplines with different proportions of female participation, the new study doesn’t distinguish the results by field or topic. Research papers published in Nature also may not be representative of the gender balance in the academic community or of research overall, Davidson says.

To account for that possible bias, the researchers selected another random sample of 36 000 research papers published over the same period in other journals run by publishing giant Springer Nature, which owns Nature . When compared with that data set, the estimated proportion of men quoted in Nature news and feature articles in 2020 (69%) is higher than the percentage of male first authors of the sample papers (about 63%) but lower than the rate of male last authors (76%). In contrast, the male quotation rate is lower than the rates of male first and last authors of Nature manuscripts, which are 74% and 80%, respectively. Davidson says that Nature research papers are more likely to be male-dominated (in first and last authors) than those published in other Springer Nature journals.

In an editorial published in response to the analysis, Nature acknowledges that its journalists need to work harder to eliminate biases, noting that the new analysis has shown that software can be used to recognize such trends. The editorial also mentions that Nature has been collecting data on gender diversity in its commissioned content for the last five years.

Gender bias in Physics Today

Nature is not alone in grappling with gender bias in science journalism. In an attempt to approximately replicate the Nature study’s methodology, Physics Today recorded the people quoted in 2005 and 2020 in two staff-written sections of the printed magazine: Search & Discovery, which covers new scientific research, and Issues & Events, which focuses on science policy and matters of interest to the physical sciences community.

In 2005, about 89% of quotes in those Physics Today articles were from male sources, a rate slightly more skewed than Nature ’s 87% in the same year. In 2020 the male quotation proportion was down to 74%, compared with Nature ’s 69%. Unlike in the Nature study, Physics Today did not examine the gender breakdown of the authors of journal articles in the physical sciences.

Although Physics Today is doing better than in the past, clearly there is still a lot more work to do. Physics Today ’s editors have been reaching out to more diverse sources in recent years and will continue to make those efforts a priority.

— Physics Today editors

Outside researchers say the new research, though not yet peer reviewed, is solid. Luke Holman, an evolutionary biologist at Edinburgh Napier University in the UK, says the new study has “novel, high-quality, and transparent methodology.” Holman co-authored a 2018 study that found that at the current rate of change, it would take 16 years for female researchers—averaged across scientific disciplines—to catch up with men and produce the same number of papers. In physics the gender gap would take 258 years to disappear.

Although Holman likes the new study, he notes that it doesn’t mention how many different people are quoted in each article in the sample, how many quotes are from the same sources, and how much page space is given to each source.

“It’s a really good thing that more female scientists are being quoted, even though things like this don’t normally directly contribute to tenure decisions,” says Barton Hamilton, an economist at Washington University in St Louis who has written about the gender gap in National Institutes of Health grant applications . “It’s very important that the faculty being quoted are representative of the faculty that are doing the work.”

Other analyses have also shown that women are being quoted more often in science news than in the past. For example, the World Association for Christian Communication released the latest quinquennial report on 14 July as part of the nongovernmental organization’s Global Media Monitoring Project. The report investigated, among other things, the extent to which women are quoted in the news media. Of all the news topics, women feature most often as sources and subjects in science and health news, says study editor Sarah Macharia, a consultant in gender, media, and international policy based in Toronto.

In 1995, women were 27% of the subjects and sources in science and health stories across different types of media; that representation increased to 35% by 2015. But Macharia says that as science and health news has grown as a percentage of all news coverage during the COVID-19 pandemic, the proportion of women as subjects and sources has decreased to 30%. “So as that topic has come to the limelight so dramatically and interest in the news has grown, women have been displaced from that space,” Macharia says.

Davidson and Greene’s study also compared quotation rates to rates of first or last authorship for scientists with various name origins in manuscripts published in Nature and other Springer Nature journals. They reported severe under-quotation relative to their rates of authorship for scientists with names originating in East Asia, and overrepresentation of scientists with English, Irish, Scottish, or Welsh names.

Deborah Blum, a science writer and director of the Knight Science Journalism program at MIT, explains that the reporter is responsible for identifying who did what in the studies they report on and for finding commenters from diverse backgrounds who did not work on the studies. “And that’s not just journalists trying to be politically correct,” she says. “When you have a diversity of scientists, the science is smarter. If you bring that to your reporting, your story is smarter too.”

But choosing diverse sources is not always easy or straightforward. Journalists often have to produce stories under tight deadlines and are sometimes limited to experts in a particular geographical location or time zone.

Holman sympathizes with the work that goes into finding sources but says, “If you have the opportunity to quote two equally qualified people and one of them is from an underrepresented part of the world or is a woman,” it’s best to quote that person.

Editor’s note: Dalmeet Singh Chawla regularly writes news pieces for Nature but had no involvement with the study. Madison Brewer performed the research for the Physics Today case study described in the box.

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• Dr. Richard Fletcher
• Prof. Daniel Frey
• Dr. Mike Teodorescu
• Amit Gandhi
• Audace Nakeshimana

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Exploring fairness in machine learning for international development, case study with data: mitigating gender bias on the uci adult database.

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Mitigating Gender Bias slides (PDF - 1.6MB)

Learning Objectives

• Explore steps and principles involved in building less-biased machine learning modules.
• Explore two classes of technique, data-based and model-based techniques for mitigating bias in machine learning.
• Apply these techniques to the UCI adult dataset.

The repository for this module can be found at Github - ML Bias Fairness .

Defining algorithmic/model bias

Bias or algorithmic bias will be defined as systematic errors in an algorithm/model that can lead to potentially unfair outcomes.

Bias can be quantified by looking at discrepancies in the model error rate for different populations.

UCI adult dataset

The UCI adult dataset is a widely cited dataset used for machine learning modeling. It includes over 48,000 data points extracted from the 1994 census data in the United States. Each data point has 15 features, including age, education, occupation, sex, race, and salary, among others.

The dataset has twice as many men as women. Additionally, the data shows income discrepancies across genders. Approximately 1 in 3 of men are reported to make over $50K, whereas only 1 in 5 women are reported to make the same amount. For high salaries, the number of data points in the male population is significantly higher than the number of data points in the female category.

Preparing data

In order to prepare the data for machine learning, we will explore different steps involved in transforming data from raw representation to appropriate numerical or categorical representation. One example is converting native country to binary, representing individuals whose native country was the US as 0 and individuals whose native country was not the US as 1. Similar representations need to be made for other attributes such as sex and salary. One-hot encoding can be used for attributes where more than two choices are possible.

Binary coding was chosen for simplicity, but this decision must be made on a case-by-case basis. Converting features like work class can be problematic if individuals from different categories have systematically different levels of income. However, not doing this can also be problematic if one category has a population that is too small to generalize from.

Illustrating gender bias

We apply the standard ML approach to the UCI adult dataset. The steps that are followed are 1) splitting the dataset into training and test data, 2) selecting model (MLPClassifier in this case), 3) fitting the model on training data, and 4) using the model to make predictions on test data. For this application, we will define the positive category to mean high income (>$50K/year) and the negative category to mean low income (<=$50K/year).

The model results show that the positive rates and true positive rates are higher for the male demographic. Additionally, the negative rate and true negative rates are higher for the female demographic. This shows consistent disparities in the error rates between the two demographics, which we will define as gender bias.

Exploring data-based debiasing techniques

We hypothesize that gender bias could come from unequal representation of male and female demographics. We attempt to re-calibrate and augment the dataset to equalize the gender representation in our training data. We will explore the following techniques and their outcomes. We will compare the results after describing each approach.

Debiasing by unawareness: we drop the gender attribute from the model so that the algorithm is unaware of an individual’s gender. Although the discrepancy in overall accuracy does not change, the positive, negative, true positive, and true negative rates are much closer for the male and female demographics.

Equalizing the number of data points: we attempt different approaches to equalizing the representation. The different equalization criteria are #male = #female, #high income male = #high income female, #high income male/#low income male = #high income female/#low income female. One of the disadvantages of equalizing the number of data points is that the dataset size is limited by the size of the smallest demographic. Equalizing the ratio can overcome this limitation.

Augment data with counterfactuals: for each data point X i with a given gender, we generate a new data point Y i that only differs with X i at the gender attribute and add it to our dataset. The gaps between male and female demographics are significantly reduced through this approach.

We see varying accuracy across different approaches on accuracy for the male and female demographics, as shown in the plot below. The counterfactual approach is shown to be the best at reducing gender bias. We see similar behavior for the positive rates and negative rates as well as the true positive and true negative rates.

Model-based debiasing techniques

Different ML models show different levels of bias. By changing the model type and architecture, we can observe which ones will be less biased for this application. We examine single and multi-model architectures. The models that will be considered are support vector, random forest, KNN, logistic regression, and MLP classifiers. Multi-model architectures involve training a group of different models that make a final prediction based on consensus. Two approaches can be used for consensus; hard voting, where the final prediction is the majority prediction among the models and soft voting, where the final prediction is the average prediction. The following plots show the differences in overall accuracy and the discrepancies between accuracy across gender.

It is also important to compare the results of the models across multiple training sessions. For each model type, five instances of the model were trained and compared. Results are shown the plot below. We can see that different models have different variability in performance for different metrics of interest.

Dua, D. and Graff, C. (2019). UCI Machine Learning Repository . Irvine, CA: University of California, School of Information and Computer Science.

Bishop, Christopher M. Pattern Recognition and Machine Learning . New York: Springer 2006. ISBN: 9780387310732.

Hardt, Moritz. (2016, October 7). “ Equality of opportunity in machine learning .” Google AI Blog .

Zhong, Ziyuan. (2018, October 21). “ A tutorial on fairness in machine learning .”  Toward Data Science .

Kun, Jeremy. (2015, October 19). “ One definition of algorithmic fairness: statistical parity .” 

Olteanu, Alex. (2018, January 3). “ Tutorial: Learning curves for machine learning in Python .”  DataQuest .

Garg, Sahaj, et al. 2018. “ Counterfactual fairness in text classification through robustness .” arXiv preprint arXiv:1809.10610.

Wikipedia contributors. (2019, September 6). “ Algorithmic bias .” In Wikipedia, The Free Encyclopedia . 

Contributions

Content presented by Audace Nakeshimana (MIT).

This content was created by Audace Nakeshimana and Maryam Najafian (MIT).

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Case Study UT Star Icon

Pao & Gender Bias

Ellen Pao stirred debate in the venture capital and tech industries when she filed a lawsuit against her employer on grounds of gender discrimination.

On May 10, 2012, executive Ellen Pao filed a lawsuit against her employer, Silicon Valley-based tech venture capital firm Kleiner Perkins Caufield & Byers (Kleiner Perkins), on grounds of gender discrimination. Pao began working at Kleiner Perkins in 2005. She became a junior investing partner, but after several years at the firm was passed over for a senior partner position and was eventually terminated. Pao claimed that men with similar profiles and achievements were promoted instead.

In late 2011, Pao and a coworker were asked by a senior partner to come up with ways of improving the firm’s treatment of women, but the senior partner, according to Pao, was “noncommittal.” On January 4, 2012, Pao took this issue a step further and wrote a formal memorandum to several of her superiors and the firm’s outside counsel. In the memorandum, she described harassment she had received while at the firm, claiming she had been excluded from meetings by male partners, and asserting an absence of training and policies to prevent discrimination at the firm. Pao’s memo indicated that she wished to work with the firm on improving conditions for women. She was fired on October 1, 2012. The lawsuit went to trial in February 2015.

In a testimony during the trial, Pao explained that she sued because there was no process for HR issues at the firm and believed she had exhausted all options for addressing these issues internally:

“It’s been a long journey, and I’ve tried many times to bring Kleiner Perkins to the right path. I think there should be equal opportunities for women and men to be venture capitalists. I wanted to be a VC but I wasn’t able to do so in that environment. And I think it’s important…to make those opportunities available in the future. And I wanted to make sure my story was told.”

Pao’s lawsuit made four claims against Kleiner Perkins: 1) they discriminated against Pao on the basis of gender by failing to promote her and/or terminating her employment; 2) they retaliated by failing to promote her because of conversations she had in late 2011 and/or the memo from January 4, 2012; 3) they failed to take all reasonable steps to prevent gender discrimination against her; and 4) they retaliated against her by terminating her employment because of conversations she had in late 2011 and/or the memo from January 4, 2012.

Pao’s legal team argued that men were promoted ahead of women, women who experienced sexual harassment received little support, and women’s ideas were often more quickly dismissed than men’s. Pao’s performance reviews revealed contradictory criticisms such as “too bold” and “too quiet.” Pao also accused company partner Ajit Nazre of pressuring her into an affair and subsequently retaliating against her after she ended the relationship. She said she received an inappropriate gift containing erotic imagery and was present while men at the firm were making inappropriate conversation. Further, the legal team described how Pao and other women had been left out of certain meetings and gatherings.

The defense’s case focused on Pao’s performance and character, noting that Pao received several negative performance reviews and acted entitled or resentful toward other employees and was not a team player. Evidence included evaluations, self-evaluations, meeting summaries, and messages both personal and professional. Kleiner Perkins claimed that Pao was paid more than her male counterparts, including bonuses and training. The firm also argued that Pao’s job description was mostly managerial and that limiting her involvement in investing was therefore not a form of discrimination.

The verdict was announced on March 27, 2015. The jury ruled 10 to 2 in favor of Kleiner Perkins on the first three claims, and 8 to 4 in favor of Kleiner Perkins on the fourth claim. Speaking after the trial, juror Steve Sammut said that the verdict came down to performance reviews, in which Pao’s negative criticism remained consistent each year. But he added that he wished there was some way for Kleiner Perkins to be punished for its treatment of employees, “It isn’t good. It’s like the wild, wild West.” Juror Marshalette Ramsey voted in favor of Pao, believing Pao had been discriminated against. Ramsey stated that the male junior partners who were promoted “had those same character flaws that Ellen was cited with.”

Deborah Rhode, law professor at Stanford University, said that even with this loss, Pao’s lawsuit succeeded in prompting debate about women in venture capital and tech. She stated, “This case sends a powerful signal to Silicon Valley in general and the venture capital industry in particular… Defendants who win in court sometimes lose in the world outside it.” After the verdict was announced, Pao stated that she hoped the case at least helped level the playing field for women and minorities in venture capital. She later wrote:

“I have a request for all companies: Please don’t try to silence employees who raise discrimination and harassment concerns. …I hope future cases prove me wrong and show that our community and our jurists have now developed a better understanding of how discrimination works in real life, in the tech world, in the press and in the courts.”

Pao’s case has since been credited for inspiring others facing workplace discrimination to act; similar lawsuits have been filed against companies such as Facebook, Twitter, and Microsoft.

Discussion Questions

1. At what points in this case study did Pao make the choice to voice her values? How did she voice her values in each of these instances?

2. Do you think Pao acted on her values effectively? Why or why not? Does the fact that she lost the lawsuit impact your reasoning? Explain.

3. Think through the seven pillars of GVV in relation to the case study above. Can you identify each pillar in Pao’s actions? Are there any pillars that you think Pao could have engaged more effectively? Explain.

4. If you were in Pao’s position at Kleiner Perkins, what would you have done and why? How might the pillars of GVV influence your actions? Select one of the pillars and describe how you would enact it in a situation described in the case study.

5. Based on the information in the case study, if you were a juror would you have ruled in favor of Pao or Kleiner Perkins? Why? How might your own values or biases influence your decision?

6. Have you ever worked at a job where you faced ethically questionable behavior? What did you do? In retrospect, do you wish you had done anything differently? How would you prepare for a similar situation today?

7. Have you ever witnessed or experienced discrimination in the workplace? What did you do? In retrospect, would you have done something differently? What do you think would be the ethically ideal way to handle instances of discrimination in the workplace?

Related Videos

Intro to GVV

Giving Voice to Values is learning about how to act on your values effectively – not about wondering whether you could.

GVV Pillar 1: Values

Know and appeal to a short list of widely shared values. Don’t assume too little (or too much) commonality with the viewpoints of others.

GVV Pillar 2: Choice

Believe that you have a choice about voicing your values and know what has helped – and hindered you – in the past so you can work around these factors.

GVV Pillar 3: Normalization

Normalization means expecting values conflicts so that you approach them calmly and competently. Over-reaction can limit your choices unnecessarily.

GVV Pillar 4: Purpose

Define your personal and professional purpose explicitly and broadly before conflicts arise, and appeal to this sense of purpose in others.

GVV Pillar 5: Self-Knowledge & Alignment

Self-knowledge and alignment means to voice and act on your values in a way that is consistent with who you are and builds on your strengths.

GVV Pillar 6: Voice

You are more likely to say words that you’ve pre-scripted for yourself, and more likely to “voice” your values, with scripting and practice.

GVV Pillar 7: Reasons & Rationalizations

By anticipating the typical reasons & rationalizations given for ethically questionable behavior, you are able to identify and prepare well-reasoned responses.

Bibliography

Ellen Pao Loses Silicon Valley Bias Case Against Kleiner Perkins http://www.nytimes.com/2015/03/28/technology/ellen-pao-kleiner-perkins-case-decision.html

Kleiner Perkin Portrays Ellen Pao as Combative and Resentful in Sex Bias Trial http://www.nytimes.com/2015/03/12/technology/kleiner-perkins-portrays-ellen-pao-as-combative-and-resentful-in-sex-bias-trial.html

Ellen Pao explains why she sued: “I wanted to make sure my story was told’ http://www.businessinsider.com/ellen-pao-explains-why-she-sued-kleiner-perkins-2015-3

Ellen Pao wanted “a multimillion dollar payout,” Kleiner lawyers contend http://arstechnica.com/tech-policy/2015/03/ellen-pao-wanted-a-multimillion-dollar-payout-kleiner-lawyers-contend/

Ellen Pao asked for a $10 million payment from Kleiner Perkins as the cost of ‘not fixing problems’ http://www.businessinsider.com/ellen-pao-asked-for-10-million-2015-3

What the Jury in the Ellen Pao-Kleiner Perkins Case Needed to Decide http://www.nytimes.com/interactive/2015/03/27/technology/document-ellen-pao-kleiner-perkins-suit-verdict-form-and-jury-instructions.html

A Juror Speaks About His Vote for Kleiner Perkins but Still Wants the Firm to ‘Be Punished’ http://recode.net/2015/03/30/a-juror-speaks-about-his-vote-for-kleiner-perkins-but-still-wants-the-firm-to-be-punished/

Ellen Pao Speaks: ‘I Am Now Moving On’ http://recode.net/2015/09/10/ellen-pao-speaks-i-am-now-moving-on/

After Loss, Pao Hopes Case Leveled the Playing Field http://www.wired.com/2015/03/ellen-pao-kleiner-verdict/

Pao’s Alleged Firing Could Hurt Kleiner Perkins in Retaliation Suit http://www.wired.com/2012/10/ellen-pao-kleiner-perkins/

Gender Bias Will Soon Shine a Harsh Light on Microsoft http://www.wired.com/2015/09/microsoft-gender-lawsuit/

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• Countering sex and...

Countering sex and gender bias in cardiovascular research requires more than equal recruitment and sex disaggregated analyses

• Related content
• Peer review
• Carolina Rau Steuernagel , researcher 1 ,
• Carolyn S P Lam , professor 2 ,
• Trisha Greenhalgh , professor 3
• 1 University of Oslo, Centre for Sustainable Healthcare Education, Oslo, Norway
• 2 National Heart Centre Singapore and Duke-National University of Singapore, Singapore
• 3 University of Oxford, Nuffield Department of Primary Care Health Sciences, Oxford, UK
• Correspondence to: C B Rau Steuernagel c.b.r.steuernagel{at}medisin.uio.no

Carolina Rau Steuernagel , Carolyn Lam , and Trish Greenhalgh argue for more attention to be given to social and economic factors to overcome implicit biases in research about women’s cardiovascular health

The US Multiple Risk Factor Intervention Trial in the 1970s screened 325 348 men and no women for risk of cardiovascular disease; 12 866 of these men were identified as high risk and offered prevention strategies. 1 Dozens of publications resulted, producing a robust evidence base on cardiovascular risk and prevention—in white men. 1 Tellingly, the trial’s acronym was “Mr Fit.”

This flagrant sex and ethnic bias was part of a wider pattern. The Physicians Health Study, which established the efficacy of aspirin for prevention of myocardial infarction, 2 and various cardiovascular prevention studies that ran till the mid-1990s were limited to white men. 3 4 Indeed, in the second half of the 20th century, women in childbearing years were routinely excluded from medical research trials on the grounds that their hormone cycles made study populations too heterogeneous, 5 and to avoid a repeat of the thalidomide tragedy in which an experimental drug proved teratogenic. 6 Yet cardiovascular disease, then as now, is the leading cause of death in women globally. 7

Multiple initiatives have helped to achieve sex balanced recruitment to trials. The US National Institutes of Health mandated the inclusion of women and people from ethnic minorities in government funded health research from 1994, 5 6 and in the UK the National Institute for Health and Care Research published guidance on representativeness of sex and gender in 2020. 4 Despite these measures and overall increased awareness, representation of women in cardiovascular trials remains significantly lower than that of men. 7 8 9 A cross specialty review of 20 000 trials showed that under-representation of women is worse in cardiovascular trials than in other adult specialties. 10 In 700 cardiovascular trials registered between 2000 and 2017, male participants outnumbered females by (on average) two to one, with clear under-representation of women relative to their prevalence of disease for all subtypes of cardiovascular disease except pulmonary hypertension. 11

The under-representation of women in cardiovascular research persists, distorting knowledge and leading to serious consequences for patient care and outcomes. We argue that under-representation results from interdependent sex and gender bias ( box 1 ) and propose solutions to counter the persistence of these imbalances.

Conceptual differences between variables of sex and gender and impact on health

Sex —A biological characteristic relating, for example, to differences in sex hormones, chromosomes, or different molecular expressions at cell level. Analysis by sex variables investigates physical and physiological differences between male, female, and intersex people in relation to disease presentation, pathophysiology, and responses to treatments

Gender —A social construct, relating to how people identify and how they may be treated differently as a result of social norms. Gender may affect access to healthcare, health seeking behaviour, interpretation of symptoms, and clinical decision making

Selection bias

Under-representation of women in cardiovascular research stems from both explicit and implicit biases in selection criteria. Women of reproductive age are often excluded by default from trials. This exclusion criterion was originally formulated to protect against potential teratogenic harms in early phase drug trials but has been broadly applied without justification. 12 Trial protocols may also incorporate implicit sex biased inclusion criteria such as age limits (women with cardiovascular disease are generally older than men), body size limits (women generally have lower body weight than men), and male defined thresholds for common cardiovascular indicators (eg, left ventricular ejection fraction, QRS duration) of severe disease. 12 13 14 Although ethnicity is known to affect cardiovascular risk (non-white women experience a higher proportion adverse pregnancy outcomes associated with increased cardiovascular risk than white women 15 ), this variable also remains overlooked. 16

These subtle but important biases show how any numerical finding, metric, or standard that purports to objectively measure a biomarker reflects the subjective assumptions and judgments behind its selection (for example, that a particular cut-off reflects an equivalent level of disease in both sexes). 5 17 Research protocols may also exclude female specific conditions that are known to increase the risk of cardiovascular disease (eg, polycystic ovary syndrome, gestational diabetes, hypertensive disorders of pregnancy, pregnancy loss) rather than seeking to study how these conditions affect cardiovascular risk. 12 13 18 19

Recruitment and retention bias

Even when women meet eligibility criteria for a trial, they are much less likely to be enrolled. 20 A randomised study of patient willingness to participate in cardiovascular trials showed that women had 15% lower willingness to participate than men, 21 potentially because of an increased perception of risk. Trials may present an element of uncertainty that women are more reluctant than men to accept. 22 Women may need more time to make a decision, seeking additional advice and opinions from friends or family. 23 In addition, healthcare staff may invite fewer women than men to participate in trials, and logistical barriers (such as transportation and number of follow-ups) may increase the trial burden for women, particularly for ethnic minorities, and affect their participation. 20 24 Recruitment of more women to clinical trials may therefore require new approaches to enrolment, such as increased diversity in the research team, greater community involvement, community recruitment, and expanding awareness of trials in social media platforms. 20

Interestingly, trials of heart failure led by women recruited and retained more female participants than those led by men. 12 Although the reasons for this are unclear, female leaders may spend more time building trust through the study protocol, consent process, and follow-up plan. 12 The systematic review also suggested that female representation is affected by trial location (North America, Europe, or Asia), recruitment from ambulatory settings, and type of intervention (drugs or devices). 12

Selection, recruitment, and retention bias mean that data representing white men may become the norm against which women’s health and disease are benchmarked. In the case of heart failure, for instance, underenrolment of women in trials relative to disease prevalence means that estimates from data on male participants unduly informs treatment practices and assumptions about the safety of interventions. 8 In the Systolic Blood Pressure Intervention Trial (Sprint), only 35% of participants in the intensive or standard arms were women, despite the planned enrolment target of 50%. 25 This study was terminated prematurely because of the benefit observed in the intensive treatment arm, but this did not take into account the low recruitment or event rates in women, or sex specific outcomes, and could therefore have missed potential unintended negative consequences of lowering systolic blood pressure in women.

Paucity of sex disaggregated data

Current knowledge about cardiovascular diseases in women is based on descriptive data on sex differences. 26 Sex specific studies are seen as central to understanding why cardiovascular risk and disease manifestations vary by sex. 26 In 2016, funding schemes for medical research in the US, Canada, and Europe introduced a policy requiring disaggregation of findings by sex. 17 This important policy has begun to generate sex specific clinical guidelines and protocols, 27 but it is far from fully implemented. A follow-up study of 10 years of preclinical studies in the US showed that although there was a substantial increase in the proportion of biological studies that included both sexes, there was no proportional translation into analysis and reporting by sex. 28 This tendency also seems to be observed in clinical trials. A systematic review of 224 cardiovascular trials published between 2000 and 2020, in which 28.2% of participants were female, found that only 33% of studies reported sex disaggregated subgroup analyses and 28% reported interactions between sex and treatment effect. No trial reported sex disaggregated screening, consent, or withdrawal rates, and only two trials reported sex disaggregated losses to follow-up. 8

Sex biases in research shape gender biases

The sex biases described above both reflect and reinforce gendered expectations that cardiovascular disease, and coronary heart disease in particular, is a “male” condition, or that women are protected and that men should be favoured in prevention and treatment. 9 Although oestrogen was long considered a protective factor against cardiovascular disease, largely based on animal studies, 29 a recent systematic review identified flaws in many of the key studies on which this conclusion depended, along with evidence suggesting publication bias. 29 Views that menstruating women are protected by oestrogen until menopause should be revised alongside our contemporary understandings of how hormonal mechanisms affect the natural course of cardiovascular disease. Indeed the prospective Women’s Health Initiative hormone therapy trials in more than 27 000 postmenopausal women have shown a complex relation of risks and benefits with postmenopausal hormone therapy and do not support the use of hormone replacement to prevent cardiovascular disease. 30 But it is difficult to disentangle the influence of explicit sex biases in research that mask biological diversity such as hormonal mechanisms from the impact of subtle, subconscious biases when it comes to how clinicians approach women with cardiovascular disease or risk factors. 26

Recent claims suggesting that sex-treatment interactions hold limited clinical relevance 31 imply that the observed disparities in cardiovascular outcomes by sex cannot be solely attributed to concealed biological differences. Evidence suggests that persistent inconsistencies in risk assessment and preventive therapy contribute to a rising epidemic of cardiovascular disease, particularly in younger women. 32 Women are less likely than men to be told that they are at risk of a cardiovascular event and to be counselled towards preventive behaviour modifications. 32 Although women with diabetes (for which guidelines recommend preventive use of statins to reduce cardiovascular risk) have a hazard ratio double that of men, women are less likely to receive statins. 32

Misrecognition of symptoms of heart disease is also associated with gender biases. 26 In an experimental study to measure gender variation in clinical decision making, in which physicians were presented with videotapes of patients presenting with cardiovascular symptoms, 31% of women received a mental health condition as the most certain diagnosis, compared with 16% of men. 33 A national representative survey in the US showed that women are more often advised to lose weight than to get their cardiac risk assessed. 32

Long held assumptions in cardiovascular research using men as the norm (hence, the default research participant) have been widely translated into practice as interpreting heart attacks in women as “atypical.” 9 26 Current guidelines encourage the use of the term “understudied,” 26 expressing the gaps in knowledge about how the presentation and experience of this condition differs because of both sex diversity (eg, in metabolism, hormones, and the autonomic nervous system) and gender differences (eg, in sociocultural patterns of symptoms, behaviour, and care). 32

Interdependence between sex and gender

Health is the outcome of social determinants that intersect in complex ways. For example, being female and black and poor may produce more and different disadvantage than any of these determinants alone. 34 Even when biological sex is incorporated as a variable in research, this will not cover the wider ethnic, social, cultural, and political complexities that interact with gender to affect women’s health outcomes (for example, that women overall have lower incomes, fewer years of education, and less access to a car or a computer). 32 35 Clinical guidelines and pathways that are informed by sex disaggregated data are not sufficient because findings disaggregated by sex alone will not reveal important differences within the broad categories “female” and “male” (such as by class or ethnicity). 35 For example, overall, men are more likely to smoke than women, but lower income women often smoke more than upper income men. 35

To take account of gender as well as sex, we need to collect data on social, economic, and behavioural issues that disproportionately affect one sex as well as undertaking sex disaggregated analyses. 36 Observed differences in health outcomes cannot be attributed solely to physio-pathological differences between men and women; they are also related to women and men being treated differently in healthcare and research. 37 38

Redressing entrenched inequities in cardiovascular care that stem from sexism and gender bias in research needs action at multiple levels, directed at multiple underlying causes and mediators and involving multiple actors, including clinicians, academics, government and other funding agencies, societies, and industry ( table 1 ). 20 Enhanced attention to both sex and gender throughout the whole research process, coupled with the inclusion of educational and training curriculums that emphasise the significance of sex and gender in cardiovascular disease, is imperative to develop tailored therapies and enhance cardiovascular health outcomes. 37

Measures that could help overcome sex biases in cardiovascular research

• View inline

Both sex and gender matter. If investigations and treatments are to be optimised for everyone, such diversity need to be carefully teased out, explored, and used to tailor assessments and interventions in sex and gender specific ways. Taking gender aspects into consideration in research will potentially explain why observed differences occur. 37 Until that occurs, clinical guidelines will continue to be biased towards men 27 39 and a proportion of women with cardiovascular disease will be denied effective therapies. 14

Key messages

Women have traditionally been under-represented in cardiovascular research studies, leading to biased guidelines, underdetection, underinvestigation, and undertreatment

Although some progress towards redressing this problem has been made, biases in cardiovascular research remain by sex and gender

Researchers should recruit both sexes equally, disaggregate data by sex, and be aware of gendered assumptions and expectations that can lead to hidden biases

Contributors and sources: CR is a physician with expertise in women’s health, and research experience with social science to study knowledge production and translation in health research. CL is a specialist in heart failure, has led several multinational global and regional clinical trials, and serves as a consultant in several advisory boards for cardiovascular disease. TG is a medical doctor with an interest in the social science of healthcare. CR and CL conceived the paper, CR prepared the initial draft, and TG and CL revised the initial draft. All authors provided conceptual input and edited the paper.

Competing interests: We have read and understood BMJ policy on declaration of interests and have no competing interests to declare.

Provenance and peer review: Not commissioned; externally peer reviewed.

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Assessing gender bias in machine translation: a case study with Google Translate

• Original Article
• Published: 27 March 2019
• Volume 32 , pages 6363–6381, ( 2020 )

Cite this article

• Marcelo O. R. Prates   ORCID: orcid.org/0000-0002-5576-7060 1 ,
• Pedro H. Avelar 1 &
• Luís C. Lamb 1  

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Recently there has been a growing concern in academia, industrial research laboratories and the mainstream commercial media about the phenomenon dubbed as machine bias , where trained statistical models—unbeknownst to their creators—grow to reflect controversial societal asymmetries, such as gender or racial bias. A significant number of Artificial Intelligence tools have recently been suggested to be harmfully biased toward some minority, with reports of racist criminal behavior predictors, Apple’s Iphone X failing to differentiate between two distinct Asian people and the now infamous case of Google photos’ mistakenly classifying black people as gorillas. Although a systematic study of such biases can be difficult, we believe that automated translation tools can be exploited through gender neutral languages to yield a window into the phenomenon of gender bias in AI. In this paper, we start with a comprehensive list of job positions from the U.S. Bureau of Labor Statistics (BLS) and used it in order to build sentences in constructions like “He/She is an Engineer” (where “Engineer” is replaced by the job position of interest) in 12 different gender neutral languages such as Hungarian, Chinese, Yoruba, and several others. We translate these sentences into English using the Google Translate API, and collect statistics about the frequency of female, male and gender neutral pronouns in the translated output. We then show that Google Translate exhibits a strong tendency toward male defaults, in particular for fields typically associated to unbalanced gender distribution or stereotypes such as STEM (Science, Technology, Engineering and Mathematics) jobs. We ran these statistics against BLS’ data for the frequency of female participation in each job position, in which we show that Google Translate fails to reproduce a real-world distribution of female workers. In summary, we provide experimental evidence that even if one does not expect in principle a 50:50 pronominal gender distribution, Google Translate yields male defaults much more frequently than what would be expected from demographic data alone. We believe that our study can shed further light on the phenomenon of machine bias and are hopeful that it will ignite a debate about the need to augment current statistical translation tools with debiasing techniques—which can already be found in the scientific literature.

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Acknowledgements

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001 and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).

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Prates, M.O.R., Avelar, P.H. & Lamb, L.C. Assessing gender bias in machine translation: a case study with Google Translate. Neural Comput & Applic 32 , 6363–6381 (2020). https://doi.org/10.1007/s00521-019-04144-6

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Gender and feminist considerations in artificial intelligence from a developing-world perspective, with India as a case study

• Shailendra Kumar   ORCID: orcid.org/0000-0002-7493-5496 1 &
• Sanghamitra Choudhury   ORCID: orcid.org/0000-0003-1417-1735 2 , 3 , 4 , 5 , 6  

Humanities and Social Sciences Communications volume  9 , Article number:  31 ( 2022 ) Cite this article

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• Complex networks
• Development studies
• Information systems and information technology
• Science, technology and society

This manuscript discusses the relationship between women, technology manifestation, and likely prospects in the developing world. Using India as a case study, the manuscript outlines how Artificial Intelligence (AI) and robotics affect women’s opportunities in developing countries. Women in developing countries, notably in South Asia, are perceived as doing domestic work and are underrepresented in high-level professions. They are disproportionately underemployed and face prejudice in the workplace. The purpose of this study is to determine if the introduction of AI would exacerbate the already precarious situation of women in the developing world or if it would serve as a liberating force. While studies on the impact of AI on women have been undertaken in developed countries, there has been less research in developing countries. This manuscript attempts to fill that need.

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Introduction.

Women in some South-Asian countries, like India, Pakistan, Bangladesh, and Afghanistan face significant hardships and problems, ranging from human trafficking to gender discrimination. Compared to their counterparts in developed countries, developing-world women encounter a biased atmosphere. Many South Asian countries have a patriarchal and male-dominated society, and their culture has a strong preference for male offspring (Kristof, 1993 ; Bhalotra et al., 2020 ; Oomman and Ganatra, 2002 ). These countries, particularly India, have experienced instances where technology has been utilized to create gender bias (Guilmoto, 2015 ). For example, there has been a great misuse of some of the techniques, of which sonography, or ultrasound , is one. The public misappropriated sonography , which was intended to determine the unborn’s health select the fetus’s gender, and perform an abortion if the fetus is female (Alkaabi et al., 2007 ; Akbulut-Yuksel and Rosenblum, 2012 ; Bowman-Smart et al., 2020 ). Many Indian states, particularly the northern states of India, have seen a significant drop in the sex ratio due to this erroneous use of technology. India’s unbalanced child sex ratio has rapidly deteriorated. In 1981, there were 962 females in the 0–6-year age group for every 1000 boys. In 1991, there were 945 girls, then 927 girls in 2001, and 918 girls at the time of the 2011 Census (Bose, 2011 ; Hu and Schlosser, 2012 ). In 1994, the Indian government passed the Pre-conception and Pre-Natal Diagnostic Techniques (Prohibition of Sex Selection) Act to halt this trend. The law made it unlawful for medical practitioners to divulge the sex of a fetus due to worries that ultrasound technology was being used to detect the sex of the unborn child and terminate the female fetus (Nidadavolu and Bracken, 2006 ; Ahankari et al., 2015 ). However, as the Indian Census data over the years demonstrates, the law did not operate as well as intended. According to public health campaigners, this is due to the Indian government’s failure to enforce the law effectively; sex determination and female feticide continue due to medical practitioners’ lack of oversight. Radiologists and gynecologists, on the other hand, argue that it’s because the law was misguided from the outset, holding the medical profession responsible for a societal problem (Tripathi, 2016 ).

In the realm of artificial intelligence, gender imbalance is a critical issue. Because of how AI systems are developed, gender bias in AI can be problematic. Algorithm developers may be unaware of their prejudices, and implicit biases and unknowingly pass their socially rooted gender prejudices onto robots. This is evident because the present trends in machine learning reinforce historical stereotypes of women, such as humility, mildness, and the need for protection. For instance, security robots are primarily male, but service and sex robots are primarily female. Another example is AI-driven risk analysis in the justice system. The algorithms may overlook the fact that women are less likely to re-offend than men, placing women at a disadvantage. Female gendering increases bots’ perceived humanity and the acceptability of AI. Consumers believe that female AI is more humane and more reliable and therefore more ready to meet users’ particular demands. Because the feminization of robots boosts their marketability, AI is attempting to humanize them by embedding feminist characteristics and striving for acceptability in a male-dominated robotic society. There’s a risk that machine learning technologies will wind up having biases encoded if women don’t make a significant contribution. Diverse teams made up of both men and women are not just better at recognizing skewed data, but they’re also more likely to spot issues that could have dire societal consequences. While women’s characteristics are highly valued in AI robots, protein-based Footnote 1 women’s jobs are in jeopardy. Presently, women hold only 22% of worldwide AI positions while men hold 78% (World Economic Forum Report, 2018 ). According to another study by wired.com, only 12% of machine learning researchers are women, which is a concerning ratio for a subject that is meant to transform society (Simonite, 2018 ). Because women make up such a small percentage of the technological workforce, technology may become the tangible incarnation of male power in the coming years. The situation in the developing world is worse, and hence a cautious approach is required to ensure that a male-dominated society in some of the developing world’s countries does not abuse AI’s power and use it to exacerbate the predicament of women who are already in a precarious situation.

This manuscript discusses the relationship between women, technology, manifestation, and probable prospects in the developing world. Taking India as a case study, the manuscript further focuses on how the ontology and epistemology perspectives used in the fields of AI, and robotics will affect the futures of women in developing countries. Women in the developing world, particularly in South Asia, are stereotyped as doing domestic work and have low representation in high-level positions. They are disproportionately underemployed and endure employment discrimination. The article will attempt to explore, whether the introduction of AI would exacerbate the already fragile position of women in South Asia or serve as a liberating force for them. While studies on the influence of AI on women have been conducted in industrialized countries, research in developing countries has been minimal. This manuscript will aim to bridge this gap.

The study tests the following hypothesis:

H01: The changing lifestyle, growing challenges, and increasing use of AI robots in daily life may not be a threat to the existing human relationship.

HA1: The changing lifestyle, growing challenges, and increasing use of AI robots in daily life may be a threat to the existing human relationship.

H02: There is no significant difference in the perception of females and males towards AI robots.

HA2: There is a significant difference in the perception of females and males towards AI robots.

H03: There is no major variation in the requirements and utilization of AI robots between men and women.

HA3: There is a considerable difference in the requirements and use of AI robots between men and women.

H04: When it comes to the gender of the robots, there is no substantial difference between male and female preferences.

HA4: When it comes to the gender of the robots, there is a substantial difference between male and female preferences.

The manuscript is divided into four sections. The first section is an introduction, followed by a literature review, methodology, results and discussion, and finally, a conclusion.

Literature review

AI’s basic assumption is that human intellect can be studied and simulated so that computers can be programmed to perform tasks that people can do (Guo, 2015 ). Alan Turing, the pioneer of AI, felt that to develop intelligent things like homo sapiens, humans ought to be considered as mechanical beings rather than as emotionally manifested super-beings so that they could be studied and replicated (Evers, 2005 ; Sanders, 2008 ). Rosalind Picard published “Affective Computing” in 1997, with the basic premise being that if we want smarter computers that interact with people more naturally, we must give them the ability to identify, interpret, and even express emotions. This approach went against popular belief, which held that pure logic was the highest type of AI (Venkatraman, 2020 ). Many human features have been transferred into non-human robots as a result of AI advancements, and expertise and knowledge will no longer be confined to only humans (Lloyd, 1985 ). Researchers like Lucy Suchman look at how agencies are now arranged at the human-machine interface and how they might be reimagined creatively and materially (Suchman, 2006 ). Weber believes that recent advancements in robotics and AI are going towards social robotics, as opposed to past achievements in robotics and AI, which can be attributed to fairly strict, law-oriented, conceding to adaptive human behavior towards machines (Weber, 2005 , p. 210). Weber goes on to say that social roboticists want to take advantage of the human predisposition to anthropomorphize machines and connect with them socially by structuring them to look like a woman, a child, or a pet (Weber, 2005 , p. 211). Reeves and Nass say humans communicate with artificial media, such as computers, in the same way, that they connect with other humans (Reeves and Naas, 1996 ). Studies further indicate that humans are increasingly relying on robots, and with the advancement of social artificially intelligent bots such as Alexa and Google Home, comme les companionship between comme les robots and humans is now becoming a reality (de Swarte et al., 2019 ; Odekerken-Schröder et al., 2020 ). It is believed that robots will not only get smarter over the next few decades, but they will also establish physical and emotional relationships with humans. This raises a fresh challenge about how people view robots intended for various types of closeness, both as friends and as possible competitors (Nordmo et al., 2020 ). According to Erika Hayasaki, artificial intelligence will be smarter than humans in the not-too-distant future. However, as technology advances, it may become increasingly racial, misogynistic, and inhospitable to women as it absorbs cultural norms from its designers and the internet (Hayasaki, 2017 ). The rapid advancement in robot and AI technology has highlighted some important problems with issues of gender bias (Bass, 2017 ; Leavy, 2018 ). There are apprehensions that algorithms will be able to target women specifically in the future (Caliskan et al., 2017 ). Given the increasing prominence of artificial intelligence in our communities, such attitudes risk leaving women stranded in many facets of life (UNESCO Report, 2020 ; Prives, 2018 ). Discrimination is no longer a purely human problem, as many decision-makers are aware that discriminating against someone based on an attribute such as sex is illegal and immoral. Therefore, they conceal their true intent behind an innocuous, constructed excuse (Santow, 2020 ). In the literature surrounding the discipline of Critical Algorithm Series, gender bias is a commonly debated topic (Pillinger, 2019 ). Donna Haraway published her famous essay titled, “A Cyborg Manifesto” in Socialist Review in 1985. In the essay, she criticized the traditional concepts of feminism as they mainly focus on identity politics. Haraway, inspires a new way of thinking about how to blur the lines between humans and machines and supports coalition-building through affinity (Pohl, 2018 ). She employs the notion of the cyborg to encourage feminists to think beyond traditional gender, feminism, and politics (Haraway, 1987 , 2006 ). She further claims that, with the help of technology, we may all promote hybrid identities, and people will forget about gender supremacy as they become more attached to their robotics (Haraway, 2008 ). To date, however, this has not been the case. In recent times, growing machine prejudice is a problem that has sparked great concern in academia, industry research laboratories, and the mainstream commercial media, where trained statistical models, unknown to their developers, have grown to reflect critical societal imbalances like gender or racial bias (Hutson, 2017 ; Hardesty, 2018 ; Nurock, 2020 ; Prates et al., 2020 ). While previous research indicates that gendered and lifelike robots are perceived as more sentient, the researchers of those studies primarily ignored the distinction between female and male bots (DiMaio, 2021 ). The study by Sylvie Borau et al. indicates that female artificial intelligence is preferred by customers because it is seen to have more good human attributes than male artificial intelligence, such as affection, understanding, and emotion (Borau et al., 2021 ). This is consistent with the literature, which suggests that male robots may appear intimidating in the home and that people trust female bots for in-home use (Carpenter, 2009 ; Niculescu et al., 2010 ). Another study indicates that when participants’ gender matched the gender of AI personal assistant Siri’s voice, participants exhibited more faith in the machine (Lee et al., 2021 ). Human–robot-interaction (HRI) researchers have undertaken various studies on gender impacts to determine if men or women are more inclined to prefer or dislike robots. According to research, males showed more positive attitudes toward interacting with social robots than females in general (Lin et al., 2012 ), and females had more negative attitudes regarding robot interactions than males in particular (Nomura and Kanda, 2003 ; Nomura et al., 2006 ). In another study, Nomura urged researchers to explore whether gendering robots for specific roles is truly required to foster human–robot interaction (Nomura, 2017 ). The investigation by R. A. Søraa demonstrates how gendering practices of humans influence mechanical species of robots, concluding that the more sapient a robot grows, the more gendered it may become (Søraa, 2017 ). “I am for more women in robotics, not for more female robots,” Martina Mara, director of the RoboPsychology R & D division at the Ars Electronica Futurelab, adds (Hieslmair, 2017 ). While there is a large body of work describing gender bias in AI robots in developed countries, little research has been done on the impact of AI robots on women in developing and undeveloped countries. This article will try to bridge the gaps in the studies.

Methodology

The overarching purpose of this exploratory project is to look at gender and feminist issues in artificial intelligence from a developing-world perspective. It also intends to depict how men and women in developing countries react to the prospect of having robot lovers, companions, and helpers in their everyday lives. A vignette experiment was conducted with 125 female and 100 male volunteers due to the lack of commercial availability of such robots. The survey was distributed online, which aided in the recruitment of volunteers. The vast majority of those who responded (76%) were university students from India. Because the study was conducted during the COVID-19 pandemic phase, the questionnaire was prepared in Google Form and distributed to participants via WhatsApp group and email. The participants ranged from 16 to 60 years old, with an average age of 27.25 (SD = 7.722) years. The vignette was created to portray a futuristic human existence as well as a variety of futuristic robots and their influence on people. The extracts from the vignette are: “At today’s science fair, Sam and Sophie, who are husband and wife, came across a variety of AI robots, including domestic robots, sex robots, doctor robots, nurse robots, engineer robots, personal assistant robots, and so on. This made them pleasantly surprised, and they were left to believe that in the future, AI robot technology will become so sophisticated that it will develop as an efficient alternative to protein-based humans. Back at home, Sophie utilizes Google Assistant and Alexa Assistant in the form of AI devices in the couple’s house to listen to music, cook food recipes, and entertain their children, while Sam uses them to get weather information, traffic information, book products online, set reminders, and so on. Mesmerized by the advancements in AI technology displayed at the science fair, Sam jokingly told Sophie that if there was a beautiful robot that could do household chores and give love and care to a partner, then the person would not need a marriage nor would he have to go through problems like break-up and divorce. Sophie disagreed, believing that the robot could not grasp or duplicate the person’s feelings and mood. Sam disagreed, claiming that a protein-based individual isn’t immune to these flaws either, because if that had been the case, human relationships would be devoid of misery, pain, violence, and breakups. Sophie thought that people need a companion but are unwilling to put up with human imperfections and that many people love the feminine traits inherent in AI robots but do not want to engage in a true relationship with real women.” After the respondents had finished reading the vignettes, they were handed the questionnaire and asked to fill it out. The questions were all delivered in English, with translation services available if necessary. Participation was entirely voluntary, and respondents were offered the option of remaining anonymous and not disclosing any further personal information such as their address, email address, or phone number. The participants gave their informed consent, and the participants’ personal information was kept private and confidential.

In this study, a varied group was subjected to demographic data sheets as well as a self-developed questionnaire. The people that have been surveyed are of different sexes, ages, educational levels, and marital statuses. The purposive (simple random) sampling technique was used to attain the objectives.

The research was conducted using a self-developed questionnaire. All the items on the scale were analyzed using IBM SPSS ® 23. Mean, standard deviation, total-item correlation, regression, and reliability analysis were performed on all the items. The questionnaire measured the items of AI using the following four scales: perspective, gender, requirements/use, and the threat of using AI. The alpha has been set to default 0.05 as a cut-off for significance.

Results and discussion

Table 1 shows a positive and significant intra-correlation between factors, such as perceptions towards AI robots, AI robot use and requirements, robot gender, and the threat from AI robots.

A regression study to identify threat factors with respect to AI robots is shown in Table 2 . The threat posed by AI robots is predicted by people’s perception of AI robots and the gender of AI robots. As a result, the hypothesis, that the changing lifestyle, growing challenges, and increasing use of AI robots in daily life may be a threat to the various existing human relationships is accepted. It could be inferred that people may be more motivated to live with AI robots due to changing lifestyles and increasing challenges and complications in human relationships (see Fig. 1 ). The majority of the respondents believe that greater use and reliance on AI robot technology will jeopardize the existence of protein-based people and lead to more prejudiced, discriminatory, and solitary societies. This is in support of the findings of the study, which show that people have an innate dread that robots will one day outwit them to the point that they will start exploiting humans (see Fig. 2 ). Moreover, the majority of respondents feel that AI may have a significant impact on gender balance in countries like India and that it may also affect gender balance in the subcontinent. This is in line with past concerns in India about the misuse of sonography technology (see Fig. 3 ).

Total no. of respondents: 225 (Female: 125, Male: 100).

Table 3 exhibits the results of the t -test. The results portray a significant difference between male and female respondents on the perception of AI robots. Therefore, the null hypothesis is rejected and the alternate hypothesis stating that there is a significant difference in the perception of females and males towards AI robots can be accepted. The t -test further indicates that there exists no significant difference between males and females on the requirements and use of AI robots, as no significant gender difference was found on the requirements and use of AI robots by both males and females. The majority of respondents believe that living with AI robots will become a reality soon (see Fig. 4 ) and that the AI robots’ ethnic and racial appearance may have a significant impact on consumers’ AI robot purchasing preferences (see Figs. 5 and 6 ). The respondents also advocated different ethical programming for the female and male robots (see Fig. 7 ). However, as far as the use of robots is concerned, it is evident that all other categories of robots have shown roughly equal demand from both males and females, except for sex and love robots, where the gender discrepancy is more than twice, with 24% of males and 8.8% of females indicating a need for sex and love robots (see Fig. 8 ). Assistant robots, teaching robots, entertainment robots, robots that do household tasks and errands, and robots that offer care were among the most popular. Females showed the least interest in sex and love robots, while males showed the least interest in companion and friendship robots. Overall, 15.56% of respondents said they were open to having sex and love robots. This demonstrates the general concern and reluctance to engage in sexual or romantic relationships with AI computers. Females, on the other hand, appear to be more hesitant and averse to engaging in intimacy with robots than males. The key reasons for this are sentiments of envy and insecurity. The study’s findings also show that males in developing countries have a more favorable attitude toward sex robots than females. This confirms the existence of gender differences in emotional intimacy and sex preferences (Johnson, 2004 ). Sex robots have the potential to reduce or eliminate prostitution, human trafficking, and sex tourism for women (Yeoman and Mars, 2012 ) in developing countries. According to data from the Indian government’s National Crime Record Bureau (NCRB), 95% of trafficked people in India are forced into prostitution (Divya, 2020 ; Munshi, 2020 ).

Total number of respondents:225 (Female: 125, Male: 100).

The t -test further indicates that there exists no significant difference between male and female respondents as far as the gender of the robots is concerned. However, the analysis of mean figures indicates that the majority of respondents believe that gender has a role in AI robot development and production (see Fig. 9 ), and AI will have a greater impact on both men and women (see Fig. 10 ), but when asked which gender AI will have the greatest impact on, both genders answer that AI will have the greatest impact on their gender (see Fig. 11 ). While most people disagreed with the premise that female robots are seen by them as more humane (see Fig. 12 ), they did agree that female robots are regarded differently by them (see Fig. 13 ). They further agreed that feminizing robots improves their marketability and acceptance (see Fig. 14 ), and that corporations are using feminity to humanize non-human things like AI robots (see Fig. 15 ). The responses also indicate that a majority of the respondents (55.11%) believe that the use of feminine features in robots increases the risk of females being stereotyped (see Fig. 16 ).

The gendering of the robots in AI is problematic and does not always lead to the desired improved acceptability, as gender makes no difference in terms of robot functionality and performance. The study contradicts the widely held belief that women in developing nations such as India are wary about living with AI robots in the near future. It also shows that both men and women feel AI will have a stronger impact on both males and females. The majority of respondents dissented that female robots are considered more commiserate than male robots, but they accede to the fact that female robots are perceived differently, even when they are robots. The majority of respondents feel that AI will have a significant impact on gender balance in nations like India just like the sonography technique that was misused for doing gender selection. However, they are in general agreement with the fact that people may be motivated to live with AI robots due to changing lifestyles and increasing challenges and complications in human relationships. Due to the rising cost of maintaining a protein-based lifestyle, humans may turn to robots to eschew the issues that come with it. The study also found people in developing countries have an innate dread that robots will one day outwit them.

Data availability

The data underpinning the study includes a dataset that has been deposited in the Harvard Dataverse repository. Please refer to Kumar, Shailendra; Choudhury, Sanghamitra, 2022, “Gender and Feminist Considerations in Artificial Intelligence from a Developing-World Perspective, with India as a Case Study”, https://doi.org/10.7910/DVN/0T3P1E , Harvard Dataverse, V1, UNF:6:oecwn9YFMHRv369S0mDW5w== [fileUNF].

The term “protein-based” has been used in the manuscript as a synonym for “humans”, with the understanding that, except for water and fat, the human body is virtually entirely made up of protein. Muscles, bones, organs, skin, and nails are all made up of protein. Muscles are made up of around 80% protein, excluding water.

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Acknowledgements

The authors are grateful to everyone who volunteered to take part in this study and helped to create this body of knowledge. Professor Lashiram Laddu Singh, Vice-Chancellor, Bodoland University, India, is to be thanked for his unwavering support and direction throughout the study’s duration. Thank you to Bishal Bhuyan and Kinnori Kashyap of Sikkim University, India for their help with data testing using SPSS software.

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Conceptualization, SK and SC; methodology, SK and SC; software, SK; validation, SK and SC; formal analysis, SC; investigation, SK; resources, SC; data curation, SK; writing—original draft preparation, SK; writing—review and editing, SK and SC. All authors have read and agreed to the published version of the manuscript.

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Ethical approval was obtained from Bodoland University’s Authorities and Research Ethics Committee. This study was conducted in compliance with the Charter of Fundamental Rights of the EU (2010/C 83/02), the European Union European Charter for Researchers, and the General Data Protection Regulation (GDPR).

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Informed consent was obtained from all participants and/or their legal guardians. Every participant gave their consent before questionnaires were administered or interviews were conducted. Essentially, the online survey would get open only when the participant read, understood, and agreed with what participation in the study would entail, and each one had the option to discontinue their participation at any time.

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Kumar, S., Choudhury, S. Gender and feminist considerations in artificial intelligence from a developing-world perspective, with India as a case study. Humanit Soc Sci Commun 9 , 31 (2022). https://doi.org/10.1057/s41599-022-01043-5

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The gender gap is one of the most contentious diversity issues in the world of work. These are just a few of the companies who have taken action to try and correct the issue.

It is no secret that the tech industry has struggled with a diversity problem. The problem spans all levels of business, from how female and minority employees are compensated, to their representation at all employee levels. However, the promise of a turning point is on the horizon as more companies start to pay attention and address the issue.

Research has continually shown that diverse teams outperform non-diverse teams financially. Knowing this, HR professionals at top firms have started to prioritise diversity in recruitment above all else.

In April 2018, the first slew of gender pay gap data was released in the UK following a law that was passed mandating large enterprises to do so. Prior to this, Iceland brought in legislation requiring organisations to provide proof that men and women are being compensated fairly, or face daily fines .

Many companies have taken steps to address gender gap issues. In a few cases, such as with tech giant Google , the efforts were found to be lacking. Yet in other cases, changes made have led to significant progress in addressing gender disparity. Here are some of the companies who have recently made inroads in this area, and how they did it.

Duolingo CEO and co-founder Luis von Ahn took to Twitter in October to highlight how the company had achieved a 50:50 ratio for new software engineer hires. Grimly, yet perhaps unsurprisingly, the response the company received was dominated by, in Von Ahn’s words, “men angrily arguing discrimination, and that we should hire the best people instead”.

Duolingo just tweeted about how we achieved a 50% female ratio of new engineering college graduate hires. We're very proud of this. I'm disappointed that the top comments were all from men angrily arguing discrimination, and that we should hire the best people instead. Idiots. https://t.co/WHjq2WnKzH — Luis von Ahn (@LuisvonAhn) October 11, 2018

The co-founder took great issue with this idea that promoting diversity somehow compromises quality. According to Von Ahn, all female hires had “either perfect or near-perfect GPAs from the best universities in the world, with stellar recommendations, and aced our very thorough interview process”.

Duolingo achieved its 50:50 ratio through a multipronged, data-driven approach. It only recruited from colleges with more than the US national average (18pc) of women enrolled in their computer science programmes, such as Duke, Cornell, Harvard and MIT. It then reached out to the women groups at each school and went along to any network events it held. It sponsored the 2017 Grace Hopper Conference and had all its female engineers attend. Finally, Duolingo says it put all its interviewers through unconscious bias training.

Duolingo has expressed a continued commitment to promoting diversity and gender parity in the workplace through both internal and external action.

Since Salesforce started examining its pay gap in 2016, it has shelled out $6m in order to correct compensation imbalances.

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This action aligns with promises that Salesforce CEO Marc Benioff made in 2015 in an interview with HuffPost. “My job is to make sure that women are treated 100pc equally at Salesforce in pay, opportunity and advancement,” Benioff said, noting that while he did not know what the gender pay gap was at the time, he was determined to find out and act accordingly.

Salesforce committed to undertaking regular pay audits, reflecting the fact that pay equity is, as executive VP of global employee success Cindy Robbins  put it , “a moving target”.

In March 2018, Bloomberg editor in chief John Micklethwait announced a new staff policy regarding outside speaking engagement. So as to promote gender equality both within the newsroom and outside it, it is now a requirement that at least one woman is on any panel in order for a Bloomberg journalist to participate. “At the risk of stating the obvious, the woman could be you,” Micklethwait noted.

If this condition is not met, journalists will be required to decline, though there seems to be an appeals system in place if a journalist feels their participation on an all-male panel is necessary. “But I think this is a standard that we should be able to uphold on the vast majority of occasion,” Micklethwait concluded.

At cloud-based HR and payroll software company Gusto, the journey to gender parity began when software engineer Julia Lee asked Gusto co-founder and chief technology officer Edward Kim for a meeting. In it, she flagged that she was the only woman on the engineering team and disclosed her previous experiences of being dismissed due to her gender. Kim was receptive, and made a point to examine the gender breakdowns of other tech companies.  

The results were dismal to say the least, so Kim met with Gusto’s HR team to come up with a strategy to address the issue. First, it elected to move away from using ‘masculine’ phrases such as “ninja rockstar coder” in its job ads. For the first six months of 2018, it focused solely on recruiting female engineers, though made a point to equally consider any men who approached the company so it would not breach anti-discrimination laws.

Like Duolingo, it sent representatives to the Grace Hopper conference. Now, Gusto reports that 51pc of its staff are women and more than 24pc of its engineers are women.

It also submitted to gender pay auditing by human resources firm Mercer, which found no disparity. It offers 16 weeks’ paid leave complete with generous grocery and housecleaning benefits for a primary parent.

Nike has had a year peppered with controversy in the world of gender, culminating when four women hit the sportswear company with a lawsuit over alleged discrimination. The women maintain that Nike violated US equal pay laws and fostered a work environment that allowed for sexual harassment, The Guardian reported in August of this year.

Prior to the suit being filed, Nike responded to the issues raised by ousting a number of high-profile executives in what was termed a “ harassment reckoning ”. A month before the suit was filed, Nike HR chief Monique Matheson admitted in a staff memo obtained by The Wall Street Journal that the company had failed women and that it wants to “to create a culture of true inclusion” and that, in order to do this, it needs to “improve representation of women and people of colour”. That same month, the company revealed that it planned to adjust the pay of 7,000 of its employees after an internal compensation review in order to address pay disparities.

Nike is arguably in the more nascent stages of dealing with its issues. These steps are more about putting out fires than they are about instituting structural change, but it’s an excellent start from the footwear giant.

Related: software engineers , Salesforce , diversity , equality

Eva Short was a journalist at Silicon Republic, specialising in the areas of tech, data privacy, business, cybersecurity, AI, automation and future of work, among others.

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A Decade of Stagnation: New UNDP data shows gender biases remain entrenched

Lack of progress in the Gender Social Norms Index parallels human rights violations and is socially wasteful

June 12, 2023

Ameni Kharroubi from Tunisia, Arab Youth Leader at the UN Economic and Social Council (ECOSOC) Youth Forum in 2019.

New York - The latest Gender Social Norms Index (GSNI) report has revealed no improvement in biases against women in a decade, with almost 9 out of 10 men and women worldwide still holding such biases today. Half of people worldwide still believe men make better political leaders than women, and more than 40 percent believe men make better business executives than women. A staggering 25 percent of people believe it is justified for a man to beat his wife, according to the new GSNI report launched today by the United Nations Development Programme (UNDP), reflecting the latest data from the World Values Survey.

The report argues that these biases drive hurdles faced by women, manifested in a dismantling of women’s rights in many parts of the world with movements against gender equality gaining traction and, in some countries, a surge of human rights violations. Biases are also reflected in the severe underrepresentation of women in leadership. On average, the share of women as heads of state or heads of government has remained around 10 percent since 1995 and in the labour market women occupy less than a third of managerial positions. The report also sheds light on a broken link between women’s progress in education and economic empowerment. Women are more skilled and educated than ever before, yet even in the 59 countries where women are now more educated than men, the average gender income gap remains a staggering 39 percent in favour of men.

“Social norms that impair women’s rights are also detrimental to society more broadly, dampening the expansion of human development. In fact, lack of progress on gender social norms is unfolding against a human development crisis: the global Human Development Index (HDI) declined in 2020 for the first time on record—and again the following year. Everyone stands to gain from ensuring freedom and agency for women,” said Pedro Conceição, head of UNDP’s Human Development Report Office.

The report emphasizes that governments have a crucial role in shifting gender social norms. For instance, parental leave policies have changed perceptions around care work responsibilities, and labor market reforms led to a change in beliefs around the employment of women.

“An important place to start is recognizing the economic value of unpaid care work. This can be a very effective way of challenging gender norms around how care work is viewed. In countries with the highest levels of gender biases against women, it is estimated that women spend over six times as much time as men on unpaid care work,” said Raquel Lagunas, Director of UNDP’s Gender Team. 

The report emphasizes that despite the continued prevalence of bias against women, the data shows change can happen. An increase in the share of people with no bias in any indicator was evident in 27 of the 38 countries surveyed. The report authors emphasize that to drive change towards greater gender equality, the focus needs to be on expanding human development through investment, insurance, and innovation. 

This includes investing in laws and policy measures that promote women’s equality in political participation, scaling up insurance mechanisms, such as strengthening social protection and care systems, and encouraging innovative interventions that could be particularly effective in challenging harmful social norms, patriarchal attitudes, and gender stereotypes. For example, combatting online hate speech and gender disinformation can help to shift pervasive gender norms towards greater acceptance and equality.

In addition, the report recommends directly addressing social norms through education to change people’s views, policies and legal changes that recognize the rights of women in all spheres of life, and more representation of women in decision-making and political processes.

Access the report at:  https://hdr.undp.org/content/2023-gender-social-norms-index-gsni

About the United Nations Development Programme (UNDP)  

UNDP is the leading United Nations organization fighting to end the injustice of poverty, inequality, and climate change. Working with our broad network of experts and partners in 170 countries and territories, we help nations to build integrated, lasting solutions for people and planet.  

About the Gender Social Norms Index:   

The Gender Social Norms Index captures how social beliefs can obstruct gender equality in multiple dimensions— political, educational, economic, and physical integrity. It is constructed based on responses to seven questions from the World Values Survey, which are used to create seven indicators using data from 80 countries and territories, covering 85% of the global population. This report presents an update of the GSNI since it was first calculated in 2019 (with data up to 2010-2014) and includes the most recent data for the period 2017-2022.  

Contact Information:  

Victor Garrido Delgado.  [email protected] . +1 917 995 1687

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'The evidence was disappointingly poor': The full interview with Dr. Hilary Cass

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Listen: Our full hour on the 'Cass Review' and gender-affirming care for youth.

British pediatrician Dr. Hilary Cass led a highly anticipated independent scientific review of gender health services for children in England, commissioned by the National Health Service.

Now popularly known as the ' Cass Review, ' it concludes for most young people, "a medical pathway will not be the best way to manage their gender-related distress.”

In this podcast exclusive, she gives On Point her first broadcast interview in the U.S.

Hilary Cass , pediatrician. Led the independent scientific review of gender health services for children in England, commissioned by Britain’s National Health Service. Former president of the Royal Society of Pediatrics and Child Health.

Statements on the 'Cass Review' and gender-affirming care

Statement from the american academy of pediatrics, statement from the endocrine society, transcript: hilary cass extended interview.

HILARY CASS: The quality was disappointingly poor, and there's a number of reasons for that. One of the significant reasons is that they just didn't follow up for long enough, particularly for young people who were taking masculinizing and feminizing hormones. Because it's not enough to just follow up for a couple of years.

You really want to know how people are doing in the longer term, and if they're thriving into adulthood. So that was one problem. Another problem is that many of the studies didn't take account of the fact that this is a really, what we call heterogeneous, so a mixed population of young people who were very different from each other.

And that population has changed in recent years, from predominantly birth registered boys presenting quite early, to predominantly birth registered girls presenting in the teenage years. Now, also, they have much greater complexity in their presentations, within that group are young people with autism, there are young people who may have other complex mental health issues.

And for each of those young people, you need to think about how all of those factors are going to impact on how well they do. And so you can't take the results of how somebody does if they are presenting as a child and have had consistent long-term gender incongruence from say when they were four or five.

They may not have the same response to medication as somebody who is presenting considerably later. And I think the other thing to say is that young people present, in many different ways, in how they present their gender identity. So the commonest group now, or the most rapidly growing group, rather, is young people who see themselves as non-binary .

And we have even less research on what the right approach is for those young people. So you can't put all of these young people into the same treatment group and say they're all going to respond in exactly the same way to this kind of approach.

MEGHNA CHAKRABARTI: So Dr. Cass, over the past 10 years, there's been a dramatic change in who's seeking care for their gender dysphoria. As you talked about, it's now many adolescent girls . Similarly, it seems that there has been a change in the understood definition of gender-affirming care from a decade or two ago. Can you talk about that a little bit?

CASS: Yes. So there has been a real swing to seeing gender-affirming care as being pretty much synonymous with medical care.

And that certainly doesn't have to be the case. Certainly, young adults have said to us, there are many more ways of being trans than just binary medical treatments. Conversely, it's really worth saying that just giving hormones without supporting people is not helpful. And an adult trans person said to me the other day, "If you just get the hormones, that does not make years of dysphoria go away, and you need some therapeutic support, as well."

CHAKRABARTI: Okay. More specifically, in the systematic review of studies relating to the use of puberty blockers, we should say that puberty blockers do have quite a well-established evidence base for use in some situations, right? For example, children with precocious puberty. Or there's also some adult cases where puberty blockers can be used, right?

So they are an accepted treatment for certain things.

CASS: Absolutely right. Yes. So, in the UK, they are what's called licensed in children, if you have precocious puberty. And the difference with those children is that they have hormones that are abnormally high at too early a stage, and that's what puts them into very early puberty.

And there's been extensive studies of using puberty blockers just to stop that very early puberty. And then when they restart their puberty at a later point, all the long-term studies have been very reassuring, and that's why they're licensed for that group. It's a very different thing to take a young person whose hormones are going through the normal increases that you expect to see in puberty and pausing that.

Because during puberty, all sorts of things are going on. Your brain is developing very rapidly. You're developing what's called your executive functioning, which is how you do some complex problem solving, complex judgment abilities. And you're also developing your sexuality and developing your identity.

And we just don't know what happens if you put brakes on all of that.

CHAKRABARTI: Okay. Specifically, in the review report , there's a discussion that there are claims, actually from quite well-respected bodies, including here in the United States, that providing puberty blockers as a form of treatment and care for gender questioning youth, they're prescribed as treatment, because they can alleviate gender dysphoria, they can improve mental health of young people who are genuinely suffering.

Did the systematic evidence find an evidence base for those goals or aims?

CASS: Okay, so that's a really important question, and we have to go back to how the thinking started about use of puberty blockers. As this started in the Netherlands, and a consultant who'd worked in adult gender services was seeing poor outcomes in some of her patients.

And she felt that the reason for that is that they weren't managing to pass in adult life. And when she moved to working in children's services, she reasoned that if you could stop puberty before you developed irreversible features of male puberty, dropping your voice, growing facial hair, that might help you pass in later life. And that would give you better psychological outcome.

So that was the first part of the thinking. And she had a second key thought that if you could pause puberty, it would just buy young people more time to think and to work out who they were, understand their identity. So those are the two things that she originally thought would be advantages of this treatment.

And then the Dutch went on to look at other outcomes from treating their first cohort. And as you say, the particular things they wanted to look at was, does this improve mental health, reduce distress, and also does it improve body image? Does it reduce the dysphoria? And the Dutch found that there were some improvements in mental health of those young people, but it didn't affect the dysphoria.

So in the UK, we attempted to reproduce that, using exactly the same approaches as the Dutch. And disappointingly, the team did not find improvements in mental health. In fact, some young people got worse, some got better, some got worse, and some made no changes. And that's the sort of result you might expect from a treatment that's not particularly effective for those outcomes.

It's really important to say that there may be a group of young people who do have early gender incongruence for whom this might be the right treatment, particularly that group of birth registered boys who will develop irreversible changes of male puberty. And so we in the UK have not said we're not going to do this at all, but we've said that we need to do this under a proper research protocol, to understand who might benefit.

But just to go back to the systematic reviews, the other studies that the team looked at, none of them really effectively reproduced the Dutch results of seeing robust improvements in mental health.

CHAKRABARTI: So to be clear, the report states, quote, "that the University of York concluded ," and that's the group that did the review.

CASS: That's right.

CHAKRABARTI: "That there is insufficient or inconsistent evidence about the effects of puberty suppression on psychological or psychosocial health."

CASS: Correct.

CHAKRABARTI: And as you said, that doesn't mean it doesn't work for some young people, but just so that, again, people hearing this can understand, that just means that no one can really affirmatively claim that we know for sure it will help.

CASS: Yes. Yes. And we also have to think about which young people have been receiving puberty blockers. Because certainly in the UK, as time has gone on, the young people who were most likely to receive puberty blockers are most commonly aged around 15. And By 15, obviously you've gone through most of puberty.

So instead of really thinking, okay, how are we going to manage the distress that these young people are feeling, whilst they're making a decision about, in the long term, whether they go down a medical pathway, somehow, we've got locked into puberty blockers as the totemic treatment that young people feel. That if they don't get on that pathway, if they don't get onto puberty blockers, they're not going to get onto a medical pathway.

But actually, if you stop and think about it, there are many different ways in which we can manage distress and anxiety in a 15-year-old that don't involve puberty blockers. And yet we've somehow stopped short of trying those, just because puberty blockers have become so widely believed to be effective.

CHAKRABARTI: This is a really important point that's been brought up by the Cass Review. About did the focus on trying to provide medical forms of therapy, perhaps overshadow other forms of care. But so I want to read to you, this is from 2022, and this is from the United States Department of Health and Human Services Office of Population Affairs, and they stated in 2022 , that quote, "Research demonstrates that gender-affirming care improves the mental health and overall well-being of gender diverse children and adolescents, because gender-affirming care encompasses many facets of health care needs and support. It has been shown to increase positive outcomes for transgender and non-binary children and adolescents." End quote.

Now I should say that they're speaking about gender-affirming care overall and not just exclusively medical treatments . But there's a gap there though between what seems to be the conclusions of the Cass Review versus that statement, which is not uncommon from the United States.

CASS: One of the things that young adults said to us, we spoke to young adults directly through the Review, and we also had some qualitative research, so some researchers talking to young adults, as well. And one of the things that they said is, I wish I'd known when I was younger that there were more ways of being trans or expressing my identity than just a binary medical pathway. And it may be that they're gender fluid.

It may be that they're nonbinary. It may be they're binary trans, but haven't medically transitioned, and equally it may be that they have gone down a medical transition path. But I think when people are younger, they often have only understood one or two options. And there's a whole range of options that are open to them. And so a lot of what the focus of our review has been on is saying what do we do to help these young people to thrive, and how do we give them the widest range of options that also don't foreclose for them.

CHAKRABARTI: I just want to recap. So that the systematic review found that there's insufficient evidence or inconclusive evidence about the effect of puberty blockers on mental and psychosocial health or in the alleviation of gender dysphoria. There's also the question of, there have been competing claims about whether puberty blockers have negative impact on a young person's bone health?

CASS: Again, those results were inconclusive, and we need to follow people up for much, much longer. I think one thing is important to say about the physical side effects of treatment, whether it's on bone health, or whether there may be long term cancer risks or any of those things.

And that is that for somebody who is going to go on and have an enduring trans identity, to some degree, the physical costs of treatment are almost a very small, are outweighed by the fact that there is no other way for them to live a life that manages that dysphoria that they've experienced. So the tricky thing for children and young people is not knowing which young people are going to go on and have an enduring trans identity. So I think you have to weigh those physical side effects with that in mind.

CHAKRABARTI: Okay, so you've said several times that it's tricky, if not impossible, to know which young people will go on to have an enduring trans identity. But the review also finds that the vast majority of young people who did begin puberty suppression went on to having cross sex hormones treatment. From some perspectives, that might show the success of the puberty blockers, that the children who identified as trans and then began puberty suppression, did so correctly, because then the next step was cross sex hormones.

CASS: Yeah, and that's one of the really tricky questions to understand. Because we need to view this in the broader context of what's happening to adolescents and adolescent girls in particular, across most English speaking, most of the English-speaking world. And they do have higher rates of anxiety, of depression, of self-harm, of suicidal ideation, of distress about body image. But if in the early part of your puberty, from those multiple reasons, you feel a level of distress and discomfort with your body and your identity and yourself, and you feel socially isolated and you're not meeting what's deemed to be social norms, and you then go onto puberty blockers.

Then you go through an extended period where you haven't got the typical hormone surges that might be part of working out your sexual identity, your personal identity, and so on. And then you go on to Testosterone, which is a powerful hormone, and which will give you a strong libido and start to masculinize you.

That may be absolutely the right decision, but conversely, you have very little experience of your own puberty. And probably very little basis on which you might change your mind, because you feel good on your testosterone. We have absolutely no way of knowing whether we have changed the trajectory for those young people, it's a huge unknown.

And so the more we can let young people go through their typical puberty, and work out their identity and leave their options open, as long as possible, the more likely it is that they will make the best possible decision.

CHAKRABARTI: So Dr. Cass, one thing that the review notes very clearly at the top, which is true both in the UK and elsewhere around the world, including the United States, is the rapid rise, and actually the exponential rise in the number of young people, adolescents in particular, seeking treatment for gender dysphoria.

In fact, you have a chart here that shows that around 2013, 2014, every year, essentially, the numbers spike up higher, and it's many more adolescent girls. What do you think, or what did the review seem to find in terms of what may be driving that rapid rise?

CASS: That's a really good question.

So we looked at what we understand about the biology, but obviously biology hasn't changed suddenly in the last 10 years. So then we tried to look at, what has changed? And one is the overall mental health of teenage girls, in particular, although boys, to some degree. Part of this is something to do with the well-being of girls, and that may also be driven by social media, by early exposure to pornography, and a whole series of other factors that are happening for girls.

It's a tough time to grow up. But secondly, a much more fluid approach to how young people see gender. They see gender much more flexibly than, say, my generation did. So for some young people, gender becomes the main anxiety for them and the way in which they focus their distress. And just as an example, a colleague of mine described a not infrequent sequence of events, which is a young person comes to clinic, a birth registered female, who's very distressed by her breasts, is identifying as male. And the first thing she may do for that young person is put them on the pill to stop their periods.

That's a much more straightforward intervention than puberty blockers. If she's binding her breasts, it's really important that she does it safely. So the nurse in the clinic will show her how to do that safely. And then often by the next visit, that young person is less anxious. They may still be choosing to identify as non-binary or using he/him pronouns, but the heat has gone out of the gender distress, and they're then able to talk about other issues.

And over time, they may go on to have a trans identity, or they may --

CHAKRABARTI: Is that in conflict with what the American Academy of Pediatrics has said, as recently as last year? They said that when a child declares their gender, quote, "We operate under the assumption that what they're telling us is their truth, and that the child's sense of reality and feeling of who they are is the navigational beacon to orient treatment around."

CASS: What's different about children and adolescents is that they are evolving and developing and how a young person feels at any point in their life is real. It's as real as it is for any adult, but I think the important thing is that young people are in a developing state, and how you feel at seven and ten and 20 may be quite different.

So people are developing, and the more they can keep their options open, the better it is, to do that if it's possible.

CHAKRABARTI: Is that why the review recommends that children not, adolescents not go on a medicalized pathway because of the mercurial or the evolving nature of that sense of self until later in life?

CASS: Yeah. So brains are developing until we are into our twenties. Now, that doesn't mean that nobody should go on hormones under the age of mid-twenties, it's that's an individual choice. And our reviews remit only went up to 18. I think all we can recommend is caution and keeping options open.

It's probably worth saying that for birth registered females, the male hormones work fast, and there are significant irreversible effects in terms of dropping your voice, developing facial hair and other effects. And so within a few months, you do have significant irreversible effects. Whereas for birth registered boys, estrogen takes longer to take effect, and the effects are easier to reverse.

And for any one person, it's just a careful decision about balancing, whether you have arrived at your final destination in terms of understanding your identity, versus keeping those options open. And that's a really personal decision that you have to take with your medical practitioner, with the best understanding that we can give young people about the risks versus the benefits.

CHAKRABARTI: So to get back to what was published in the now known as Cass Review about cross sex hormones, again, because I'm very, I'm quite focused on understanding the evidence base, right? Or lack thereof.

CASS: Sure.

CHAKRABARTI: So regarding cross sex hormones, the systematic review authors said there is a lack of high-quality research assessing the actual outcomes of cross sex hormones.

CASS: Yes, because following up for one year, or two years or three years tells you very little. We need to follow up for much longer than a year or two to know if you continue to thrive on those hormones in the longer term. And we also need to know, particularly from young adults, are those young people in relationships?

Are they getting out of the house? Are they in employment? Do they have a satisfactory sex life? What are the things that matter to them? And are they achieving those things?

CHAKRABARTI: So once again, the answer is, as far as the review goes, we don't know. There's insufficient evidence or poor-quality, studies which aren't enough to make informed guidelines for families and practitioners.

Been quite a lot of misinformation that we discarded anything that wasn't a case-controlled study. We didn't set the bar that high. We were very happy with some good quality cohort studies, i.e. that's just where you follow up, and look at what happens to that group compared to another appropriate group.

But there were very few good quality cohort studies, and the problem is, as we said, that they didn't follow up for long enough.

CHAKRABARTI: Okay, so there's another aspect of the report in the evidence that your team examined that is very important for us to talk about. And it again relates to mental health, because by the time young people are seeking out help for gender dysphoria, they are quite distressed, right?

And as the report says, it is well established that children and young people with gender dysphoria are at increased risk of suicide. But then the report adds this, " But suicide risk appears to be comparable to other young people with a similar range of mental health and psychosocial challenges." So first of all, what's the evidence for that and why is that important to understand?

CASS: The most crucial thing we need to know is how do we address that suicide risk? And how do we know if this is down to their gender-related distress, and identifying as trans? Or is it because they also have an eating disorder, or they're depressed or they're isolated, perhaps because they're being discriminated against on the basis of sexuality, or a whole raft of other issues.

And because a majority of these young people have all of these issues, then what you need to do is compare to what the population rates are of suicidality in young people who have all of those other issues. But are not gender questioning. And that's where you find that the rates are fairly comparable.

So we can't say that it is the gender-questioning or the gender incongruence that's giving you additional suicide risk. So that's the first part. And so the second part is, does the gender-affirming treatment pathway reduce that suicidality, and thankfully, suicides are still very rare in young people. Although they're more common than we would wish, but they're not frequent events.

So it can be hard to make sense of the data, but such data as we have shows that people do commit suicide, both after they've had gender-affirming treatment, and before they've had gender-affirming treatment. And we can't detect a difference in the suicide rates before and after treatment.

CHAKRABARTI: So the systematic review then though really went, combed over all of the studies essentially that are cited when people say that gender-affirming treatment helps save lives.

I'm not, that's not an overstatement on my part because Admiral Rachel Levine, who's the Assistant Secretary for Health and Human Services in the United States, in fact, has said that gender-affirming care is quote, quite literally suicide prevention care.

So I'm sure you've heard similar things in the UK, but the review concluded that in a majority of studies that looked at a reduction in suicidality with gender-affirming treatment, found that there was, the studies report that there was a reduction. But there were problems with those studies in terms of they didn't control for the presence of those psychiatric comorbidities that you talked about. And then there was another study that showed that suicidality and self-harm decreased. But out of the 109 eligible participants, only 11 of them had actually completed the questionnaire on suicidality and self-harm.

CASS: Yeah, this is one of the things which makes this so difficult. So if you look at the abstract of that particular paper, it said there was a tendency for suicidality to reduce. Or, some words to that effect, but if such a small percentage actually completed the questionnaire, what does that mean about all those that didn't complete it?

And that is, that's just what dogs this research. And the other thing to think about is if young people are under the care of a very good service, where they're getting supportive therapy alongside the hormone treatment, it's really difficult to know what has reduced suicidality, if it is reduced, is it the hormones or is it the psychotherapy counseling, anything else that they're getting alongside of it?

So what is the important practical issue here? And that is that we have to provide holistic care for these young people. It's really key for us to, particularly in the UK, where we have got a national health system, and we will be operating in a proper networked fashion, so that there's links between local services and specialist services.

What we need to try and do is pick out young people who we think are at risk and say, what are all the things we need, to get in place to support this young person's risk? It may be helping with their eating disorder. It may be that they are in difficult family circumstances. There's a whole raft of things that we may need to think about, and it's much more important to say on an individual basis, how do we manage this person's risk, than just assuming that gender-affirming care is going to be the answer.

CHAKRABARTI: The report also cites another potential challenge is that it's not necessarily that care providers have wanted to overlook the other problems, but the focus from the beginning, whether by virtue of the medical culture, or even what the family and young person desire for themselves, has been on the gender dysphoria versus the other potential comorbidities.

CASS: It's also been that people have been nervous about seeing these young people, because there's so much toxicity in the debate and there's so little guidance and there's such poor evidence, that a lot of local practitioners have said, this is just outside my expertise and referred them straight to the specialist service.

And so they haven't had the real basic assessments that would happen for other young people who were similarly distressed. So I think it's a combination of things. It's just focusing on the dysphoria or it's actually just not seeing them at all in local services, because people think they need to go straight to the specialist service.

CHAKRABARTI: So there's another part of the review which I think many people were quite surprised by. There's a whole section on social transition. And the review concludes that it is possible that social transition can be done in childhood, and that could mean anything from appearance, pronouns, et cetera. It's quite a wide range.

But the review concludes that social transition in childhood may change the trajectory of gender identity development for children with early gender incongruence. For this reason, a more cautious approach needs to be taken for children than for adolescents. Elaborate on that, Dr. Cass.

CASS: So let's take a boy who is presenting some degree of gender incongruence in how they behave, in the clothes that they want to wear.

That may be because they're going to grow up and have a stable trans identity, but more commonly, young boys who present like that tend to grow up into gay men, and sometimes they'll grow up as cis, straight men. If you close down the possibilities too early, by the parent thinking that they're doing the best thing, and continuing to socialize them as a girl, it's possible that you have changed that trajectory of a child who may have grown up to be a gay man.

CHAKRABARTI: But we don't know, again.

CASS: We don't know. We don't know. And I think one of the things that many trans advocates have said to us is that by suggesting that is a worse outcome, you are suggesting that a cis outcome is better. And it's really important to say that a cis outcome and a trans outcome have equal value.

One should never be valued more than the other. But it is the case that if you are going to go through a medical transition, that is going to have lifetime implications in terms of being on medication, in terms of potential adverse effects on your health. So it's really important to be absolutely clear that's the right pathway for you as an individual.

So if it wasn't for the medical intervention, I think this would not be such a challenging issue for us.

CHAKRABARTI: Okay. Again, thinking of the very challenging navigation that families, and in this case, also schools have to undertake in dealing with social transition. To be clear, the report finds that there's insufficient evidence that's available to say whether social transitioning has a positive or negative impact on mental health for children, slight positive impact on adolescents.

But then it goes farther and says, social transition is an active intervention and that parents should be fully involved, and that clinical involvement should also take place, too. I think there were a lot of people who were concerned about those classifications and those recommendations, Dr. Cass.

CASS: Yeah. I think for schools, they have got a significant problem in that some members of staff will be worried that a child has spoken to them in confidence, and they may be at risk from their parents if the school staff speak to parents about it.

In the UK, certainly, our philosophy is that parents are well intentioned towards their children, unless you've got very good reasons to suspect that might not be the case. And secrets between children and their families living a different life at school from at home is challenging. A young person thrives best with the support of their family.

So our advice is that wherever possible, parent should be involved in a decision. Also, because parents may know things about the young person's history that school just don't know. Things like that they've been traumatized, that they've lost a parent, that they've gone through some kind of abusive situation, that they've had an eating disorder, and all of those things may have an impact on how that young person identifies.

And if the school isn't fully in the picture, they may make a decision that doesn't take account of really important factors. So for all those reasons, involving the parents is advisable.

CHAKRABARTI: Okay. Dr. Cass, this brings us back to where we began, and that is you and the independent review team undertook the world's largest systematic review of all of the evidence and studies related to care for gender dysphoric or gender-questioning young people.

And we've gone over some of the conclusions about lack of evidence for puberty blockers, similarly for hormones, lack of evidence to say with certainty if gender-affirming care reduces suicidality. These are very specific and concrete conclusions in terms of evidence.

It's interesting to me that I would say the world's largest and most influential body that provides guidance for trans care, the World Professional Association for Transgender Health or WPATH, in their most recent standards of care document, they said that despite the slowly growing body of evidence, the number of studies is still low, and there are few outcome studies that follow youth into adulthood.

Therefore, a systematic review regarding outcomes of treatment in adolescents is not possible. Yet, is that not what the Cass Review did? A systematic review?

CASS: Yes, and actually, so did WPATH. WPATH commissioned a systematic review from John Hopkins, which is obviously one of the most credible organizations in the U.S., but then they didn't refer to that in that part, in the youth part of their guidance. And that was one of the reasons that when our team rated the various guidelines, they rated the WPATH guidelines relatively poorly in terms of the rigor of their development process. Because there were points within the chapter on children and youth where the WPATH team suggested that there was strong evidence and there wasn't.

So there was a disconnect between the systematic review that they commissioned, and the conclusions that they reached.

CHAKRABARTI: When we talk about WPATH and their latest, their 8 standards of care, they do conclude that the evolving science has shown clinical benefit for transgender youth, who receive their gender-affirming treatments in multidisciplinary gender clinics.

And then they cite three different studies that they claim supports the assertion of clinical benefit. Okay. But the Cass Review points out that one of those studies cited was that original Dutch protocol that we talked about, that deals with a completely different cohort of young people. Then there's another study that had a one year follow up, showing actually very modest changes for young people.

And also, I think your team thought the study was too low quality and didn't even include it in your review. And then, most remarkably, the third study that WPATH cites is one that the Cass Review said, it's a study protocol and does not even include any results.

CASS: Yeah, that's right.

CHAKRABARTI: So what, given that it seems as if the Cass Review team comes away with some pretty fundamental concerns about the quality of not just WPATH's guidance, but the guidance offered by the Endocrine Society, the American Academy of Pediatrics, other medical societies in other countries around the world.

What's the common problem you see there?

CASS: Yes, so you have read this extremely carefully, probably better than most of the UK commentators. I think the problem is that there has been an echo chamber of guidelines. So one of the things that the York team did was they looked at where guidelines had followed each other, and they found that most of the guidelines, there was a circularity between the Endocrine Society, WPATH and a series of other guidelines. The ones that had not taken that approach and had really started with a clean slate were the Nordic ones, the Finish and the Swedish ones.

And I think the striking difference between those was that they said from the outset that this is a different population of young people, and their conclusions were very similar to our own.

CHAKRABARTI: Okay. Dr. Cass, it's now been a month since the independent review was first made public. And of course, there's been quite a bit of response to it.

I just want to quote some of the criticisms that have been made of the report. For example, the World Professional Association for Transgender Health that we just mentioned, they issued an email statement saying the report is, quote, "Rooted in the false premise that non-medical alternatives to care will result in less adolescence distress."

And they criticized some of the recommendations from the report, which they claim would, quote, "Severely restrict access to physical health care for gender-questioning young people." Your response to that?

CASS: We've not taken a position that any form of care is best, but what we have said is that it is important that all young people get access to evidence based, non-medical interventions that address the full range of their difficulties.

This group of young people, if they are depressed, if they're anxious, if they need an autism diagnosis, all of those things should be put in place. We don't know which young people may benefit from medical care, and we have proposed that every young person who walks through the door should be included in some kind of proper research protocol, so that we can follow them up and we can get those answers over time.

But for those young people where there is a clear, clinical view that they may benefit from treatments, they will, medical treatment. They will be given that medical treatment. But as I say, under proper research supervision, so that we don't continue in this black hole of not knowing what's best.

CHAKRABARTI: And I suppose another set of criticisms really are rooted in the fraught political activity around the issue of care for gender-questioning youth.

I know it's been quite fraught in the UK, and you know how serious it is here in the United States.

CHAKRABARTI: So many professional associations and advocacy groups are just calling the Cass Report harmful, just flat out harmful. Because it could be used to weaponize political goals to severely restrict or even end any kind of care for gender-questioning young people. Is that a concern of yours?

CASS: It certainly was a concern that might be the case in the UK. I'm really pleased to say that in the UK, both of the main parties, the main political parties here have accepted the findings of the report and said we shouldn't be politicizing this. Because this is about trying to decide the best clinical care for young people, and it shouldn't be political.

None of this should be decided on ideological grounds from either side of the debate. It should be decided by really carefully working with young people, families, clinicians, and academics to try and pick through what is the best clinical approach. That's all that should matter here.

CHAKRABARTI: Dr. Cass, I just have two more questions for you.

One, to summarize the findings of, it's a 388-page report, but I think it can, it's fair to say that generally after this systematic review of all the available studies of different aspects of medicalized care for gender-questioning youth. The review found that when it comes to the use of puberty blockers, cross sex hormones, that there is an insufficient evidence base to make any certain claims about the efficacy of those treatments.

Dr. Cass, the report also points out though that the use of those treatments has skyrocketed, along with the increase in the number of children, female adolescents, reporting gender distress. Have you ever seen that kind of growth for a treatment method that didn't have an appropriate evidence base already?

CASS: This has been quite different from anything I have observed before in my clinical practice, and I think it has partly been driven by the availability of a treatment and partly by a series of sociocultural beliefs about how gender may be expressed and the mutability and flexibility of gender.

And that, in some, that changed belief set is positive in many ways. Because certainly if younger people have a much more flexible view of how gender can be expressed, that breaks down gender stereotypes. It maybe breaks down misogyny. There's lots that's good about that more flexible view, but it doesn't necessarily mean that you have to treat it medically.

People are really clear in the trans community that this should not be pathologized. And so I guess we have to think about, when is it the right thing to give quite significant medications, and when is gender expression just an expression, a normal expression that doesn't need to be treated in that way.

CHAKRABARTI: Does the Cass Review essentially bring an end to gender-affirming care in England?

CASS: No, But I think it just injects more caution. There was a study that came out just as we were going to press, and it demonstrated that gender non-contentedness, and they define gender non-contentedness by the question, "I want to be the other gender."

It was highest around 11 and it dropped off continuously into early twenties. And so it's not about saying there shouldn't be gender-affirming care. It's just, when is the right time to embark on that gender-affirming care? And most particularly, when is it safe to embark on the components of that care that might be hardest to reverse?

CHAKRABARTI: You write in the report that gender-questioning young people have been failed by the medical establishment, by the NHS in England. In order to recover from that failure, what does the report recommend change for the treatment of young people?

CASS: I think first and foremost, seeing them as a young person and not as somebody who is gender questioning, or with a gender problem or a gender issue.

They are a young person first. And I think one problem has been just seeing them through a gender lens. I think we need to re-empower professionals to not be afraid and to realize these are the same young people that they're seeing in their clinics with many other problems.

And in the long term, I think if young people could walk through the same door that doesn't have to be labelled gender, but is a clinic for young people to talk about a range of issues, whether it's their mental health, their sexual health, their sexuality and their gender, and they could see somebody who would really see them as a whole person and work out what the care package is that they need, then I think they would get a much better deal.

CHAKRABARTI: Dr. Cass, I just would like to read the last sentence of the review. You write, quote, "I am aware that this report would generate much discussion and that strongly held views will be expressed. While open and constructive debate is needed, I would urge everybody to remember the children and young people trying to live their lives, and the families and carers and clinicians doing their best to support them. All should be treated with compassion and respect."

For those children and families and clinicians listening to this interview now, Dr. Cass, what would you tell them? What thought would you leave them with?

CASS: I think the most important thing is keep your options open. I'd say what some of the young adults said, it's not as urgent as it feels.

Take your time. Think about all the possibilities open to you. Talk to other young people. But try not to rush.

CHAKRABARTI: Dr. Hilary Cass, she led the team that recently published the Independent Review of Gender Identity Services for Children and Young People. It's a massive report that was published at the behest of the National Health Services in England. Dr. Cass, thank you so much for joining us.

CASS: Thank you.

Dorey Scheimer Senior Editor, On Point Dorey Scheimer is a senior editor at On Point.

Meghna Chakrabarti Host, On Point Meghna Chakrabarti is the host of On Point.

Tim Skoog Sound Designer and Producer, On Point Tim Skoog is a sound designer and producer for On Point.

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Title: akal badi ya bias: an exploratory study of gender bias in hindi language technology.

Abstract: Existing research in measuring and mitigating gender bias predominantly centers on English, overlooking the intricate challenges posed by non-English languages and the Global South. This paper presents the first comprehensive study delving into the nuanced landscape of gender bias in Hindi, the third most spoken language globally. Our study employs diverse mining techniques, computational models, field studies and sheds light on the limitations of current methodologies. Given the challenges faced with mining gender biased statements in Hindi using existing methods, we conducted field studies to bootstrap the collection of such sentences. Through field studies involving rural and low-income community women, we uncover diverse perceptions of gender bias, underscoring the necessity for context-specific approaches. This paper advocates for a community-centric research design, amplifying voices often marginalized in previous studies. Our findings not only contribute to the understanding of gender bias in Hindi but also establish a foundation for further exploration of Indic languages. By exploring the intricacies of this understudied context, we call for thoughtful engagement with gender bias, promoting inclusivity and equity in linguistic and cultural contexts beyond the Global North.

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