problem solving by country

Nov 8, 2023

How Do Different Cultures Solve Problems?

Written by: liu liu , executive contributor, executive contributors at brainz magazine are handpicked and invited to contribute because of their knowledge and valuable insight within their area of expertise..

I saw this poster a few times, and every time it made me chuckle. Funny aside, there seems to be some truth in it.

International guidelines for problem solving

Here are three questions to help you reflect before we dive deeper to unpack the different approaches various cultures take to solve problems.

What is your approach to problem-solving?

What other different approaches to problem-solving have you seen?

What would you say are the Pros and Cons of these different approaches?

Group culture approach

In group culture, when there is a problem, people tend to look up to those who are in a higher position for a solution rather than start thinking for themselves about what the solution could be. The solution needs to be a group decision led by a leader. This cultural group is good at solving context-based problems, meaning if the problem has to do with relationships, connections, and issues related to humans.

Individual culture approach

Individual cultures might see problem-solving differently. They might see that everyone in the team can contribute to finding the solution despite their position in the team. People from this culture tend to look at a problem from a process and rule angle and are good at solving problems in these areas.

High context and low contact culture approach

When people from a high-context culture meet problems, they take a perceptual approach. This means the way to find a solution is guided by intuition, your heart, and soul, or your gut feeling as people sometimes call it. They would like to review the problem in connection with time and space because they don’t believe anything happens in isolation. Observation is the primary method to understand the problem.

Different from the high-context culture, the low-context culture approaches problem-solving from an analytical perspective. They don’t rely on their “gut feelings”. Instead, they like to use facts and data to understand the problem and try to find a solution through an analytic and subject process.

Relationship approach

When it comes to problem-solving, another set of cultural lenses we need to look through is our relationship-based versus task-oriented cultures. If you recall, broadly speaking, hot climate and high context cultures are more relationship-based; and cold climate and low context cultures are more task-oriented.

In my years of working with people from these two cultures, I noticed this. When problems occur, a relationship-based culture tends to accept reality quickly. The response often is,” This is bad, how can we work around it and find a new path?” When finding a new path to the solution, people are important. They will try not to embarrass anybody or damage relationships during the process. Ethics and social customs are followed.

Task-oriented approach

On the contrary, the first question task-oriented people tend to ask is “Why did this happen”. The why question is paramount, they want to gather data and analyze every detail and will not shy away from pointing out the mistakes made by people, no matter who that person is. The focus is solely on solving the problem logically.

Graphic by Yang Liu, source: How Western and Eastern people deal with problems

This picture by Liu Yang in an article called “How Western and Eastern people deal with Problems” very vividly summarizes these two different approaches to problem-solving. There is a link at the bottom of the slide to the full article which talks more about the culturally different views on issues. I would encourage you to read it.

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By Jeevan Vasagar

Roula Khalaf, Editor of the FT, selects her favourite stories in this weekly newsletter.

Maths lessons have changed since Tom Ding was at school. Recalling his favourite subject, Ding remembers: “A big pile of textbooks, the teacher taking you through an example, giving you a bit of context and then telling you what page to open the book at.”

So he was surprised to enter a classroom as a trainee maths teacher to find the textbooks on a shelf while pupils grappled with questions such as: “Does speaking a different language mean you count differently?” In another lesson, students debated the best way to represent a number – was it as a fraction, a decimal or a percentage?

Ding, who gave up a career in advertising to train as a teacher with the UK state school chain Ark, says that such questions are a way for students to move beyond rote learning. “If something is learned too much by rote, there’s a chance those broader concepts are lost.”

Education is under pressure to respond to a changing world. As repetitive tasks are eroded by technology and outsourcing, the ability to solve novel problems has become increasingly vital.

The origin of the word computer is an indication of the shift. The first computers were not machines but groups of people, each working on part of a complex calculation.

As computers have grown more powerful, humans are no longer needed to crunch the numbers. Instead the role of people is to work out which mathematical model approximates best to a real life situation – whether that is the fastest way to deliver Christmas shopping, or organising relief in a disaster zone.

As the rise of tech companies shows, there are high salaries for those most able to organise the world’s messy information. The challenge for schools is to combine the teaching of knowledge with the ability to marshal those facts in unfamiliar situations. How well are they doing it? And can they do better?

The first of those questions was answered in April this year, when the OECD published an assessment of the problem-solving skills of teenagers around the world.

About 85,000 teenagers in 44 countries and regions took the tests for the OECD’s Programme for International Student Assessment study. The tests expected them to devise strategies for tackling unfamiliar problems. In one, they were shown a map of routes linking the suburbs of a fictional city and asked to suggest a place where three people could meet but no one would have to travel for more than 15 minutes.

They faced situations where the information was incomplete, such as dealing with a new digital device: “You have no instructions for your new air conditioner. You need to work out how to use it.”

And they had to cope with surprises. In another problem, students were told to buy a number of tickets at a concession fare from a ticket machine, only to discover that the concession was not available.

Pupils at Williamwood High School attend a math class

Schools in Europe are frequently criticised by business leaders as “exam factories” that churn out students unable to cope with life beyond the classroom. But the lesson to be drawn from international comparison is that Europe’s schools are far better at teaching creative thought than this criticism implies.

Students from the main western European countries – England, France, Germany, Italy, the Netherlands and Belgium – all performed above the average, as did pupils from the Czech Republic and Estonia. In the rest of the rich world, the US, Canada and Australia also performed above average. But the laurels were taken by east Asian territories; Singapore and South Korea performed best, followed by Japan, and the Chinese regions of Macau and Hong Kong.

That result poses a challenge to schools in the west. Critics of east Asian education systems attribute their success at maths and science to rote learning.

But the OECD’s assessment suggests that schools in east Asia are developing thinking skills as well as providing a solid grounding in core subjects.

Across the world, the OECD study found a strong and positive correlation between performance in problem solving and performance in maths, reading and science.

In general, the high-performing students were also the ones best able to cope with unfamiliar situations.

But there were interesting exceptions to the rule. When Japanese students were compared with children in other countries of similar performance in maths, science and reading, the Japanese teenagers showed better problem-solving abilities.

This, the OECD suggested, might be explained by Japan’s focus on developing problem- solving skills through cross-curricular, student-led projects.

While there is agreement about the goal, there is a divide over how best to teach children the skill of critical thinking.

Daisy Christodoulou, an educationalist and the author of Seven Myths about Education , argues that such skills are domain specific – they cannot be transferred to an area where our knowledge is limited.

“Trying to teach abstract strategies that can apply across domains, there isn’t much evidence for that,” she says.

“The farther away from the original domain you are, the weaker the transfer is. In our lives this does ring true. We all know people who are good at thinking critically about a historical problem, and not very good at thinking critically about a mathematical problem.”

Critical thinking is a skill that is impossible to teach directly but must be intertwined with content, Christodoulou argues. Shakespeare, lauded for breaking rules, was the product of a rigidly traditional education.

“We have a good idea of what Shakespeare’s education was like,” she says. “He would have learned figures of speech by heart, in Latin.” And the rhetorical devices that he learned as a schoolboy are deployed with increasing confidence in his plays.

“In his early plays, it is quite mechanical, and as he goes on he is playing with these figures of speech and using them in a creative way. Learning by rote, far from stifling creativity, enabled it,” Christodoulou says.

Some argue that placing too strong an emphasis on children acquiring knowledge alone leaves them struggling when faced with more complex problems.

Tim Taylor, a former primary school teacher who now trains teachers, says: “If you front-load knowledge and leave all the thinking and critical questioning until later, children don’t develop as effective learners.”

There are some generic tools that transfer across disciplines, Taylor argues. “What is reading if not a cognitive tool? And that is clearly ‘transferable’.”

The style of teaching that he coaches, called Mantle of the Expert, encourages children to pose as experts faced with an imaginary scenario; aiming to engage their imaginations and help them figure out how they would get access to the information they need.

In a class studying the Great Fire of London, for example, pupils will play the parts of experts helping a museum create an exhibition about the fire. “It’s a way of making content more meaningful,” Taylor says.

The way to teach generic skills is to be “mindful of it as a teacher”, Taylor suggests. “You create opportunities to keep that in the forefront of what you are doing – how is this helping us? How can we use this in another context? That is the point of education, to develop a ‘growth mindset’,” he states.

It is hard to know how much of the advantage east Asian pupils have in international comparisons comes from the academic rigour of their schools, and how much is derived from recent reforms in the countries that have sought to give students a more holistic education.

The OECD suggests that those countries where students do best at problem solving, are not only good at teaching the core subjects, but are good at providing learning opportunities that prepare students well for complex, real-life problems.

Ding, the trainee maths teacher, says the school where he works in north London attempts to sidestep the debate between facts and skills by pursuing both with equal relish.

“On the one hand, our maths lessons begin with times table drills,” says Ding. “We put a lot of emphasis on repetition, and frequent testing means students are regularly rehearsing and assessing what they know.”

“On the other hand, we also try to use rich, open questions to structure the units of work, making them more enjoyable and memorable for students, and allowing us to avoid shallow rote learning and discuss higher-order concepts along the way.”

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International Edition

An IERI – International Educational Research Institute Journal

Open access
Published: 10 December 2014

The acquisition of problem solving competence: evidence from 41 countries that math and science education matters

Ronny Scherer 1 , 2 &
Jens F Beckmann 3

Large-scale Assessments in Education volume 2 , Article number: 10 ( 2014 ) Cite this article

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On the basis of a ‘problem solving as an educational outcome’ point of view, we analyse the contribution of math and science competence to analytical problem-solving competence and link the acquisition of problem solving competence to the coherence between math and science education. We propose the concept of math-science coherence and explore whether society-, curriculum-, and school-related factors confound with its relation to problem solving.

By using the PISA 2003 data set of 41 countries, we apply multilevel regression and confounder analyses to investigate these effects for each country.

Our results show that (1) math and science competence significantly contribute to problem solving across countries; (2) math-science coherence is significantly related to problem solving competence; (3) country-specific characteristics confound this relation; (4) math-science coherence is linked to capability under-utilisation based on science performance but less on math performance.

Conclusions

In sum, low problem solving scores seem a result of an impeded transfer of subjectspecific knowledge and skills (i.e., under-utilisation of science capabilities in the acquisition of problem solving competence), which is characterised by low levels of math-science coherence.

The ability to solve real-world problems and to transfer problem-solving strategies from domain-specific to domain-general contexts and vice versa has been regarded an important competence students should develop during their education in school (Greiff et al. [ 2013 ]; van Merriënboer [ 2013 ]). In the context of large-scale assessments such as the PISA study problem solving competence is defined as the ability to solve cross-disciplinary and real-world problems by applying cognitive skills such as reasoning and logical thinking (Jonassen [ 2011 ]; OECD [ 2004 ]). Since this competence is regarded a desirable educational outcome, especially math and science educators have focused on developing students’ problem solving and reasoning competence in their respective domain-specific contexts (e.g., Kind [ 2013 ]; Kuo et al. [ 2013 ]; Wu and Adams [ 2006 ]). Accordingly, different conceptual frameworks were proposed that describe the cognitive processes of problem solving such as understanding the problem, building adequate representations of the problem, developing hypotheses, conducting experiments, and evaluating the solution (Jonassen [ 2011 ]; OECD [ 2005 ]). In comparing these approaches in math and science, it seems apparent that there is a conceptual overlap between the problem solving models in these two domains. This overlap triggers the question regarding its contribution to the development of students’ cross-curricular problem-solving competence (Abd-El-Khalick et al. [ 2004 ]; Bassok and Holyoak [ 1993 ]; Hiebert et al. [ 1996 ]).

The operationalization and scaling of performance in PISA assessments enables direct contrasting of scores in students’ competences in math and problem solving. Leutner et al. ([ 2012 ]) suggest that discrepancies between math and problem solving scores are indicative of the relative effectiveness of math education (OECD [ 2004 ]). In line with a “Capability-Utilisation Hypothesis”, it is assumed that math scores that negatively deviate from their problem solving counterpart signify an under-utilisation of students’ problem-solving capabilities as indicated by their scores in generic problem solving.

We intend to extend this view in two ways: First, by introducing the concept of math-science coherence we draw the focus on the potential synergistic link between math and science education and its contribution to the acquisition of problem solving competence. Second, the introduction of a Capability Under-Utilisation Index will enable us to extend the focus of the Capability-Utilisation Hypothesis to both, math and science education. The combination of the concept of math-science coherence with the notion of capability-utilisation will help to further explore the facilitating processes involved in the transition of subject-specific knowledge and skills to the acquisition of problem solving competence. These insights are expected to contribute to a better understanding of meaningful strategies to improve and optimize educational systems in different countries.

Theoretical framework

Problem solving as an educational goal.

In the PISA 2003 framework, problem solving is referred to as “an individual’s capacity to use cognitive processes to resolve real, cross-disciplinary situations where the solution path is not immediately obvious” (OECD [ 2004 ], p. 156). This definition is based on the assumption of domain-general skills and strategies that can be employed in various situations and contexts. These skills and strategies involve cognitive processes such as: Understanding and characterizing the problem, representing the problem, solving the problem, reflecting and communicating the problem solution (OECD [ 2003 ]). Problem solving is often regarded a process rather than an educational outcome, particularly in research on the assessment and instruction of problem solving (e.g., Greiff et al. [ 2013 ]; Jonassen [ 2011 ]). This understanding of the construct is based on the assumption that problem solvers need to perform an adaptive sequence of cognitive steps in order to solve a specific problem (Jonassen [ 2011 ]). Although problem solving has also been regarded as a process skill in large-scale assessments such as the PISA 2003 study, these assessments mainly focus on problem solving performance as an outcome that can be used for international comparisons (OECD [ 2004 ]). However, problem solving competence was operationalized as a construct comprised of cognitive processes. In the context of the PISA 2003 study, these processes were referred to as analytical problem solving, which was assessed by static tasks presented in paper-and-pencil format. Analytical problem-solving competence is related to school achievement and the development of higher-order thinking skills (e.g., Baumert et al. [ 2009 ]; OECD [ 2004 ]; Zohar [ 2013 ]). Accordingly, teachers and educators have focused on models of problem solving as guidelines for structuring inquiry-based processes in their subject lessons (Oser and Baeriswyl [ 2001 ]). Van Merriënboer ([ 2013 ]) pointed out that problem solving should not only be regarded a mere instructional method but also as a major educational goal. Recent curricular reforms have therefore shifted towards the development of problem solving abilities in school (Gallagher et al. [ 2012 ]; Koeppen et al. [ 2008 ]). These reforms were coupled with attempts to strengthen the development of transferable skills that can be applied in real-life contexts (Pellegrino and Hilton [ 2012 ]). For instance, in the context of 21 st century skills, researchers and policy makers have agreed on putting emphasis on fostering skills such as critical thinking, digital competence, and problem solving (e.g., Griffin et al. [ 2012 ]). In light of the growing importance of lifelong learning and the increased complexity of work- and real-life problem situations, these skills are now regarded as essential (Griffin et al. [ 2012 ]; OECD [ 2004 ]). Hence, large-scale educational studies such as PISA have shifted towards the assessment and evaluation of problem solving competence as a 21 st century skill.

The PISA frameworks of math and science competence

In large-scale assessments such as the PISA studies, students’ achievement in the domains of science and mathematics play an important role. Moreover, scientific and mathematical literacy are now regarded essential to being a reflective citizen (Bybee [ 2004 ]; OECD [ 2003 ]). Generally, Baumert et al. ([ 2009 ]) have shown that students’ math and science achievements are highly related to domain-general ability constructs such as reasoning or intelligence. In this context, student achievement refers to “the result of domain-specific processes of knowledge acquisition and information processing” (cf. Baumert et al. [ 2009 ], p. 169). This line of argument is reflected in definitions and frameworks of scientific and mathematical literacy, which are conceptualized as domain-specific competences that are hierarchically organized and build upon abilities closely related to problem solving (Brunner et al. [ 2013 ]).

Scientific literacy has been defined within a multidimensional framework, differentiating between three main cognitive processes, namely describing, explaining, and predicting scientific phenomena, understanding scientific investigations, and interpreting scientific evidence and conclusions (OECD [ 2003 ]). In addition, various types of knowledge such as ‘knowledge about the nature of science’ are considered as factors influencing students’ achievements in this domain (Kind [ 2013 ]). We conclude that the concept of scientific literacy encompasses domain-general problem-solving processes, elements of scientific inquiry (Abd-El-Khalick et al. [ 2004 ]; Nentwig et al. [ 2009 ]), and domain-specific knowledge.

The definition of mathematical literacy refers to students’ competence to utilise mathematical modelling and mathematics in problem-solving situations (OECD [ 2003 ]). Here, we can also identify overlaps between cognitive processes involved in mathematical problem solving and problem solving in general: Structuring, mathematizing, processing, interpreting, and validating (Baumert et al. [ 2009 ]; Hiebert et al. [ 1996 ]; Kuo et al. [ 2013 ]; Polya [ 1945 ]). In short, mathematical literacy goes beyond computational skills (Hickendorff [ 2013 ]; Wu and Adams [ 2006 ]) and is conceptually linked to problem solving.

In the PISA 2003 framework, the three constructs of math, science, and problem solving competence overlap conceptually. For instance, solving the math items requires reasoning, which comprises analytical skills and information processing. Given the different dimensions of the scientific literacy framework, the abilities involved in solving the science items are also related to problem solving, since they refer to the application of knowledge and the performance of inquiry processes (OECD [ 2003 ]). This conceptual overlap is empirically supported by high correlations between math and problem solving ( r = .89) and between science and problem solving ( r = .80) obtained for the sample of 41 countries involved in PISA 2003 (OECD [ 2004 ]). The relation between math and science competence was also high ( r = .83). On the one hand, the sizes of the inter-relationships, give rise to the question regarding the uniqueness of each of the competence measures. On the other hand, the high correlations indicate that problem-solving skills are relevant in math and science (Martin et al. [ 2012 ]). Although Baumert et al. ([ 2009 ]) suggest that the domain-specific competences in math and science require skills beyond problem solving (e.g., the application of domain-specific knowledge) we argue from an assessment perspective that the PISA 2003 tests in math, science, and problem solving measure predominantly basic academic skills relatively independent from academic knowledge (see also Bulle [ 2011 ]).

The concept of capability-utilisation

Discrepancies between students’ performance in math/science and problem solving were studied at country level (OECD [ 2004 ]) and were, for example for math and problem solving scores, interpreted in two ways: (1) If students’ perform better in math than in problem solving, they would “have a better grasp of mathematics content […] after accounting for the level of generic problem-solving skills…” (OECD [ 2004 ], p. 55); (2) If students’ estimated problem-solving competence is higher than their estimated math competence, “… this may suggest that students have the potential to achieve better results in mathematics than that reflected in their current performance…” (OECD [ 2004 ], p. 55). Whilst the latter discrepancy constitutes a capability under-utilisation in math, the former suggests challenges in utilising knowledge and skills acquired in domain-specific contexts in domain-unspecific contexts (i.e., transfer problem).

To quantify the degree to which students are able to transfer their problem solving capabilities from domain-specific problems in math or science to cross-curricular problems, we introduce the Capability Under-Utilisation Index (CUUI) as the relative difference between math or science and problem solving scores:

A positive CUUI indicates that the subject-specific education (i.e., math or science) in a country tends to under-utilise its students’ capabilities to problem solve. A negative CUUI indicates that a country’s educational system fails to fully utilise its students’ capabilities to acquire math and science literacy in the development of problem solving. The CUUI reflects the relative discrepancies between the achievement scores in different domains a .

The concept of math-science coherence

In light of the conceptual and empirical discussion on the relationship between math, science, and problem solving competence, we introduce the concept of math-science coherence as follows: First, math-science coherence refers to the set of cognitive processes involved in both subjects and thus represents processes which are related to reasoning and information processing, relatively independent from domain-specific knowledge. Second, math-science coherence reflects the degree to which math and science education is harmonized as a feature of the educational environment in a country. This interpretation is based on the premise that PISA measures students’ competence as educational outcomes (OECD [ 2004 ]). The operationalization of math-science coherence is realized by means of the correlation between math and science scores [ r (M,S)] at the country level. Low math-science coherence indicates that students who are successful in the acquisition of knowledge and skills in math are not necessarily successful in the acquisition of knowledge and skills in science and vice versa.

On the basis of this conceptualization of math-science coherence, we expect a significant and positive relation to problem solving scores, since the conceptual overlap between mathematical and scientific literacy refers to cognitive abilities such as reasoning and information processing that are also required in problem solving (Arts et al. [ 2006 ]; Beckmann [ 2001 ]; Wüstenberg et al. [ 2012 ]). Hence, we assert that math-science coherence facilitates the transfer of knowledge, skills, and insights across subjects resulting in better problem solving performance (OECD [ 2004 ]; Pellegrino and Hilton [ 2012 ]).

We also assume that math-science coherence as well as capability utilisation is linked to characteristics of the educational system of a country. For instance, as Janssen and Geiser ([ 2012 ]) and Blömeke et al. ([ 2011 ]) suggested, the developmental status of a country, measured by the Human Development Index (HDI; UNDP [ 2005 ]), is positively related to students’ academic achievements as well as to teachers’ quality of teaching. Furthermore, the socio-economic status of a country co-determines characteristics of its educational system, which ultimately affects a construct referred to as national intelligence (Lynn and Meisenberg [ 2010 ]). Research also indicated that curricular settings and educational objectives are related to school achievement in general (Bulle [ 2011 ]; Martin et al. [ 2004 ]). Besides these factors, school- and classroom-related characteristics might also confound the relation between math-science coherence and problem solving. For instance, the schools’ autonomy in developing curricula and managing educational resources might facilitate the incorporation of inquiry- and problem-based activities in science lessons (Chiu and Chow [ 2011 ]). These factors have been discussed as being influential to students’ competence development (OECD [ 2004 ], [ 2005 ]). Ewell ([ 2012 ]) implies that cross-national differences in problem solving competence might be related to differences in education and in using appropriate teaching material. These factors potentially confound the relation between math-science coherence and problem solving.

Discrepancies between math and problem solving scores are discussed in relation to quality of education. Although research has found that crossing the borders between STEM subjects positively affects students’ STEM competences (e.g., National Research Council NRC [ 2011 ]), we argue that the PISA analyses have fallen short in explaining cross-country differences in the development of problem solving competence, since they ignored the link between math and science competences and the synergistic effect of learning universally applicable problem-solving skills in diverse subject areas. Hence, we use the concept of math-science coherence to provide a more detailed description of the discrepancies between problem solving and domain-specific competences. In this regard, we argue that the coherence concept indicates the synergistic potential and students’ problem-solving competence the success of transfer.

The present study

The current study is based on the premise that in contrast to math and science competence problem solving competence is not explicitly taught as a subject at school. Problem solving competence, however, is an expected outcome of education (van Merriënboer [ 2013 ]). With the first step in our analyses, we seek to establish whether math and science education are in fact main contributors to the acquisition of problem solving competence. On the basis of this regression hypothesis, we subsequently focus on the question whether there are significant and systematic differences between countries ( Moderation-Hypothesis ). In light of the conceptual overlap due to cognitive processes involved in dealing with math, science and problem solving tasks and the shared item format employed in the assessments, we expect math and science competence scores to substantially predict scores in problem solving competence. Furthermore, since math and science education are differently organized across the 41 countries participating in the PISA 2003 study, differences in the contribution are also expected.

On the basis of these premises, we introduce the concept of math-science coherence, operationalised as the correlation between math and science scores [ r (M,S)], and analyse its relationship to problem solving and the effects of confounders (i.e., country characteristics) as a step of validation. Since math, science, and problem solving competence show a conceptual overlap, we expect problem solving and math-science coherence to be positively related. Countries’ educational systems differ in numerous aspects, their educational structure, and their educational objectives. Countries also differ with regard to the frequency of assessments, the autonomy of schools in setting up curricula and resources, and the educational resources available. Consequently, we expect the relation between math-science coherence and problem solving competence to be confounded by society-, curriculum-, and school-related factors ( Confounding-Hypothesis ).

In a final step, we aim to better understand the mechanisms with which math and science education contributes to the acquisition of problem-solving competence by exploring how math-science coherence, capability utilisation, and problem solving competence are related. We thus provide new insights into factors related to the transfer between students’ domain-specific and cross-curricular knowledge and skills ( Capability-Utilisation Hypothesis ).

In PISA 2003, a total sample of N = 276,165 students (49.4% female) from 41 countries participated. The entire sample was randomly selected by applying a two-step sampling procedure: First, schools were chosen within a country. Second, students were chosen within these schools. This procedure consequently led to a clustered structure of the data set, as students were nested in 10,175 schools. On average, 27 students per school were chosen across schools within countries. Students’ mean age was 15.80 years ( SD = 0.29 years) ranging from 15.17 to 16.25 years.

In the PISA 2003 study, different assessments were used in order to measure students’ competence in math, science, and problem solving. These assessments were administered as paper-and-pencil tests within a multi-matrix design (OECD [ 2005 ]). In this section, the assessments and further constructs are described that served as predictors of the contribution of math and science competence to problem solving at the country level.

Student achievement in math, science, and problem solving

In order to assess students’ competence to solve cross-curricular problems (i.e., analytical problem solving requiring information retrieval and reasoning), students had to work on an analytical problem-solving test. This test comprised a total of 19 items (7 items referred to trouble-shooting, 7 items referred to decision-making, and 5 items referred to system analysis and design; see OECD [ 2004 ]). Items were coded according to the PISA coding scheme, resulting in dichotomous and polytomous scores (OECD [ 2005 ]). Based on these scores, models of item response theory were specified in order to obtain person and item parameters (Leutner et al. [ 2012 ]). The resulting plausible values could be regarded as valid indicators of students’ abilities in problem solving (Wu [ 2005 ]). The problem solving test showed sufficient reliabilities between .71 and .89 for the 41 countries.

To assess mathematical literacy as an indicator of math competence , an 85-items test was administered (for details, refer to OECD [ 2003 ]). Responses were dichotomously or polytomously scored. Again, plausible values were obtained as person ability estimates and reliabilities were good (range: 0.83 – 0.93). In the context of mathematical literacy, students were asked to solve real-world problems by applying appropriate mathematical models. They were prompted to “identify and understand the role mathematics plays in the world, to make well-founded judgements and to use […] mathematics […]” (OECD [ 2003 ], p. 24).

Scientific literacy as a proxy for science competence was assessed by using problems referring to different content areas of science in life, health, and technology. The reliability estimates for the 35 items in this test ranged between .68 and .88. Again, plausible values served as indicators of this competence.

Country-specific characteristics

In our analyses, we incorporated a range of country-specific characteristics that can be subdivided into three main categories. These are: society-related factors, curriculum-related factors, and school-related factors. Country-specific estimates of National Intelligence as derived by Lynn and Meisenberg ([ 2010 ]) as well as the Human Development Index (HDI) were subsumed under society-related factors . The HDI incorporates indicators of a country’s health, education, and living standards (UNDP [ 2005 ]). Both variables are conceptualised as factors that contribute to country-specific differences in academic performance.

Holliday and Holliday ([ 2003 ]) emphasised the role of curricular differences in the understanding of between-country variance in test scores. We incorporated two curriculum-related factors in our analyses. First, we used Bulle’s ([ 2011 ]) classification of curricula into ‘progressive’ and ‘academic’. Bulle ([ 2011 ]) proposed this framework and classified the PISA 2003 countries according to their educational model. In her framework, she distinguishes between ‘academic models’ which are primarily geared towards teaching academic subjects (e.g., Latin, Germanic, and East-Asian countries) and ‘progressive models’ which focus on teaching students’ general competence in diverse contexts (e.g., Anglo-Saxon and Northern countries). In this regard, academic skills refer to the abilities of solving academic-type problems, whereas so called progressive skills are needed in solving real-life problems (Bulle [ 2011 ]). It can be assumed that educational systems that focus on fostering real-life and domain-general competence might be more conducive to successfully tackling the kind of problem solving tasks used in PISA (Kind [ 2013 ]). This classification of educational systems should be seen as the two extreme poles of a continuum rather than as a strict dichotomy. In line with the reflections above, we would argue that academic and progressive skills are not exclusively distinct, since both skills utilise sets of cognitive processes that largely overlap (Klahr and Dunbar [ 1988 ]). The fact that curricular objectives in some countries are shifting (e.g., in Eastern Asia) makes a clear distinction between both models even more difficult. Nonetheless, we will use this form of country-specific categorization based on Bulle’s model in our analyses.

Second, we considered whether countries’ science curricula were ‘integrated’ or ‘not integrated’ (Martin et al. [ 2004 ]). In this context, integration refers to linking multiple science subjects (biology, chemistry, earth science, and physics) to a unifying theme or issue (cf. Drake and Reid [ 2010 ], p. 1).

In terms of school-related factors, we used the PISA 2003 scales of ‘Frequency of assessments in schools’, ‘Schools’ educational resources’, and ‘School autonomy towards resources and curricula’ from the school questionnaire. Based on frequency and rating scales, weighted maximum likelihood estimates (WLE) indicated the degree to which schools performed in these scales (OECD [ 2005 ]).

The country-specific characteristics are summarized in the Table 1 .

The PISA 2003 assessments utilised a randomized incomplete block design to select different test booklets which covered the different content areas of math, science, and problem solving (Brunner et al. [ 2013 ]; OECD [ 2005 ]). The test administration took 120 minutes, and was managed for each participating country separately. It was established that quality standards of the assessment procedure were high.

Statistical analyses

In PISA 2003, different methods of obtaining person estimates with precise standard errors were applied. The most accurate procedure produced five plausible values, which were drawn from a person ability distribution (OECD [ 2005 ]). To avoid missing values in these parameters and to obtain accurate estimates, further background variables were used within the algorithms (Wu [ 2005 ]). The resulting plausible values were subsequently used as indicators of students’ competence in math, science, and problem solving. By applying Rubin’s combination rules (Bouhilila and Sellaouti [ 2013 ]; Enders [ 2010 ]), analyses were replicated with each of the five plausible values and then combined. In this multiple imputation procedure, standard errors were decomposed to the variability across and within the five imputations (Enders [ 2010 ]; OECD [ 2005 ]; Wu [ 2005 ]).

Within the multilevel regression analyses for each country, we specified the student level as level 1 and the school level as level 2. Since PISA 2003 applied a random sampling procedure at the student and the school level, we decided to control for the clustering of data at these two levels (OECD [ 2005 ]). In addition to this two-level procedure, we regarded the 41 countries as multiple groups (fixed effects). This decision was based on our assumption that the countries selected in PISA 2003 did not necessarily represent a sample of a larger population (Martin et al. [ 2012 ]). Moreover, we did not regard the effects of countries as interchangeable, because, given the specific characteristics of education and instruction within countries; we argue that the effects of competences in mathematics and science on problem solving have their own distinct interpretation in each country (Snijders and Bosker [ 2012 ]). The resulting models were compared by taking into account the Akaike’s information criteria ( AIC ), Bayesian information criteria ( BIC ), and the sample-size adjusted BIC . Also, a likelihood ratio test of the log-Likelihood values ( LogL ) was applied (Hox [ 2010 ]).

To test the Moderation-Hypothesis, we first specified a two-level regression model with problem solving scores as outcomes at the student level (level 1), which allowed variance in achievement scores across schools (level 2). In this model, math and science scores predicted problem solving scores at the student level. To account for differences in the probabilities of being selected as a student within the 41 countries and to adjust the standard errors of regression parameters, we used the robust maximum likelihood (MLR) estimator and students’ final weights (see also Brunner et al. [ 2013 ]; OECD [ 2005 ]). All analyses were conducted in Mplus 6.0 by using the TYPE = IMPUTATION option (Muthén and Muthén [ 2010 ]). As Hox ([ 2010 ]) suggested, using multilevel regression models without taking into account the clustering of data in schools often leads to biased estimates, since achievement variables often have substantial variance at the school level. Consequently, we allowed for level-2-variance within the scores.

After having established whether success in math and science education contributes to the development in problem solving competence across the 41 countries, we then tested whether cross-country differences in the unstandardized regression coefficients were statistically significant by using a multi-group regression model, in which the coefficients were constrained to be equal across countries. We compared this model with the freely estimated model.

Finally, we conceptualized the correlation between math and science scores as an indicator of the level of coherence in math and science education in a country. In relation to the Confounding-Hypothesis, we tested country-specific characteristics for their potentially confounding effects on the relation between math-science coherence and problem solving competence. Following the recommendations proposed by (MacKinnon et al. [ 2000 ]), the confounding analysis was conducted in two steps: (1) we estimated two regression equations. In the first equation, problem solving scores across the 41 countries were regressed on math-science coherence. In the second equation, the respective country characteristics were added as further predictors; (2) the difference between the regression coefficients for math-science coherence obtained in either equation represented the magnitude of a potential confounder effect.

Lastly, we tested the Capability-Utilisation Hypothesis by investigating the bivariate correlations among the CUU Indices and math-science coherence.

Regressing problem solving on math and science performance

To test the Moderation-Hypothesis, we specified regression models with students’ problem-solving score as the outcome and math and science scores as predictors for each of the 41 countries. Due to the clustering of data in schools, these models allowed for between-level variance. Intraclass correlations (ICC-1) for math, science, and problem solving performance ranged between .03 and .61 for the school level ( M = .33, SD = .16).

We specified multilevel regression models for each country separately. These results are reported in Table 2 . The regression coefficients for math on problem solving ranged from .53 to .82 with an average of M( β Math ) = .67 ( SD = .06). The average contribution of science towards problem solving was M( β Science ) = .16 ( SD = .09, Min = -.06, Max = .30). The combination of the distributions of both parameters resulted in substantial differences in the variance explanations of the problem solving scores across the 41 countries ( M[R 2 ] = .65, SD = .15, Min = .27, Max = .86). To test whether these differences were statistically significant, we constrained the regression coefficients of math and science competence within the multi-group regression model to be equal across the 41 countries. Compared to the freely estimated model ( LogL = -4,561,273.3, df = 492, AIC = 9,123,530.5, BIC = 9,128,410.7), the restricted model was empirically not preferred LogL = -4,564,877.9, df = 412, AIC = 9,130,579.8, BIC = 9,134,917.6; Δχ 2 [80] = 7,209.2, p < .001. These findings lend evidence for the Moderation-Hypothesis.

From a slightly different perspective, the country-specific amount of variance in problem solving scores that is explained by the variation in math and science performance scores ( R 2 ) is strongly associated with the country’s problem solving score ( r = .77, p < .001), which suggests that the contribution of science and math competence to the acquisition of problem solving competence was significantly lower in low-performing countries.

As shown in Table 2 , the regression weights of math and science were significant for all but two countries. Across countries the regression weight for math tended to be higher than the regression weight for science when predicting problem solving competence. This finding indicates a stronger overlap between students’ competences in mathematics and problem solving on the one hand and similarities between the assessments in both domains on the other hand.

Validating the concept of math-science coherence

In order to validate the concept of math-science coherence, which is operationalised as the correlation between math and science scores [ r (M,S)], we explored its relation to problem solving and country characteristics.

Regarding the regression outcomes shown in Table 2 , it is apparent that math-science coherence varied considerably across countries, ranging from .39 to .88 with an average of M(r) = .70 ( SD = .13). Interestingly, countries’ level of coherence in math-science education was substantially related to their problem solving scores ( r = .76, p < .001). An inspection of Figure 1 reveals that this effect was mainly due to countries that both achieve low problem solving scores and show relatively low levels of math-science coherence (see bottom left quadrant in Figure 1 ), whilst amongst the remaining countries the correlational link between math-science coherence and problem solving score was almost zero ( r = -.08, p = .71) b . This pattern extends the moderation perspective on the presumed dependency of problem solving competence from math and science competences.

The relation between math-science coherence and problem solving performance across the 41 countries.

As a result of the moderator analysis, we know that countries not only differ in regard to their average problem-solving scores and level of coherence between math and science, countries also differ in the strengths with which math-science coherence predicts problem solving scores. To better understand the conceptual nature of the link between math-science coherence and problem solving, we now attempt to adjust this relationship for potential confounding effects that country-specific characteristics might have. To this end, we employed linear regression and path analysis with students’ problem-solving scores as outcomes, math-science coherence (i.e., r [M,S]) as predictor, and country characteristics as potential confounders.

To establish whether any of the country characteristics had a confounding effect on the link between math-science coherence and problem solving competence, two criteria had to be met: (1) a reduction of the direct effect of math-science coherence on problem solving scores, and (2) testing the difference between the direct effect within the baseline Model M0 and the effect with the confounding Model M1 (Table 3 ).

Regarding the society-related factors, both the countries’ HDI and their national intelligence were confounders with a positive effect. Furthermore, the countries’ integration of the science curriculum was also positively related to the problem solving performance. Finally, the degree of schools’ autonomy towards educational resources and the implementation of curricula and the frequency of assessments were school-related confounders, the former with a positive effect whilst the latter represents a negative confounder. The direct effect of math-science coherence to problem solving decreased and thus indicated that confounding was present (MacKinnon et al. [ 2000 ]).

These findings provide evidence on the Confounding-Hypothesis and support our expectations on the relation between math-science coherence, problem solving, and country characteristics. We regard these results as evidence for the validity of the math-science coherence measure.

Relating math-science coherence to the capability under-utilisation indices

To advance our understanding of the link between math-science coherence and problem solving scores, we tested the Capability-Utilisation Hypothesis. To this end, we explored the relationship between math-science coherence and the CUU Indices for math and science, respectively. For math competence the average Capability Under-Utilisation Index was rather neutral with M CUUI-Math = -0.001 ( SD = 0.02). This suggests that, on average, all countries sufficiently utilise their students’ math capabilities in facilitating the development of problem solving competence (i.e., transfer). It also suggests that math education across participating countries tends to sufficiently utilise generic problem-solving skills (Figure 2 ). The picture is different for science education. Here, the Capability Under-Utilisation Indices and their variation across the participating countries ( M CUUI-Science = -0.01, SD = 0.04) suggest that in a range of countries knowledge and skills taught in science education tend to be under-utilised in the facilitation of the acquisition of problem solving competence (Figure 3 ).

The relation between math-science coherence and the capability under-utilisation index for math and problem solving scores across the 41 countries.

The relation between math-science coherence and the capability under-utilisation index for science and problem solving scores across the 41 countries.

For math competence, the relative difference to problem solving was not related to math-science coherence ( r = .02, p = .89; Figure 2 ). In contrast, the Capability Under-Utilisation Index for science showed a strong positive correlation with math-science coherence ( r = .76, p < .001; Figure 3 ), indicating that low levels of coherence between math and science education were associated with a less effective transfer of domain-specific knowledge and skills to problem solving.

The present study was aimed at investigating the differences in the contribution of math and science competence to problem solving competence across the 41 countries that participated in the PISA 2003 study (Moderation-Hypothesis). To this end, we proposed the concept of math-science coherence and explored its relationship to problem solving competence and how this relationship is confounded by country characteristics (Confounding-Hypothesis). To further extend our understanding of the link between math-science coherence and problem solving, we introduced the concept of capability-utilisation. Testing the Capability-Utilisation Hypothesis enabled us to identify what may contribute to varying levels of math-science coherence and ultimately the development of problem solving competence.

The contribution of math and science competence across countries

Regarding the prediction of problem solving competence, we found that in most countries, math and science competence significantly contributed to students’ performance in analytical problem solving. This finding was expected based on the conceptualizations of mathematical and scientific literacy within the PISA framework referring to shared cognitive processes such as information processing and reasoning (Kind [ 2013 ]; OECD [ 2005 ]), which are regarded as components of problem solving (Bybee [ 2004 ]; Klahr and Dunbar [ 1988 ]; Mayer [ 2010 ]).

It is noteworthy that, for some of the below-average performing countries, science competence did not significantly contribute to the prediction of problem solving competence. It can be speculated that education in these countries is more geared towards math education and modelling processes in mathematical scenarios, whilst the aspect of problem solving in science is less emphasised (Janssen and Geiser [ 2012 ]). The results of multilevel regression analyses supported this interpretation by showing that math competence was a stronger predictor of problem solving competence. On the one hand, this finding could be due to the design of the PISA tests (Adams [ 2005 ]), since math and problem solving items are designed in such a way that modelling real-life problems is required, whereas science items are mostly domain-specific and linked to science knowledge (Nentwig et al. [ 2009 ]; OECD [ 2004 ]). Moreover, one may argue that math and problem solving items allow students to employ different solution strategies, whereas science items offer fewer degrees of freedom for test takers (Nentwig et al. [ 2009 ]). In particular, the shared format of items in math, science, and problem solving may explain an overlap between their cognitive demands. For instance, most of the items were designed in such a way that students had to extract and identify relevant information from given tables or figures in order to solve specific problems. Hence, these items were static and did not require knowledge generation by interaction or exploration but rather the use of given information in problem situations (Wood et al. [ 2009 ]). In contrast to the domain-specific items in math and science, problem solving items did not require the use of prior knowledge in math and science (OECD [ 2004 ]). In addition, some of the math and science items involved cognitive operations that were specific to these domains. For instance, students had to solve a number of math items by applying arithmetic and combinatorial operations (OECD [ 2005 ]). Finally, since items referred to contextual stimuli, which were presented in textual formats, reading ability can be regarded as another, shared demand of solving the items. Furthermore, Rindermann ([ 2007 ]) clearly showed that the shared demands of the achievement tests in large-scale assessments such as PISA were strongly related to students’ general reasoning skills. This finding is in line with the strong relations between math, science, and problem solving competence, found in our study. The interpretation of the overlap between the three competences can also be interpreted from a conceptual point of view. In light of the competence frameworks in PISA, we argue that there are a number of skills that can be found in math, science, and problem solving: information retrieval and processing, knowledge application, and evaluation of results (Griffin et al. [ 2012 ]; OECD [ 2004 ], [ 2005 ]). These skills point out to the importance of reasoning in the three domains (Rindermann [ 2007 ]). Thus, the empirical overlap between math and problem solving can be explained by shared processes of, what Mayer ([ 2010 ]) refers to as, informal reasoning. On the other hand, the stronger effect of math competence could be an effect of the quality of math education. Hiebert et al. ([ 1996 ]) and Kuo et al. ([ 2013 ]) suggested that math education is more based on problem solving skills than other subjects in school (e.g., Polya [ 1945 ]). Science lessons, in contrast, are often not necessarily problem-based, despite the fact that they often start with a set problem. Risch ([ 2010 ]) showed in a cross-national review that science learning was more related to contents and contexts rather than to generic problem-solving skills. These tendencies might lead to a weaker contribution of science education to the development of problem solving competence (Abd-El-Khalick et al. [ 2004 ]).

In sum, we found support on the Moderation-Hypothesis, which assumed systematic differences in the contribution of math and science competence to problem solving competence across the 41 PISA 2003 countries.

The relation to problem solving

In our study, we introduced the concept of math-science coherence, which reflects the degree to which math and science education are harmonized. Since mathematical and scientific literacy show a conceptual overlap, which refers to a set of cognitive processes that are linked to reasoning and information processing (Fensham and Bellocchi [ 2013 ]; Mayer [ 2010 ]), a significant relation between math-science coherence and problem solving was expected. In our analyses, we found a significant and positive effect of math-science coherence on performance scores in problem solving. In this finding we see evidence for the validity of this newly introduced concept of math-science coherence and its focus on the synergistic effect of math and science education on problem solving. The results further suggest that higher levels of coordination between math and science education has beneficial effects on the development of cross-curricular problem-solving competence (as measured within the PISA framework).

Confounding effects of country characteristics

As another step of validating the concept of math-science coherence, we investigated whether country-specific characteristics that are linked to society-, curriculum-, and school-related factors confounded its relation to problem solving. Our results showed that national intelligence, the Human Development Index, the integration of the science curriculum, and schools’ autonomy were positively linked to math-science coherence and problem solving, whilst a schools’ frequency of assessment had a negative confounding effect.

The findings regarding the positive confounders are in line with and also extend a number of studies on cross-country differences in education (e.g., Blömeke et al. [ 2011 ]; Dronkers et al. [ 2014 ]; Janssen and Geiser [ 2012 ]; Risch [ 2010 ]). Ross and Hogaboam-Gray ([ 1998 ]), for instance, found that students benefit from an integrated curriculum, particularly in terms of motivation and the development of their abilities. In the context of our confounder analysis, the integration of the science curriculum as well as the autonomy to allocate resources is expected to positively affect math-science coherence. At the same time, an integrated science curriculum with a coordinated allocation of resources may promote inquiry-based experiments in science courses, which is assumed to be beneficial for the development of problem solving within and across domains. Teaching science as an integrated subject is often regarded a challenge for teachers, particularly when developing conceptual structures in science lessons (Lang and Olson, [ 2000 ]), leading to teaching practices in which cross-curricular competence is rarely taken into account (Mansour [ 2013 ]; van Merriënboer [ 2013 ]).

The negative confounding effect of assessment frequency suggests that high frequencies of assessment, as it presumably applies to both math and science subjects, contribute positively to math-science coherence. However, the intended or unintended engagement in educational activities associated with assessment preparation tends not to be conducive to effectively developing domain-general problem solving competence (see also Neumann et al. [ 2012 ]).

The positive confounder effect of HDI is not surprising as HDI reflects a country’s capability to distribute resources and to enable certain levels of autonomy (Reich et al. [ 2013 ]). To find national intelligence as a positive confounder is also to be expected as the basis for its estimation are often students’ educational outcome measures (e.g., Rindermann [ 2008 ]) and, as discussed earlier, academic achievement measures share the involvement of a set of cognitive processes (Baumert et al. [ 2009 ]; OECD [ 2004 ]).

In summary, the synergistic effect of a coherent math and science education on the development of problem solving competence is substantially linked to characteristics of a country’s educational system with respect to curricula and school organization in the context of its socio-economic capabilities. Math-science coherence, however, also is linked to the extent to which math or science education is able to utilise students’ educational capabilities.

Math-science coherence and capability-utilisation

So far, discrepancies between students’ performance in math and problem solving or science and problem solving have been discussed as indicators of students’ capability utilisation in math or science (Leutner et al. [ 2012 ]; OECD [ 2004 ]). We have extended this perspective by introducing Capability Under-Utilisation Indices for math and science to investigate the effectiveness with which knowledge and skills acquired in the context of math or science education are transferred into cross-curricular problem-solving competence. The Capability Under-Utilisation Indices for math and science reflect a potential quantitative imbalance between math, science, and problem solving performance within a country, whilst the also introduced concept of math-science coherence reflects a potential qualitative imbalance between math and science education.

The results of our analyses suggest that an under-utilisation of problem solving capabilities in the acquisition of science literacy is linked to lower levels of math-science coherence, which ultimately leads to lower scores in problem solving competence. This interpretation finds resonance in Ross and Hogaboam-Gray’s ([ 1998 ]) argumentation for integrating math and science education and supports the attempts of math and science educators to incorporate higher-order thinking skills in teaching STEM subjects (e.g., Gallagher et al. [ 2012 ]; Zohar [ 2013 ]).

In contrast, the CUU Index for math was not related to math-science coherence in our analyses. This might be due to the conceptualizations and assessments of mathematical literacy and problem solving competence. Both constructs share cognitive processes of reasoning and information processing, resulting in quite similar items. Consequently, the transfer from math-related knowledge and skills to cross-curricular problems does not necessarily depend on how math and science education are harmonised, since the conceptual and operational discrepancy between math and problem solving is rather small.

Math and science education do matter to the development of students’ problem-solving skills. This argumentation is based on the assumption that the PISA assessments in math, science, and problem solving are able to measure students’ competence as outcomes, which are directly linked to their education (Bulle [ 2011 ]; Kind [ 2013 ]). In contrast to math and science competence, problem solving competence is not explicitly taught as a subject. Problem solving competence requires the utilisation of knowledge and reasoning skills acquired in specific domains (Pellegrino and Hilton [ 2012 ]). In agreement with Kuhn ([ 2009 ]), we point out that this transfer does not happen automatically but needs to be actively facilitated. In fact, Mayer and Wittrock ([ 2006 ]) stressed that the development of transferable skills such as problem solving competence needs to be fostered within specific domains rather than taught in dedicated, distinct courses. Moreover, they suggested that students should develop a “repertoire of cognitive and metacognitive strategies that can be applied in specific problem-solving situations” (p. 299). Beyond this domain-specific teaching principle, research also proposes to train the transfer of problem solving competence in domains that are closely related (e.g., math and science; Pellegrino and Hilton [ 2012 ]). In light of the effects of aligned curricula (as represented by the concept of math-science coherence), we argue that educational efforts to increase students’ problem solving competence may focus on a coordinated improvement of math and science literacy and fostering problem solving competence within math and science. The emphasis is on coordinated, as the results of our analyses indicated that the coherence between math and science education, as a qualitative characteristic of a country’s educational system, is a strong predictor of problem solving competence. This harmonisation of math and science education may be achieved by better enabling the utilisation of capabilities, especially in science education. Sufficiently high levels of math-science coherence could facilitate the emergence of educational synergisms, which positively affect the development of problem solving competence. In other words, we argue for quantitative changes (i.e., improve science attainment) in order to achieve qualitative changes (i.e., higher levels of curriculum coherence), which are expected to create effective transitions of subject-specific knowledge and skills into subject-unspecific competences to solve real-life problems (Pellegrino and Hilton [ 2012 ]; van Merriënboer [ 2013 ]).

Finally, we encourage research that is concerned with the validation of the proposed indices for different forms of problem solving. In particular, we suggest studying the facilities of the capability-under-utilisation indices for analytical and dynamic problem solving, as assessed in the PISA 2012 study (OECD [ 2014 ]). Due to the different cognitive demands in analytical and dynamic problems (e.g., using existing knowledge vs. generating knowledge; OECD [ 2014 ]), we suspect differences in capability utilisation in math and science. This research could provide further insights into the role of 21 st century skills as educational goals.

a The differences between students’ achievement in mathematics and problem solving, and science and problem solving have to be interpreted relative to the OECD average, since the achievement scales were scaled with a mean of 500 and a standard deviation of 100 for the OECD countries (OECD [ 2004 ], p. 55). Although alternative indices such as country residuals may also be used in cross-country comparisons (e.g., Olsen [ 2005 ]), we decided to use CUU indices, as they reflect the actual differences in achievement scores.

b In addition, we checked whether this result was due to the restricted variances in low-performing countries and found that neither ceiling nor floor effects in the problem solving scores existed. The problem solving scale differentiated sufficiently reliably in the regions below and above the OECD mean of 500.

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How to master the seven-step problem-solving process

In this episode of the McKinsey Podcast , Simon London speaks with Charles Conn, CEO of venture-capital firm Oxford Sciences Innovation, and McKinsey senior partner Hugo Sarrazin about the complexities of different problem-solving strategies.

Podcast transcript

Simon London: Hello, and welcome to this episode of the McKinsey Podcast , with me, Simon London. What’s the number-one skill you need to succeed professionally? Salesmanship, perhaps? Or a facility with statistics? Or maybe the ability to communicate crisply and clearly? Many would argue that at the very top of the list comes problem solving: that is, the ability to think through and come up with an optimal course of action to address any complex challenge—in business, in public policy, or indeed in life.

Looked at this way, it’s no surprise that McKinsey takes problem solving very seriously, testing for it during the recruiting process and then honing it, in McKinsey consultants, through immersion in a structured seven-step method. To discuss the art of problem solving, I sat down in California with McKinsey senior partner Hugo Sarrazin and also with Charles Conn. Charles is a former McKinsey partner, entrepreneur, executive, and coauthor of the book Bulletproof Problem Solving: The One Skill That Changes Everything [John Wiley & Sons, 2018].

Charles and Hugo, welcome to the podcast. Thank you for being here.

Hugo Sarrazin: Our pleasure.

Charles Conn: It’s terrific to be here.

Simon London: Problem solving is a really interesting piece of terminology. It could mean so many different things. I have a son who’s a teenage climber. They talk about solving problems. Climbing is problem solving. Charles, when you talk about problem solving, what are you talking about?

Charles Conn: For me, problem solving is the answer to the question “What should I do?” It’s interesting when there’s uncertainty and complexity, and when it’s meaningful because there are consequences. Your son’s climbing is a perfect example. There are consequences, and it’s complicated, and there’s uncertainty—can he make that grab? I think we can apply that same frame almost at any level. You can think about questions like “What town would I like to live in?” or “Should I put solar panels on my roof?”

You might think that’s a funny thing to apply problem solving to, but in my mind it’s not fundamentally different from business problem solving, which answers the question “What should my strategy be?” Or problem solving at the policy level: “How do we combat climate change?” “Should I support the local school bond?” I think these are all part and parcel of the same type of question, “What should I do?”

I’m a big fan of structured problem solving. By following steps, we can more clearly understand what problem it is we’re solving, what are the components of the problem that we’re solving, which components are the most important ones for us to pay attention to, which analytic techniques we should apply to those, and how we can synthesize what we’ve learned back into a compelling story. That’s all it is, at its heart.

I think sometimes when people think about seven steps, they assume that there’s a rigidity to this. That’s not it at all. It’s actually to give you the scope for creativity, which often doesn’t exist when your problem solving is muddled.

Simon London: You were just talking about the seven-step process. That’s what’s written down in the book, but it’s a very McKinsey process as well. Without getting too deep into the weeds, let’s go through the steps, one by one. You were just talking about problem definition as being a particularly important thing to get right first. That’s the first step. Hugo, tell us about that.

Hugo Sarrazin: It is surprising how often people jump past this step and make a bunch of assumptions. The most powerful thing is to step back and ask the basic questions—“What are we trying to solve? What are the constraints that exist? What are the dependencies?” Let’s make those explicit and really push the thinking and defining. At McKinsey, we spend an enormous amount of time in writing that little statement, and the statement, if you’re a logic purist, is great. You debate. “Is it an ‘or’? Is it an ‘and’? What’s the action verb?” Because all these specific words help you get to the heart of what matters.

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Simon London: So this is a concise problem statement.

Hugo Sarrazin: Yeah. It’s not like “Can we grow in Japan?” That’s interesting, but it is “What, specifically, are we trying to uncover in the growth of a product in Japan? Or a segment in Japan? Or a channel in Japan?” When you spend an enormous amount of time, in the first meeting of the different stakeholders, debating this and having different people put forward what they think the problem definition is, you realize that people have completely different views of why they’re here. That, to me, is the most important step.

Charles Conn: I would agree with that. For me, the problem context is critical. When we understand “What are the forces acting upon your decision maker? How quickly is the answer needed? With what precision is the answer needed? Are there areas that are off limits or areas where we would particularly like to find our solution? Is the decision maker open to exploring other areas?” then you not only become more efficient, and move toward what we call the critical path in problem solving, but you also make it so much more likely that you’re not going to waste your time or your decision maker’s time.

How often do especially bright young people run off with half of the idea about what the problem is and start collecting data and start building models—only to discover that they’ve really gone off half-cocked.

Hugo Sarrazin: Yeah.

Charles Conn: And in the wrong direction.

Simon London: OK. So step one—and there is a real art and a structure to it—is define the problem. Step two, Charles?

Charles Conn: My favorite step is step two, which is to use logic trees to disaggregate the problem. Every problem we’re solving has some complexity and some uncertainty in it. The only way that we can really get our team working on the problem is to take the problem apart into logical pieces.

What we find, of course, is that the way to disaggregate the problem often gives you an insight into the answer to the problem quite quickly. I love to do two or three different cuts at it, each one giving a bit of a different insight into what might be going wrong. By doing sensible disaggregations, using logic trees, we can figure out which parts of the problem we should be looking at, and we can assign those different parts to team members.

Simon London: What’s a good example of a logic tree on a sort of ratable problem?

Charles Conn: Maybe the easiest one is the classic profit tree. Almost in every business that I would take a look at, I would start with a profit or return-on-assets tree. In its simplest form, you have the components of revenue, which are price and quantity, and the components of cost, which are cost and quantity. Each of those can be broken out. Cost can be broken into variable cost and fixed cost. The components of price can be broken into what your pricing scheme is. That simple tree often provides insight into what’s going on in a business or what the difference is between that business and the competitors.

If we add the leg, which is “What’s the asset base or investment element?”—so profit divided by assets—then we can ask the question “Is the business using its investments sensibly?” whether that’s in stores or in manufacturing or in transportation assets. I hope we can see just how simple this is, even though we’re describing it in words.

When I went to work with Gordon Moore at the Moore Foundation, the problem that he asked us to look at was “How can we save Pacific salmon?” Now, that sounds like an impossible question, but it was amenable to precisely the same type of disaggregation and allowed us to organize what became a 15-year effort to improve the likelihood of good outcomes for Pacific salmon.

Simon London: Now, is there a danger that your logic tree can be impossibly large? This, I think, brings us onto the third step in the process, which is that you have to prioritize.

Charles Conn: Absolutely. The third step, which we also emphasize, along with good problem definition, is rigorous prioritization—we ask the questions “How important is this lever or this branch of the tree in the overall outcome that we seek to achieve? How much can I move that lever?” Obviously, we try and focus our efforts on ones that have a big impact on the problem and the ones that we have the ability to change. With salmon, ocean conditions turned out to be a big lever, but not one that we could adjust. We focused our attention on fish habitats and fish-harvesting practices, which were big levers that we could affect.

People spend a lot of time arguing about branches that are either not important or that none of us can change. We see it in the public square. When we deal with questions at the policy level—“Should you support the death penalty?” “How do we affect climate change?” “How can we uncover the causes and address homelessness?”—it’s even more important that we’re focusing on levers that are big and movable.

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Simon London: Let’s move swiftly on to step four. You’ve defined your problem, you disaggregate it, you prioritize where you want to analyze—what you want to really look at hard. Then you got to the work plan. Now, what does that mean in practice?

Hugo Sarrazin: Depending on what you’ve prioritized, there are many things you could do. It could be breaking the work among the team members so that people have a clear piece of the work to do. It could be defining the specific analyses that need to get done and executed, and being clear on time lines. There’s always a level-one answer, there’s a level-two answer, there’s a level-three answer. Without being too flippant, I can solve any problem during a good dinner with wine. It won’t have a whole lot of backing.

Simon London: Not going to have a lot of depth to it.

Hugo Sarrazin: No, but it may be useful as a starting point. If the stakes are not that high, that could be OK. If it’s really high stakes, you may need level three and have the whole model validated in three different ways. You need to find a work plan that reflects the level of precision, the time frame you have, and the stakeholders you need to bring along in the exercise.

Charles Conn: I love the way you’ve described that, because, again, some people think of problem solving as a linear thing, but of course what’s critical is that it’s iterative. As you say, you can solve the problem in one day or even one hour.

Charles Conn: We encourage our teams everywhere to do that. We call it the one-day answer or the one-hour answer. In work planning, we’re always iterating. Every time you see a 50-page work plan that stretches out to three months, you know it’s wrong. It will be outmoded very quickly by that learning process that you described. Iterative problem solving is a critical part of this. Sometimes, people think work planning sounds dull, but it isn’t. It’s how we know what’s expected of us and when we need to deliver it and how we’re progressing toward the answer. It’s also the place where we can deal with biases. Bias is a feature of every human decision-making process. If we design our team interactions intelligently, we can avoid the worst sort of biases.

Simon London: Here we’re talking about cognitive biases primarily, right? It’s not that I’m biased against you because of your accent or something. These are the cognitive biases that behavioral sciences have shown we all carry around, things like anchoring, overoptimism—these kinds of things.

Both: Yeah.

Charles Conn: Availability bias is the one that I’m always alert to. You think you’ve seen the problem before, and therefore what’s available is your previous conception of it—and we have to be most careful about that. In any human setting, we also have to be careful about biases that are based on hierarchies, sometimes called sunflower bias. I’m sure, Hugo, with your teams, you make sure that the youngest team members speak first. Not the oldest team members, because it’s easy for people to look at who’s senior and alter their own creative approaches.

Hugo Sarrazin: It’s helpful, at that moment—if someone is asserting a point of view—to ask the question “This was true in what context?” You’re trying to apply something that worked in one context to a different one. That can be deadly if the context has changed, and that’s why organizations struggle to change. You promote all these people because they did something that worked well in the past, and then there’s a disruption in the industry, and they keep doing what got them promoted even though the context has changed.

Simon London: Right. Right.

Hugo Sarrazin: So it’s the same thing in problem solving.

Charles Conn: And it’s why diversity in our teams is so important. It’s one of the best things about the world that we’re in now. We’re likely to have people from different socioeconomic, ethnic, and national backgrounds, each of whom sees problems from a slightly different perspective. It is therefore much more likely that the team will uncover a truly creative and clever approach to problem solving.

Simon London: Let’s move on to step five. You’ve done your work plan. Now you’ve actually got to do the analysis. The thing that strikes me here is that the range of tools that we have at our disposal now, of course, is just huge, particularly with advances in computation, advanced analytics. There’s so many things that you can apply here. Just talk about the analysis stage. How do you pick the right tools?

Charles Conn: For me, the most important thing is that we start with simple heuristics and explanatory statistics before we go off and use the big-gun tools. We need to understand the shape and scope of our problem before we start applying these massive and complex analytical approaches.

Simon London: Would you agree with that?

Hugo Sarrazin: I agree. I think there are so many wonderful heuristics. You need to start there before you go deep into the modeling exercise. There’s an interesting dynamic that’s happening, though. In some cases, for some types of problems, it is even better to set yourself up to maximize your learning. Your problem-solving methodology is test and learn, test and learn, test and learn, and iterate. That is a heuristic in itself, the A/B testing that is used in many parts of the world. So that’s a problem-solving methodology. It’s nothing different. It just uses technology and feedback loops in a fast way. The other one is exploratory data analysis. When you’re dealing with a large-scale problem, and there’s so much data, I can get to the heuristics that Charles was talking about through very clever visualization of data.

You test with your data. You need to set up an environment to do so, but don’t get caught up in neural-network modeling immediately. You’re testing, you’re checking—“Is the data right? Is it sound? Does it make sense?”—before you launch too far.

Simon London: You do hear these ideas—that if you have a big enough data set and enough algorithms, they’re going to find things that you just wouldn’t have spotted, find solutions that maybe you wouldn’t have thought of. Does machine learning sort of revolutionize the problem-solving process? Or are these actually just other tools in the toolbox for structured problem solving?

Charles Conn: It can be revolutionary. There are some areas in which the pattern recognition of large data sets and good algorithms can help us see things that we otherwise couldn’t see. But I do think it’s terribly important we don’t think that this particular technique is a substitute for superb problem solving, starting with good problem definition. Many people use machine learning without understanding algorithms that themselves can have biases built into them. Just as 20 years ago, when we were doing statistical analysis, we knew that we needed good model definition, we still need a good understanding of our algorithms and really good problem definition before we launch off into big data sets and unknown algorithms.

Simon London: Step six. You’ve done your analysis.

Charles Conn: I take six and seven together, and this is the place where young problem solvers often make a mistake. They’ve got their analysis, and they assume that’s the answer, and of course it isn’t the answer. The ability to synthesize the pieces that came out of the analysis and begin to weave those into a story that helps people answer the question “What should I do?” This is back to where we started. If we can’t synthesize, and we can’t tell a story, then our decision maker can’t find the answer to “What should I do?”

Simon London: But, again, these final steps are about motivating people to action, right?

Charles Conn: Yeah.

Simon London: I am slightly torn about the nomenclature of problem solving because it’s on paper, right? Until you motivate people to action, you actually haven’t solved anything.

Charles Conn: I love this question because I think decision-making theory, without a bias to action, is a waste of time. Everything in how I approach this is to help people take action that makes the world better.

Simon London: Hence, these are absolutely critical steps. If you don’t do this well, you’ve just got a bunch of analysis.

Charles Conn: We end up in exactly the same place where we started, which is people speaking across each other, past each other in the public square, rather than actually working together, shoulder to shoulder, to crack these important problems.

Simon London: In the real world, we have a lot of uncertainty—arguably, increasing uncertainty. How do good problem solvers deal with that?

Hugo Sarrazin: At every step of the process. In the problem definition, when you’re defining the context, you need to understand those sources of uncertainty and whether they’re important or not important. It becomes important in the definition of the tree.

You need to think carefully about the branches of the tree that are more certain and less certain as you define them. They don’t have equal weight just because they’ve got equal space on the page. Then, when you’re prioritizing, your prioritization approach may put more emphasis on things that have low probability but huge impact—or, vice versa, may put a lot of priority on things that are very likely and, hopefully, have a reasonable impact. You can introduce that along the way. When you come back to the synthesis, you just need to be nuanced about what you’re understanding, the likelihood.

Often, people lack humility in the way they make their recommendations: “This is the answer.” They’re very precise, and I think we would all be well-served to say, “This is a likely answer under the following sets of conditions” and then make the level of uncertainty clearer, if that is appropriate. It doesn’t mean you’re always in the gray zone; it doesn’t mean you don’t have a point of view. It just means that you can be explicit about the certainty of your answer when you make that recommendation.

Simon London: So it sounds like there is an underlying principle: “Acknowledge and embrace the uncertainty. Don’t pretend that it isn’t there. Be very clear about what the uncertainties are up front, and then build that into every step of the process.”

Hugo Sarrazin: Every step of the process.

Simon London: Yeah. We have just walked through a particular structured methodology for problem solving. But, of course, this is not the only structured methodology for problem solving. One that is also very well-known is design thinking, which comes at things very differently. So, Hugo, I know you have worked with a lot of designers. Just give us a very quick summary. Design thinking—what is it, and how does it relate?

Hugo Sarrazin: It starts with an incredible amount of empathy for the user and uses that to define the problem. It does pause and go out in the wild and spend an enormous amount of time seeing how people interact with objects, seeing the experience they’re getting, seeing the pain points or joy—and uses that to infer and define the problem.

Simon London: Problem definition, but out in the world.

Hugo Sarrazin: With an enormous amount of empathy. There’s a huge emphasis on empathy. Traditional, more classic problem solving is you define the problem based on an understanding of the situation. This one almost presupposes that we don’t know the problem until we go see it. The second thing is you need to come up with multiple scenarios or answers or ideas or concepts, and there’s a lot of divergent thinking initially. That’s slightly different, versus the prioritization, but not for long. Eventually, you need to kind of say, “OK, I’m going to converge again.” Then you go and you bring things back to the customer and get feedback and iterate. Then you rinse and repeat, rinse and repeat. There’s a lot of tactile building, along the way, of prototypes and things like that. It’s very iterative.

Simon London: So, Charles, are these complements or are these alternatives?

Charles Conn: I think they’re entirely complementary, and I think Hugo’s description is perfect. When we do problem definition well in classic problem solving, we are demonstrating the kind of empathy, at the very beginning of our problem, that design thinking asks us to approach. When we ideate—and that’s very similar to the disaggregation, prioritization, and work-planning steps—we do precisely the same thing, and often we use contrasting teams, so that we do have divergent thinking. The best teams allow divergent thinking to bump them off whatever their initial biases in problem solving are. For me, design thinking gives us a constant reminder of creativity, empathy, and the tactile nature of problem solving, but it’s absolutely complementary, not alternative.

Simon London: I think, in a world of cross-functional teams, an interesting question is do people with design-thinking backgrounds really work well together with classical problem solvers? How do you make that chemistry happen?

Hugo Sarrazin: Yeah, it is not easy when people have spent an enormous amount of time seeped in design thinking or user-centric design, whichever word you want to use. If the person who’s applying classic problem-solving methodology is very rigid and mechanical in the way they’re doing it, there could be an enormous amount of tension. If there’s not clarity in the role and not clarity in the process, I think having the two together can be, sometimes, problematic.

The second thing that happens often is that the artifacts the two methodologies try to gravitate toward can be different. Classic problem solving often gravitates toward a model; design thinking migrates toward a prototype. Rather than writing a big deck with all my supporting evidence, they’ll bring an example, a thing, and that feels different. Then you spend your time differently to achieve those two end products, so that’s another source of friction.

Now, I still think it can be an incredibly powerful thing to have the two—if there are the right people with the right mind-set, if there is a team that is explicit about the roles, if we’re clear about the kind of outcomes we are attempting to bring forward. There’s an enormous amount of collaborativeness and respect.

Simon London: But they have to respect each other’s methodology and be prepared to flex, maybe, a little bit, in how this process is going to work.

Hugo Sarrazin: Absolutely.

Simon London: The other area where, it strikes me, there could be a little bit of a different sort of friction is this whole concept of the day-one answer, which is what we were just talking about in classical problem solving. Now, you know that this is probably not going to be your final answer, but that’s how you begin to structure the problem. Whereas I would imagine your design thinkers—no, they’re going off to do their ethnographic research and get out into the field, potentially for a long time, before they come back with at least an initial hypothesis.

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Hugo Sarrazin: That is a great callout, and that’s another difference. Designers typically will like to soak into the situation and avoid converging too quickly. There’s optionality and exploring different options. There’s a strong belief that keeps the solution space wide enough that you can come up with more radical ideas. If there’s a large design team or many designers on the team, and you come on Friday and say, “What’s our week-one answer?” they’re going to struggle. They’re not going to be comfortable, naturally, to give that answer. It doesn’t mean they don’t have an answer; it’s just not where they are in their thinking process.

Simon London: I think we are, sadly, out of time for today. But Charles and Hugo, thank you so much.

Charles Conn: It was a pleasure to be here, Simon.

Hugo Sarrazin: It was a pleasure. Thank you.

Simon London: And thanks, as always, to you, our listeners, for tuning into this episode of the McKinsey Podcast . If you want to learn more about problem solving, you can find the book, Bulletproof Problem Solving: The One Skill That Changes Everything , online or order it through your local bookstore. To learn more about McKinsey, you can of course find us at McKinsey.com.

Charles Conn is CEO of Oxford Sciences Innovation and an alumnus of McKinsey’s Sydney office. Hugo Sarrazin is a senior partner in the Silicon Valley office, where Simon London, a member of McKinsey Publishing, is also based.

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The global problem-solving paradox

A woman with a child on her lap is vaccinated by a health professional.

As Secretary-General of the United Nations, I spend much of my time speaking with world leaders and taking the pulse of global trends. It’s clear to me that we are at a defining moment in international relations. Global decision making is plagued by gridlock – and a fundamental paradox lies at the heart of it.

On the one hand, many of today’s global leaders recognize our common threats – COVID, climate, the unregulated development of new technologies. They agree that something needs to be done about them. Yet that common understanding is not matched by common action.

Indeed, divides keep deepening.

We see them everywhere: in the unfair and unequal distribution of vaccines; in a global economic system rigged against the poor; in the utterly inadequate response to the climate crisis; in digital technology and a media landscape that profit from division; and in growing unrest and conflict around the world.

So if the world agrees on the diagnosis of these common problems, why is it unable to effectively treat them?

I see two fundamental reasons.

First, because foreign policy often becomes a projection of internal politics.

As a former Prime Minister, I know that despite good intentions, international affairs can be hijacked by domestic politics. Perceived national interests can easily trump the larger global good.

This impulse is understandable, even if it is wrong-headed in instances where solidarity is in a country’s self-interest.

Vaccines are a prime example.

Everyone understands that a virus like COVID-19 does not respect national borders. We need universal vaccination to reduce the risk of new and more dangerous variants emerging and affecting everyone, in every country.

Instead of prioritizing vaccines for all through a global vaccination plan, governments have acted to safeguard their people. But that is only half a strategy.

Of course, governments must ensure the protection of their own people. But unless they work simultaneously to vaccinate the world, national vaccination plans could be rendered useless as new variants emerge and spread.

Second, many of today’s global institutions or frameworks are outdated or simply weak and the necessary reforms are impeded by geo-political divides.

For example, the authority of the World Health Organization is nowhere near what is required to coordinate the response to global pandemics.

At the same time, international institutions with more power are either paralyzed by division – like the Security Council – or undemocratic – like many of our international financial institutions.

In short — global governance is failing at precisely the moment when the world should be coming together to solve global problems

We need to act together in the national and global self-interest, to protect critical global public goods, like public health and a livable climate, that support humanity’s wellbeing.

Such reforms are essential if we are to deliver on common aspirations for our collective global goals of peace, sustainable development, human rights and dignity for all.

This is a difficult and complex exercise that must take into account questions of national sovereignty.

But doing nothing is not an acceptable option. The world desperately needs more effective and democratic international mechanisms that can solve people’s problems.

As the pandemic has taught us, our fates are tied. When we leave anyone behind, we risk leaving everyone behind. The most vulnerable regions, countries and people are the first victims of this paradox in global policy. But everyone, everywhere is directly threatened.

The good news is that we can do something about our global challenges.

Problems created by humanity can be solved by humanity.

Last September, I issued a report on these issues. Our Common Agenda is a starting point; a roadmap to gather the world together to tackle these governance challenges and reinvigorate multilateralism for the 21st century.

Change won’t be easy, nor will it happen overnight. But we can begin by finding areas of consensus and moving in the direction of progress.

This is our greatest test because so much is at stake.

We are already seeing the consequences. As people start to lose trust in the ability of institutions to deliver, they also risk losing faith in the values that underlie those institutions.

In every corner of the world, we see an erosion of trust and what I fear is

the emergence of a twilight of shared values.

Injustice, inequality, mistrust, racism and discrimination are casting dark shadows across every society.

We must restore human dignity and human decency and respond to people’s anxieties with answers.

In the face of growing inter-connected threats, enormous human suffering, and shared risks, we have an obligation to speak up and act to put out the fire.

António Guterres is the Secretary-General of the United Nations. Blog originally posted on Scoop World.

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Cultural Differences and Problem Solving: An Interview with Jerome Vadon

You may have seen this amazing graphic going viral in the past couple of days.

How did such a simple and funny representation of stereotype become viral so quickly?

To find out more, we interviewed it’s creator – Jerome Vadon.

1. How did you come to think about the “joke” for each country? J.V: Almost 2 years ago I posted my first language-based joke (see it here ). It was a simple one and it got very popular too (way less than the last one, but still good for a first). Later I made a fast sketch to a American friend of mine, “quick and dirty”, on “problem resolution – international techniques”, making fun of the different solutions between US, German, English and French ways of facing the same problem (it was during the crisis). Somehow this sketch ended up on the internet, and slowly became a Meme, as people modified and posted their own version of the initial four countries by adding a fifth of their own. This first sketch never intended to be published. I didn’t put a signature but I knew it was from me… That bugged me for months, then it came back again to me, through Facebook and Twitter on the same day. That was more than I was about to handle. This is how I decided to make it cleaner: the version 1. A few days after, as the sharing started to grow, I thought it was stupid to not go further and have my Facebook friends laugh all together. Then ideas started to pop into my mind… I made an update, the version 2 and then... more than 20000 shares (Facebook & Twitter). As I am quite busy, I did not really gave time to seriously make it. So I decided to take a weekend and to make it more serious. And this Sunday I released version 3. Only 72 hours after the post, V3 is has over 300,000 shares via Facebook, Twitter, Google+, Tumblr and all other networks... Although this is very good for the Ego, it’s more than that, I am so happy to have been able to make people laugh from all around the world, somehow together... I just love the idea!

2. What do you think these “stereotypes” about other cultures say about them AND us? J.V: Stereotypes are wonderful tools: they ease tension between nations, make defaults funny and help us face some of our most characteristic traits. They give us a fair chance to evolve, without getting angry at anyone.

They say that we are just like kids - teasing and laughing gently about each other. Nobody is perfect. And it’s probably better this way? But they also can be a deadly weapon of misleading communication. History is sadly full of examples, and we don’t have to look very far… WWII, South Africa, Serbia. Most ethnic conflicts are based on stereotypes, manipulated in an evil design. As in real life, it depends in which hands the tool is. In the case of stereotypes, humour is necessary, so that everyone, wherever they come from and wherever they are understands well the message "just for fun".

3. Do you think stereotypes are useful in any way? J.V: As soon as they are not intended to be bad or to hurt someone deliberately. Humour is always a good way for auto-critics and send “polite” message to others. Stereotypes are an opportunity for everyone to raise the question: am I really like that? For example, I became fully aware of foreigner's views about the French when I settled in Iceland. Most of my friends (not French) were always making jokes about French, their arrogant way or about their abilities to complain. I've never really thought of myself as "pure" French (which I am) and I have many times taken my distances with the behaviour of my fellow countrymen, as there is no excuse to act such a way. Then I asked myself "Am I really grumpy?" And even though I'm probably less so than the average French or most of my French friends, I discovered that I was much more than my friends in other countries! So, in this case (as often) it was true! I just have to find a way to work on my unsuspected arrogant side, and then I will be the most perfect man in the universe, and humility will be one of my greatest qualities…

4. So are you looking to add more countries? J.V: Yes. I am actually fighting to find free time to finish and release the next V4, and already have ideas for a V5. Maybe a Christmas one. As I usually like to say “shortest jokes are usually… the less long” (that sounds much better in French actually!). Seriously I got several thousand of messages, comments and ideas.

So far, they are all very political, and miss the “funny” points. If stereotypes have to be more or less accurate, they have to be funny somehow and not badly intended. I have, since V3, excellent ones for Afghanistan, Israel and Palestine. I am still thinking about the pros and cons. Eventually I will try to make all countries, with time. Though, there is some ideas are very good, and I will probably use them to update some of the actual countries, but again, people does not see often the complexity of this joke: - It has to be funny. - It has to be accurate (more or less) and understandable by anyone, all around the world, despite culture and background. - It can be acid (or black humour), but it cannot be badly intended. I am not here to judge or take position for anyone (that’s a fine line). There is always a “recto” to any “verso”… I am not one to impose to others my point of view. That said, I want to keep my freedom and ultimately, publish what I think is funny and right.

5. Can people get involved? J.V: Sure. That why I have invited people (since V2) to send me comments, feedback, inputs and ideas. But I never promised to anyone that I will use their ideas (which would be impossible as most of them are contradictory…).

But I did patent the “concept” with an international company, based in Swiss, in order to allow me to bring the project to another level, sort of worldwide crowd sourced jokes. I will keep you update on this very fresh project in my mind… Thank you Jerome for taking the time to speak to us. And we also wanted to share what you also told us earlier, that “laugh (with love maybe) is the common point between all people, from all around the world, regardless of their origin, skin colour, nation, religion, culture and even age. I am not talking about sense of humour, which is deeply related to the previous list. Just the simple joy of laughing”. We look forward to your next versions! Follow Jerome: @jeromevadon

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Development challenges and solutions

The challenges.

UNDP’s work, adapted to a range of country contexts, is framed through three broad development settings. These three development challenges often coexist within the same country, requiring tailored solutions that can adequately address specific deficits and barriers. Underpinning all three development challenges is a set of core development needs, including the need to strengthen gender equality and the empowerment of women and girls, and to ensure the protection of human rights.

Outcome 1: Eradication of poverty in all its forms and dimensions

It's estimated that approximately 700 million people still live on less than US$1.90 per day, a total of 1.3 billion people are multi-dimensionally poor, including a disproportionate number of women and people with disabilities and 80 percent of humanity lives on less than US$10 per day. Increasingly, middle-income countries account for a large part of this trend.

UNDP is looking at both inequalities and poverty in order to leave no one behind, focusing on the dynamics of exiting poverty and of not falling back. This requires addressing interconnected socio-economic, environmental and governance challenges that drive people into poverty or make them vulnerable to falling back into it. The scale and rapid pace of change necessitates decisive and coherent action by many actors at different levels to advance poverty eradication in all forms and dimensions. UNDP works to ensure responses are multisectoral and coherent from global to local.

Outcome 2: Accelerating structural transformations for sustainable development

The disempowering nature of social, economic, and political exclusion results in ineffective, unaccountable, non-transparent institutions and processes that hamper the ability of states to address persistent structural inequalities.

UNDP will support countries as they accelerate structural transformations by addressing inequalities and exclusion, transitioning to zero-carbon development and building more effective governance that can respond to megatrends such as globalization, urbanization and technological and demographic changes.

Outcome 3: Building resilience to crisis and shocks

Some countries are disproportionately affected by shocks and stressors such as climate change, disasters, violent extremism, conflict, economic and financial volatility, epidemics, food insecurity and environmental degradation. Climate-related disasters have increased in number and magnitude, reversing development gains, aggravating fragile situations, and contributing to social upheaval. Conflict, sectarian strife and political instability are on the rise and more than 1.6 billion people live in fragile or conflict-affected settings.

Around 258 million people live outside their countries of origin and 68.5 million are displaced. Disasters and the effects of climate change have displaced more people than ever before – on average 14 million people annually. Major disease outbreaks result in severe economic losses from the effect on livelihoods or decline in household incomes and national GDPs, as demonstrated by the Ebola outbreak in West Africa in 2014-2015.

To return to sustainable development, UNDP is strengthening resilience by supporting governments to take measures to manage risk, prevent, respond and recover more effectively from shocks and crises and address underlying causes in an integrated manner. Such support builds on foundations of inclusive and accountable governance, together with a strong focus on gender equality, the empowerment of women and girls and meeting the needs of vulnerable groups, to ensure that no one is left behind.

The road to success

To fulfill the aims of the Strategic Plan with the multi-dimensionality and complexity that the 2030 Agenda demands, UNDP is implementing six cross-cutting approaches to development, known as Signature Solutions. A robust, integrated way to put our best work – or 'signature' skillset – into achieving the Sustainable Development Goals .

UNDP’s Signature Solutions are cross-cutting approaches to development— for example, a gender approach or resilience approach can be applied to any area of development, or to any of the SDGs.

Keeping people out of poverty

Today, 700 million people live on less than $1.90 per day and a total of 1.3 billion people are multi-dimensionally poor. People stay in or fall back into poverty because of a range of factors—where they live, their ethnicity, gender, a lack of opportunities, and others.

It’s no coincidence that our first Signature Solution relates directly to the first SDG: to eradicate all forms of poverty, wherever it exists. For UNDP, helping people to get out and stay out of poverty is our primary focus. It features in our work with governments, communities and partners across the 170 countries and territories in which we operate.

UNDP interventions help eradicate poverty, such as by creating decent jobs and livelihoods, providing social safety nets, boosting political participation, and ensuring access to services like water, energy, healthcare, credit, and productive assets. Our Signature Solution on poverty cuts across our work on all the SDGs, whether it’s decent work or peace and justice.

Governance for peaceful, just, and inclusive societies

People’s lives are better when government is efficient and responsive. When people from all social groups are included in decision-making that affects their lives, and when they have equal access to fair institutions that provide services and administer justice, they will have more trust in their government.

The benefits of our work on governance are evident in all the areas covered by the SDGs, whether it’s climate action or gender equality. UNDP’s governance work spans a wide range of institutions, from national parliaments, supreme courts, and national civil services through regional and local administrations, to some of the geographically remotest communities in the world. We work with one out of every three parliaments on the planet, help countries expand spaces for people’s participation, and improve how their institutions work, so that all people can aspire to a sustainable future with prosperity, peace, justice and security.

Crisis prevention and increased resilience

Crises know no borders. More than 1.6 billion people live in fragile and/or conflict-affected settings, including 600 million young people. More people have been uprooted from their homes by war and violence and sought sanctuary elsewhere than at any time since the Second World War. Poverty, population growth, weak governance and rapid urbanization are driving the risks associated with such crises.

UNDP helps reduce these risks by supporting countries and communities to better manage conflicts, prepare for major shocks, recover in their aftermath, and integrate risk management into their development planning and investment decisions. The sooner that people can get back to their homes, jobs, and schools, the sooner they can start thriving again. Resilience building is a transformative process of strengthening the capacity of people, communities, institutions, and countries to prevent, anticipate, absorb, respond to and recover from crises. By implementing this Signature Solution, we focus on capacities to address root causes of conflict, reduce disaster risk, mitigate and adapt to climate change impacts, recover from crisis, and build sustainable peace. This has an impact that not only prevents or mitigates crises, but also has an effect on people’s everyday lives across all SDGs.

Environment: nature-based solutions for development

Healthy ecosystems are at the heart of development, underpinning societal well-being and economic growth. Through nature-based solutions, such as the sustainable management and protection of land, rivers and oceans, we help ensure that countries have adequate food and water, are resilient to climate change and disasters, shift to green economic pathways, and can sustain work for billions of people through forestry, agriculture, fisheries and tourism.

A long-standing partner of the Global Environment Facility, and now with the second-largest Green Climate Fund portfolio, UNDP is the primary actor on climate change in the United Nations. Our aim is to help build the Paris Agreement and all environmental agreements into the heart of countries’ development priorities. After all, the food, shelter, clean air, education and opportunities of billions of people depend on getting this right.

Clean, affordable energy

People can’t prosper without reliable, safe, and affordable energy to power everything from lights to vehicles to factories to hospitals. And yet, 840 million people worldwide have no access to electricity, and 2.9 billion people use solid fuels to cook or heat their homes, exposing their families to grave health hazards and contributing to vast deforestation worldwide 3 . In these and other ways, energy is connected to every one of the SDGs.

UNDP helps countries transition away from the use of finite fossil fuels and towards clean, renewable, affordable sources of energy. Our sustainable energy portfolio spans more than 110 countries, leveraging billions of dollars in financing, including public and private sources. With this financial support, we partner with cities and industries to increase the share of renewables in countries’ national energy mix; establish solar energy access to people displaced by conflict; fuel systemic change in the transport industry; and generate renewable ways to light homes for millions of people.

Women's empowerment and gender equality

Women’s participation in all areas of society is essential to make big and lasting change not only for themselves, but for all people. Women and girls make up a disproportionate share of people in poverty, and are more likely to face hunger, violence, and the impacts of disaster and climate change. They are also more likely to be denied access to legal rights and basic services.

UNDP has the ability and responsibility to integrate gender equality into every aspect of our work. Gender equality and women’s empowerment is a guiding principle that applies to everything we do, collaborating with our partner countries to end gender-based violence, tackle climate change with women farmers, and advance female leadership in business and politics.

[1] OECD , States of Fragility 2016: Understanding Violence (Paris, 2016), p. 16. http://dx.doi.org/10.1787/9789264267213-en .

[2] sendai framework for disaster risk reduction 2015-2030, p.9. http://www.unisdr.org/we/inform/publications/43291 ., [3] source: iea, irena, unsd, wb, who, 2019, tracking sdg7: the energy progress report 2019, washington, dc..

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As the world’s only truly universal global organization, the United Nations has become the foremost forum to address issues that transcend national boundaries and cannot be resolved by any one country acting alone.

To its initial goals of safeguarding peace, protecting human rights, establishing the framework for international justice and promoting economic and social progress, in the seven decades since its creation the United Nations has added on new challenges, such as AIDS, big data and climate change.

While conflict resolution and peacekeeping continue to be among its most visible efforts, the UN, along with its specialized agencies, is also engaged in a wide array of activities to improve people’s lives around the world – from disaster relief, through education and advancement of women, to peaceful uses of atomic energy.

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Every child has the right to health, education and protection, and every society has a stake in expanding children’s opportunities in life. Yet, around the world, millions of children are denied a fair chance for no reason other than the country, gender or circumstances into which they are born.

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Democracy is a universally recognized ideal and is one of the core values and principles of the United Nations. Democracy provides an environment for the protection and effective realization of human rights.

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Ending Poverty

At current rates of progress, the world is unlikely to meet the global goal of ending extreme poverty by 2030, with estimates suggesting that nearly 600 million people will still be living in extreme poverty.

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The world is not on track to achieve Sustainable Development Goal 2, Zero Hunger by 2030. The food security and nutritional status of the most vulnerable population groups is likely to deteriorate further due to the health and socio-economic impacts of the COVID-19 pandemic.

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Gender Equality

Women and girls represent half of the world’s population and, therefore, also half of its potential. Gender equality, besides being a fundamental human right, is essential to achieve peaceful societies, with full human potential and sustainable development.

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The United Nations, since its inception, has been actively involved in promoting and protecting good health worldwide. Leading that effort within the UN system is the World Health Organization (WHO), whose constitution came into force on 7 April 1948.

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Promoting respect for human rights is a core purpose of the United Nations and defines its identity as an organization for people around the world. Member States have mandated the Secretary-General and the UN System to help them achieve the standards set out in the UN Charter and the Universal Declaration of Human Rights .

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The UN continues to promote justice and international law across its three pillars of work: international peace and security, economic and social progress and development, and respect for human rights and fundamental freedoms.

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International migration

Since the earliest times, humanity has been on the move. Today, more people than ever before live in a country other than the one in which they were born.

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Oceans and the Law of the Sea

Life itself arose from the oceans. The ocean is vast, some 72 per cent of the earth's surface. Not only has the oceans always been a prime source of nourishment for the life it helped generate, but from earliest recorded history it has served for trade and commerce, adventure and discovery.

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Saving succeeding generations from the scourge of war was the main motivation for creating the United Nations, whose founders lived through the devastation of two world wars.

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In 1950, five years after the founding of the United Nations, world population was estimated at around 2.6 billion people. It reached 5 billion in 1987 and 6 in 1999. In October 2011, the global population was estimated to be 7 billion.

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There were 110 million people forcibly displaced world-wide at the end of June 2023. Among those were 36.4 million refugees, (30.5 million refugees under UNHCR's mandate, and 5.94 million Palestine refugees under UNRWA's mandate). ;

Fresh water sustains human life and is vital for human health. There is enough fresh water for everyone on Earth. However, due to bad economics or poor infrastructure, millions of people (most of them children) die from diseases associated with inadequate water supply, sanitation and hygiene.

As youth are increasingly demanding more just, equitable and progressive opportunities and solutions in their societies, the need to address the multifaceted challenges faced by young people (such as access to education, health, employment and gender equality) have become more pressing than ever.

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The global education challenge: Scaling up to tackle the learning crisis

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Alice albright alice albright chief executive officer - global partnership for education @alicealbright.

July 25, 2019

The following is one of eight briefs commissioned for the 16th annual Brookings Blum Roundtable, “2020 and beyond: Maintaining the bipartisan narrative on US global development.”

Addressing today’s massive global education crisis requires some disruption and the development of a new 21st-century aid delivery model built on a strong operational public-private partnership and results-based financing model that rewards political leadership and progress on overcoming priority obstacles to equitable access and learning in least developed countries (LDCs) and lower-middle-income countries (LMICs). Success will also require a more efficient and unified global education architecture. More money alone will not fix the problem. Addressing this global challenge requires new champions at the highest level and new approaches.

Key data points

In an era when youth are the fastest-growing segment of the population in many parts of the world, new data from the UNESCO Institute for Statistics (UIS) reveals that an estimated 263 million children and young people are out of school, overwhelmingly in LDCs and LMICs. 1 On current trends, the International Commission on Financing Education Opportunity reported in 2016 that, a far larger number—825 million young people—will not have the basic literacy, numeracy, and digital skills to compete for the jobs of 2030. 2 Absent a significant political and financial investment in their education, beginning with basic education, there is a serious risk that this youth “bulge” will drive instability and constrain economic growth.

Despite progress in gender parity, it will take about 100 years to reach true gender equality at secondary school level in LDCs and LMICs. Lack of education and related employment opportunities in these countries presents national, regional, and global security risks.

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Among global education’s most urgent challenges is a severe lack of trained teachers, particularly female teachers. An additional 9 million trained teachers are needed in sub-Saharan Africa by 2030.

Refugees and internally displaced people, now numbering over 70 million, constitute a global crisis. Two-thirds of the people in this group are women and children; host countries, many fragile themselves, struggle to provide access to education to such people.

Highlighted below are actions and reforms that could lead the way toward solving the crisis:

Leadership to jump-start transformation. The next U.S. administration should convene a high-level White House conference of sovereign donors, developing country leaders, key multilateral organizations, private sector and major philanthropists/foundations, and civil society to jump-start and energize a new, 10-year global response to this challenge. A key goal of this decadelong effort should be to transform education systems in the world’s poorest countries, particularly for girls and women, within a generation. That implies advancing much faster than the 100-plus years required if current programs and commitments remain as is.
A whole-of-government leadership response. Such transformation of currently weak education systems in scores of countries over a generation will require sustained top-level political leadership, accompanied by substantial new donor and developing country investments. To ensure sustained attention for this initiative over multiple years, the U.S. administration will need to designate senior officials in the State Department, USAID, the National Security Council, the Office of Management and Budget, and elsewhere to form a whole-of-government leadership response that can energize other governments and actors.
Teacher training and deployment at scale. A key component of a new global highest-level effort, based on securing progress against the Sustainable Development Goals and the Addis 2030 Framework, should be the training and deployment of 9 million new qualified teachers, particularly female teachers, in sub-Saharan Africa where they are most needed. Over 90 percent of the Global Partnership for Education’s education sector implementation grants have included investments in teacher development and training and 76 percent in the provision of learning materials.
Foster positive disruption by engaging community level non-state actors who are providing education services in marginal areas where national systems do not reach the population. Related to this, increased financial and technical support to national governments are required to strengthen their non-state actor regulatory frameworks. Such frameworks must ensure that any non-state actors operate without discrimination and prioritize access for the most marginalized. The ideological divide on this issue—featuring a strong resistance by defenders of public education to tap into the capacities and networks of non-state actors—must be resolved if we are to achieve a rapid breakthrough.
Confirm the appropriate roles for technology in equitably advancing access and quality of education, including in the initial and ongoing training of teachers and administrators, delivery of distance education to marginalized communities and assessment of learning, strengthening of basic systems, and increased efficiency of systems. This is not primarily about how various gadgets can help advance education goals.
Commodity component. Availability of appropriate learning materials for every child sitting in a classroom—right level, right language, and right subject matter. Lack of books and other learning materials is a persistent problem throughout education systems—from early grades through to teaching colleges. Teachers need books and other materials to do their jobs. Consider how the USAID-hosted Global Book Alliance, working to address costs and supply chain issues, distribution challenges, and more can be strengthened and supported to produce the model(s) that can overcome these challenges.

Annual high-level stock take at the G-7. The next U.S. administration can work with G-7 partners to secure agreement on an annual stocktaking of progress against this new global education agenda at the upcoming G-7 summits. This also will help ensure sustained focus and pressure to deliver especially on equity and inclusion. Global Partnership for Education’s participation at the G-7 Gender Equality Advisory Council is helping ensure that momentum is maintained to mobilize the necessary political leadership and expertise at country level to rapidly step up progress in gender equality, in and through education. 3 Also consider a role for the G-20, given participation by some developing country partners.

PISA Scores by Country 2024

Every three years in the worldwide education systems, OECD conducts PISA to test the critical thinking of 15-year-olds in math, science, and reading in over 65 countries that make up 90% of the world’s economies.

What Is PISA? Why Does It Matter?

Programme for International Student Assessment (PISA) is a global program whereby around 600,000 15 year students from different countries are put under a two-hour test to gauge their skills and knowledge, mainly in science, reading, and mathematics. PISA test questions don't gauge memorization of facts but demand that students draw on real-world problem-solving skills and knowledge.

Since a high ranking on PISA corresponds to economic success, researchers have concluded that PISA is one of the indicators of whether school systems are preparing students for the 21st-century global knowledge economy.

U.S. critics of PISA state that the state has a higher percentage of disadvantaged children and therefore cannot fair as well as other OECD countries on the test. Data from the OECD shows that the U.S actually has around the OECD average of disadvantaged students.

However, the U.S has more students from socio-economically advantaged backgrounds. Meaning students in the U.S are better off than the average OECD country.

Typically, PISA is on a three-yearly cycle, but due to the COVID-19 pandemic, PISA 2021 was postponed to 2022.

85 countries are taking part in PISA 2022, intended to take place from 26 July to 16 September 2022. Three key learning subject areas are tested: reading literacy, mathematics, and science. These are accompanied by an innovative domain that varies from cycle to cycle. Mathematics is the key focus, while creative thinking is the innovative domain.

Around 6,300 students aged between 15-years-3-months and 16-years-2-months at the time of assessment will participate in the PISA 2022 Main Survey, conducted under the auspices of the OECD.

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Which country scores highest in PISA?

Frequently asked questions.

2024 Global Learning Challenge

Countrywide Education

Stephanie Sylvestre

Our Organization

Avatar Buddy

What is the name of your solution?

Provide a one-line summary of your solution..

internet + smartphone + school curriculum + Avatar Buddy = countrywide education

In what city, town, or region is your solution team headquartered?

In what country is your solution team headquartered.

United States

What type of organization is your solution team?

For-profit, including B-Corp or similar models

Film your elevator pitch.

What specific problem are you solving.

We are addressing the critical challenge of limited or no access to education for underserved communities, both locally and globally. This issue disproportionately affects millions, with UNESCO estimating that about 258 million children and youth were out of school in 2018, a significant portion of which are in low and middle-income countries. The scale of the problem extends to adults as well, with the Global Education Monitoring Report indicating that 773 million adults worldwide lack basic literacy skills, severely limiting their employment opportunities and ability to participate fully in society.

Our solution, Tutoring Buddy, is specifically designed to tackle the barriers these communities face, including financial constraints, lack of technological access, and the absence of culturally relevant content. By providing an AI-driven, accessible educational platform, we aim to reach individuals who are traditionally marginalized in the education system. Our tool's compatibility with low-bandwidth internet and a wide range of devices ensures that even those with minimal technological access can benefit. Furthermore, by offering content at no or low cost, we remove the financial barriers to education.

The factors contributing to the educational access problem that our solution addresses include:

Technological Barriers: Many underserved communities have limited access to high-speed internet and modern devices. Tutoring Buddy's low-bandwidth compatibility directly addresses this issue.
Financial Constraints: The high cost of education and training programs is a significant barrier. Our partnerships with philanthropic organizations and government grants help make Tutoring Buddy affordable or free.
Cultural and Linguistic Relevance: Lack of culturally relevant content can disengage learners. Tutoring Buddy incorporates diverse perspectives and languages, making learning more inclusive.

Globally, the need for accessible education is immense, with the potential to impact billions. Our focus on scalability and continuous improvement means that Tutoring Buddy has the potential to expand its reach, adapting to the evolving needs of learners worldwide and making a significant dent in the global education gap.

What is your solution?

Tutoring Buddy is an innovative, AI-driven educational solution designed to provide personalized learning experiences to individuals with limited or no access to traditional education. At its core, Tutoring Buddy leverages generative AI and proprietary small language models to create adaptive learning paths tailored to each user's needs, learning style, and pace.

What It Is : Tutoring Buddy is a digital learning assistant that offers a wide range of educational content, from basic literacy to advanced subjects like AI Engineering and Cyber Defense. It's accessible on various devices, including smartphones, tablets, and computers, ensuring users can learn anywhere, anytime.

What It Does : By conducting an initial assessment of the learner's knowledge and goals, Tutoring Buddy dynamically adjusts the difficulty and type of content provided, ensuring a continuously engaging and effective learning experience. It supports multiple languages and can translate educational content on the fly, making learning accessible to a global audience.

How It Works : Using advanced AI, Tutoring Buddy analyzes user interactions to understand learning patterns and preferences. This data informs the creation of a customized learning journey for each user, incorporating interactive exercises, real-world case studies, and periodic assessments to measure progress. Its cloud-based architecture allows for seamless updates and scalability, ensuring the platform evolves with the changing needs of learners.

Technology Used : The backbone of Tutoring Buddy is a combination of generative AI for content creation, a small language model for personalized learning experiences, and a digital persona feature that simulates human-like interaction, making learning more engaging. Accessibility features, such as voice commands and image reading capabilities, ensure that learners with disabilities can also benefit from the platform.

Tutoring Buddy is more than just an educational tool; it's a comprehensive learning companion designed to make education accessible, engaging, and effective for everyone, regardless of their background or circumstances.

Who does your solution serve, and in what ways will the solution impact their lives?

Our target population comprises indigenous people in Latin American countries, as well as communities in African and Southeast Asian nations, living in both urban and rural areas. These groups are often significantly underserved in the educational sector due to a combination of factors including geographical isolation, economic constraints, linguistic diversity, and a lack of culturally relevant educational resources. Many individuals in these communities face barriers to accessing quality education, such as limited availability of schools, insufficient infrastructure, and the absence of learning materials that reflect their cultural heritage and languages.

Who They Are: The individuals we aim to serve are diverse in culture, language, and living conditions. They include children and adults who are eager to learn and improve their lives but are hindered by the lack of accessible, relevant educational opportunities. Many from these communities are also looking to gain skills that would improve their employability and enable them to contribute more significantly to their local economies.

Current Challenges:

Geographical Isolation: Many live in remote areas where traditional schools are scarce or too far to access regularly.
Economic Constraints: The cost of education, including transportation, uniforms, and materials, is often prohibitively expensive for many families.
Linguistic Diversity: Standard educational content is rarely available in indigenous or local languages, creating a significant barrier to learning.
Cultural Relevance: Educational materials that do not reflect the unique cultures, values, and experiences of these populations can be disengaging and ineffective.

How Tutoring Buddy Addresses Their Needs:

Accessibility: By being accessible on low-bandwidth internet and compatible with a wide range of devices, Tutoring Buddy ensures that learners in remote or rural areas can access quality education.
Affordability: Offering the platform at a low cost or for free, especially to users from underserved communities, removes financial barriers to education.
Culturally Relevant Content: Tutoring Buddy includes educational materials developed with cultural relevance in mind, incorporating diverse perspectives and examples that resonate with learners from various backgrounds. This approach not only enhances engagement but also helps learners see the relevance of their education to their lives and communities.
Language Inclusion: Supporting multiple languages and featuring content in indigenous and local languages make learning more accessible and effective for these communities.

By addressing these specific needs, Tutoring Buddy aims to directly and meaningfully improve the lives of our target population, empowering them with the education and skills needed to thrive in a rapidly changing world.

How are you and your team well-positioned to deliver this solution?

Our team, led by Stephanie, is uniquely positioned to design and deliver the Tutoring Buddy solution to our target populations, largely due to our deep personal connections and understanding of the communities we aim to serve. Stephanie's background and volunteer experiences are central to our team's insight and approach.

Stephanie's Connection to the Community: Stephanie grew up in Belize, a country with a rich tapestry of cultures, including indigenous communities. Her upbringing in Belize has provided her with a firsthand understanding of the challenges faced by those in similar contexts across Latin America, Africa, and Southeast Asia. This personal experience is invaluable in guiding our project's direction and ensuring that our solutions are genuinely impactful and relevant.

Throughout her life, Stephanie has been actively involved in volunteer work, focusing on educational and developmental programs within underserved communities. Her volunteer experiences have not only deepened her understanding of the specific needs of these populations but also highlighted the importance of culturally sensitive and accessible educational solutions. This background has instilled in her a profound commitment to leveraging technology to bridge educational gaps.

Team Representation and Community Input: Our team is composed of individuals from diverse backgrounds, including members who have lived in or have direct ties to the communities we aim to serve. This diversity within our team ensures a wide range of perspectives and insights, enriching the development and implementation of Tutoring Buddy.

In designing Tutoring Buddy, we have prioritized meaningful engagement with the communities we intend to serve. This has involved:

Community Workshops: Conducting workshops to gather input on the types of educational content most needed and desired.
Feedback Loops: Establishing ongoing feedback mechanisms to continuously adapt and refine our solution based on direct community input.
Cultural Advisors: Working with cultural advisors to ensure that our content is not only linguistically but also culturally relevant and respectful.

Guided by Community Agendas: Our approach to developing Tutoring Buddy has been deeply informed by the agendas and priorities of the communities we serve. By listening to their needs and aspirations, we have tailored our solution to not only provide access to education but to do so in a way that respects and celebrates their cultural identities. This community-guided approach ensures that Tutoring Buddy is not just an educational tool but a platform that empowers learners to connect with their heritage and the global community.

Our team's proximity to and representation of our target communities, spearheaded by Stephanie's personal experiences and volunteer work, make us the right people to deliver this solution. Our commitment to being guided by the communities' input, ideas, and agendas ensures that Tutoring Buddy will be a meaningful and impactful educational resource.

Which dimension of the Challenge does your solution most closely address?

Which of the un sustainable development goals does your solution address.

4. Quality Education
8. Decent Work and Economic Growth
10. Reduced Inequalities

What is your solution’s stage of development?

Please share details about why you selected the stage above..

Our journey with Tutoring Buddy has been marked by significant milestones in development, testing, and user engagement. To date, we have built a comprehensive, AI-driven educational solution that offers personalized learning experiences across a wide range of subjects and skills. Our solution leverages advanced algorithms to adapt content according to individual learning styles, pace, and language preferences, ensuring accessibility and inclusivity for a diverse user base.

Development and Testing : In the initial phases, we focused on developing core functionalities, including the adaptive learning algorithm, language support features, and user interface design optimized for ease of use across various devices. We conducted extensive beta testing with a small group of users from our target communities to refine these features, incorporating their feedback to enhance user experience and engagement.

145 User Research Study in 2022 : A pivotal moment in our journey was the research study we conducted in 2022, involving 145 users from our target populations. This study was designed to evaluate the effectiveness of Tutoring Buddy in improving learning outcomes and engagement. Participants were selected to represent a broad spectrum of our target demographic, including individuals with backgrounds from indigenous communities in Latin America, as well as communities in African and Southeast Asian countries.

The study provided invaluable insights into the learning needs and preferences of our users, allowing us to further tailor Tutoring Buddy to better meet their needs. The feedback was overwhelmingly positive, with participants reporting significant improvements in their understanding of subjects, increased confidence in their learning abilities, and a high level of engagement with the solution.

Customers and Beneficiaries Served : To date, Tutoring Buddy has served 19 paying customers, reaching approximately 2,850 users through these engagements. These users include both direct beneficiaries, such as students and adult learners, and indirect beneficiaries, such as educators and organizations utilizing Tutoring Buddy to supplement their educational programs. Our paying customers have been instrumental in conducting pilots within their communities, providing us with further opportunities to assess and refine our solution in real-world settings.

The impact of our work has been tangible, with users reporting not only academic improvements but also increased access to educational opportunities that were previously out of reach. Our research and user feedback underscore the potential of Tutoring Buddy to make a meaningful difference in the lives of underserved communities, driving us to continue expanding and improving our platform.

Our accomplishments with Tutoring Buddy so far include the successful development and testing of a highly adaptive and inclusive educational platform, a comprehensive research study with 145 users that validated our approach, and the engagement of 19 paying customers, extending our reach to nearly 3,000 users. These achievements are a testament to our commitment to providing accessible, high-quality education to marginalized communities worldwide.

Why are you applying to Solve?

Tutoring Buddy is designed with the ambitious goal of addressing key contributors to poverty by providing accessible, high-quality education that empowers individuals to improve their economic circumstances. We believe in the transformative power of Tutoring Buddy to provide educational solution that can help to eradicate poverty in a lasting, cost-effective, and scalable manner. However, to fully realize this potential, we must navigate and overcome several barriers, where the support from Solve could be instrumental.

Financial Barriers : One of the primary challenges we face is securing sustainable funding to support the expansion of Tutoring Buddy, particularly in reaching more underserved communities. Financial support from Solve and its partners could help us scale our operations, enhance our technological infrastructure, and subsidize costs for users who cannot afford our services, thereby extending our reach to more learners in need.

Legal and Regulatory Barriers : Expanding Tutoring Buddy into new regions involves navigating complex legal and regulatory landscapes, particularly concerning data protection, intellectual property, and educational standards. Legal guidance and support from Solve's network could help us effectively manage these challenges, ensuring compliance and protecting our users and content creators.

Cultural Barriers : Our commitment to providing culturally relevant content requires a deep understanding of the diverse communities we serve. Collaborating with Solve's global network could connect us with local partners and experts who can offer insights and guidance on cultural nuances, helping us tailor our approach to be more inclusive and effective.

Market Barriers : Building awareness and trust in Tutoring Buddy among our target populations, especially in regions with limited access to technology or skepticism about online learning, is a significant challenge. Marketing support and partnerships facilitated by Solve could help us reach and engage these communities more effectively, demonstrating the value and impact of our solution.

We hope Solve can help us overcome these barriers through a combination of monetary support, technical guidance, legal advice, cultural insights, and market access. By leveraging Solve's network and resources, we can accelerate our mission to eradicate poverty through education, making Tutoring Buddy an even more powerful tool for social change.

In which of the following areas do you most need partners or support?

Product / Service Distribution (e.g. delivery, logistics, expanding client base)
Public Relations (e.g. branding/marketing strategy, social and global media)

Who is the Team Lead for your solution?

What makes your solution innovative.

Our solution, Tutoring Buddy, introduces a novel approach to educational access and equity, leveraging Generative AI to personalize learning experiences for underserved communities. Unlike traditional educational tools that offer a one-size-fits-all curriculum, Tutoring Buddy uses advanced algorithms to adapt content, pace, and learning styles to each individual's needs, ensuring that learners are not just recipients of information but active participants in their educational journey.

Innovative Approach: Tutoring Buddy's core innovation lies in its ability to integrate seamlessly into the daily lives of learners, providing them with access to quality education regardless of their geographical location or socio-economic status. By utilizing mobile technology, our solution overcomes significant barriers to education, such as lack of access to quality schools and experienced teachers. This mobile-first strategy ensures that learning can happen anytime, anywhere, making education truly accessible to all.

Catalyzing Broader Positive Impacts: Tutoring Buddy has the potential to catalyze broader positive impacts in the educational technology space by serving as a model for how technology can be used to address educational disparities. Our success can inspire other innovators and educators to explore how AI and mobile technology can be leveraged to create more inclusive and adaptive learning environments. Furthermore, by demonstrating the effectiveness of personalized learning at scale, we can encourage policymakers and educational institutions to adopt similar approaches, leading to systemic changes in how education is delivered and accessed.

Changing the Market/Landscape: The introduction of Tutoring Buddy into the market is poised to disrupt the traditional educational landscape significantly. By prioritizing the needs of underserved communities, we are not only addressing a critical gap in the market but also challenging other players in the space to reconsider their target audiences and the inclusivity of their solutions. As Tutoring Buddy gains traction, we anticipate a shift towards more equitable educational technologies that prioritize accessibility and personalization. This shift could lead to increased investment in technologies that support underserved learners, further driving innovation and competition in the space.

Moreover, Tutoring Buddy's data-driven approach to learning and improvement sets a new standard for accountability and effectiveness in educational technologies. By continuously collecting and analyzing data on learner engagement and outcomes, we can provide valuable insights into the most effective teaching practices and learning strategies. This emphasis on evidence-based improvement can encourage a more results-oriented culture in the educational technology sector, leading to higher quality and more impactful solutions.

Tutoring Buddy represents a significant leap forward in the quest to make quality education accessible to all. By harnessing the power of Generative AI and mobile technology, we are not only providing a solution to a pressing problem but also paving the way for a more inclusive, adaptive, and effective educational landscape. Our approach has the potential to inspire broader positive impacts, driving systemic change and encouraging a shift towards more equitable educational technologies.

Describe in simple terms how and why you expect your solution to have an impact on the problem.

Our solution, Tutoring Buddy, is designed to bridge educational gaps for underserved communities through personalized, AI-driven learning experiences. Here's a simplified breakdown of our theory of change:

Activities:

Development of Personalized Learning Paths: Using GenAI, we create customized learning experiences that adapt to each learner's pace, preferences, and performance.
Community Engagement and Feedback Loops: We actively engage with learners and educators in underserved communities to gather feedback and continuously refine our solution.
Accessibility and Inclusivity Enhancements: We ensure Tutoring Buddy is accessible on various devices and inclusive to learners of different backgrounds and abilities.

Immediate Outputs:

Increased Engagement: Learners find the personalized content more engaging, leading to higher participation rates.
Improved Accessibility: With Tutoring Buddy available on multiple devices, more learners in underserved communities can access quality education.
Enhanced Learning Outcomes: Early assessments show learners using Tutoring Buddy demonstrate improved understanding and retention of material.

Longer-term Outcomes:

Reduced Educational Disparities: Over time, learners from underserved communities achieve educational outcomes comparable to those from more privileged backgrounds.
Empowered Learners: Individuals gain the skills and confidence needed to pursue higher education or enter the workforce, leading to improved economic opportunities.
Informed Educational Practices: Data collected from Tutoring Buddy informs educators and policymakers about effective personalized learning strategies, influencing broader educational reforms.

Evidence Supporting Links:

Third-party Research: Studies on personalized learning indicate it can significantly improve student achievement, particularly in mathematics and reading.
Feedback from Target Population: Interviews and surveys with our learners highlight the value of personalized learning paths in maintaining their interest and improving comprehension.
Pilot Program Results: Our initial pilot showed an increase in learning outcomes for participants using Tutoring Buddy compared to traditional learning methods.

By aligning our activities with clear, measurable outputs and outcomes, and grounding our approach in evidence, we are confident Tutoring Buddy will make a significant impact on reducing educational disparities in underserved communities. This theory of change not only guides our strategy but also ensures we remain focused on achieving tangible benefits for our target population.

What are your impact goals for your solution and how are you measuring your progress towards them?

Our primary impact goal for Tutoring Buddy is to significantly enhance the educational outcomes and life opportunities for individuals in underserved communities through personalized, GenAI-driven learning experiences. We aim to transform lives by making quality education accessible and engaging, thereby empowering learners with the skills, confidence, and knowledge necessary to succeed in their personal and professional lives.

Measuring Progress Towards Impact Goals:

To gauge our progress towards these impact goals, we employ several specific indicators:

1. Learner Engagement and Satisfaction: We measure time spent using the tool, course completion rates, and feedback through surveys to assess how engaging and satisfying learners find the Tutoring Buddy experience.

2. Learning Outcomes and Skill Acquisition: Pre- and post-assessment scores help us evaluate the improvement in learners' understanding and mastery of subjects. We track progress in key areas such as problem-solving, critical thinking, and subject-specific knowledge.

3. Confidence and Empowerment: Through qualitative interviews and surveys, we collect learners' self-reported increases in confidence and their willingness to try new things. For instance, one learner reported feeling more confident to explore new subjects and challenges after using Tutoring Buddy.

4. Application of Skills: We monitor the real-world application of skills learned through Tutoring Buddy, such as improvements in writing, communication, and analytical thinking. One learner shared that her writing improved significantly; where Tutoring Buddy initially suggested extensive edits, it now only recommends changing a few words.

5. Educational and Career Advancement: We track the number of learners who advance to higher education or secure better job opportunities as a direct result of their improved skills and confidence from using Tutoring Buddy.

Evidence of Impact:

· Increased Confidence: A learner reported that after engaging with Tutoring Buddy, they felt more confident in their abilities and were more willing to take on new challenges and opportunities.

· Enhanced Understanding: Another learner could better explain complex material to peers, indicating a deeper understanding and mastery of the subject matter.

· Improved Writing Skills: A significant testament to our impact is a learner who experienced substantial improvement in writing skills. Initially, Tutoring Buddy's AI-driven feedback suggested numerous edits to her documents. Over time, as her writing improved, the suggestions diminished to changing just two words, showcasing the personalized learning path's effectiveness in enhancing her writing abilities.

To ensure we are on track to meet our impact goals, we continuously analyze these indicators, adjusting our strategies and interventions as needed. This data-driven approach allows us to refine Tutoring Buddy to better serve our learners' needs, ensuring we are making a transformational impact on their lives.

Describe the core technology that powers your solution.

Tutoring Buddy is powered by a sophisticated blend of technologies, including Generative AI, Large Language Models (LLMs), proprietary Small Language Models (SLMs), Digital Personas, and advanced translation capabilities. These technologies synergize to create a highly personalized, adaptive, and accessible learning environment tailored to the unique needs of each user. Here's an expanded overview of each core technology, incorporating the translation capabilities and the nature of Digital Personas as digital versions of human teachers:

Generative AI:

Customized Learning Paths: Utilizes Generative AI to dynamically generate content and exercises that adapt in real-time to the learner's progress, ensuring that the material remains challenging yet achievable.
Dynamic Adaptation: Modifies the learning path based on the learner's interactions, feedback, and performance, ensuring that the educational content is always relevant and engaging.

Large Language Models (LLMs):

Content Generation: Employs LLMs to produce a wide range of educational materials, from reading passages and practice questions to interactive scenarios, leveraging their ability to understand and generate human-like text.
Natural Language Understanding and Interaction: Enables Tutoring Buddy to understand and respond to natural language inputs from users, facilitating a more interactive and conversational learning experience.

Small Language Models (SLMs):

Tailored Educational Content: The proprietary SLMs access proprietary and customized training data, making the learning experience even more personalized and relevant to the learner's goals and background. These models are optimized for specific subjects or skill sets.
Efficiency and Specialization: Offers the benefits of AI-driven personalization and content generation with a focus on efficiency and reduced computational requirements for faster responses and more specialized content creation.

Digital Personas:

Personalized Interaction: Digital Personas are digital versions of human teachers, created through a process where educators complete a personality questionnaire and make a short recording. These personas, powered by the SLM, simulate interaction with a real instructor, providing a more personalized and engaging learning experience.
24/7 Accessibility: Ensures that learners have access to their "teachers" at any time, enhancing the learning experience by providing constant support and feedback.

Translation Capabilities:

Language Accessibility: Tutoring Buddy features built-in translation capabilities that automatically translate content into the learner's language of choice. This ensures inclusivity and accessibility for learners from diverse linguistic backgrounds, allowing them to engage with the content in the language they are most comfortable with.
Multilingual Support: The solution’s ability to translate on the fly into any language enhances the usability and reach of Tutoring Buddy, making quality education accessible to a global audience.

By integrating these advanced technologies, Tutoring Buddy offers an innovative solution to education, providing effective, engaging, and inclusive learning experiences. The combination of Generative AI, LLMs, SLMs, Digital Personas, and translation capabilities positions Tutoring Buddy as a leading educational technology tool, ready to meet the evolving needs of learners worldwide.

Which of the following categories best describes your solution?

A new application of an existing technology

Please select the technologies currently used in your solution:

Artificial Intelligence / Machine Learning
Software and Mobile Applications

If your solution has a website or an app, provide the links here:

https://avatarbuddy.ai, https://avatarbuddy.cc/GenAIImpact

In which countries do you currently operate?

Which, if any, additional countries will you be operating in within the next year.

South Africa

How many people work on your solution team?

Our organization adopts a unique structure to minimize costs and enhance cost-effectiveness. We forgo traditional employment models, compensating our 7 C-level executives through equity or commission, aligning their rewards with our success. Our 15 junior staff are paid hourly as independent contractors under 1099 arrangements. This approach not only keeps costs low but also ensures agility and adaptability in our operations. It motivates our team, aligns with our growth, and provides the flexibility to scale our workforce as needed, making our solution more affordable to deploy.

How long have you been working on your solution?

Our journey began in 2016, marking the inception of our initial concept. It was a period of ideation and conceptualization, where the foundational ideas were laid. 2019, we transitioned into a more intensive phase of research, dedicating ourselves to understanding the intricacies of our solution and its potential impact. This research phase culminated in the development of a prototype in 2021, a significant milestone that propelled us closer to our goal. In 2023, after years of dedication, innovation, and refinement, we successfully launched our solution. This journey, spanning over eight years, reflects our commitment to creating a transformative solution.

Tell us about how you ensure that your team is diverse, minimizes barriers to opportunity for staff, and provides a welcoming and inclusive environment for all team members.

Our commitment to diversity and inclusivity is deeply embedded in our team dynamics and operational ethos, with a significant focus on uplifting Black and Brown communities and fostering an environment that supports underrepresented groups. Our founders proudly identify as a lesbian, a woman, and an immigrant, reflecting the rich diversity and experiences that shape our organizational culture. Approximately 90% of our team members identify as Black or Brown, underscoring our dedication to creating opportunities for these communities.

Recruitment and Hiring Practices: We employ inclusive recruitment strategies, actively partnering with organizations that serve Black and Brown communities. This approach not only enriches our talent pool but also ensures our hiring process is equitable. Our collaboration with these organizations makes it easier to reach and engage underrepresented groups, including immigrants, of whom 60% make up our team, and women, who represent 80% of our workforce.

Professional Development and Growth: We are committed to the professional advancement of our team, particularly focusing on supporting the career trajectories of Black and Brown individuals, immigrants, and women. We offer tailored training, workshops, and mentorship programs to ensure all team members have the resources they need to succeed.

Inclusive Culture: Our organizational culture celebrates diversity, with respect, empathy, and open communication at its core. We encourage team members to share their ideas and feedback, fostering a collaborative environment where everyone feels valued and heard. Regular team-building activities and inclusive events celebrate our diversity, reinforcing our commitment to an inclusive environment.

Fully Remote Work Arrangements: Recognizing the diverse needs of our team, we offer 100% remote work arrangements. This approach helps minimize barriers to participation, ensuring that all team members, regardless of their background, can maintain a healthy work-life balance.

Continuous Improvement: We maintain an ongoing dialogue about diversity, equity, and inclusion, regularly assessing our practices to enhance our inclusivity and accessibility. Feedback from our team, which includes a significant representation of Black and Brown individuals, immigrants, and women, is invaluable in guiding our efforts.

By embedding these principles into every aspect of our operations, we strive to create a workplace that not only values diversity but actively promotes the success and well-being of every team member, with a particular emphasis on supporting the communities our founders and the majority of our team represent.

What is your business model?

Our business model is dedicated to providing educational support and resources to marginalized communities, focusing on delivering accessible, culturally relevant, and impactful learning experiences. We aim to bridge the educational gap faced by these communities, including Black and Brown individuals, immigrants, women, and members of the LGBTQ+ community, by offering tailored educational services that meet their unique needs and circumstances.

Value Proposition:

For Learners: We offer an inclusive and supportive learning environment that empowers marginalized communities to achieve their educational and career goals. Our services are designed to be accessible to all, regardless of their financial situation or background, providing them with the tools and resources they need to succeed.
For Educational Institutions and Nonprofits: We partner with schools, colleges, and nonprofit organizations to enhance their educational offerings, making them more inclusive and accessible to marginalized students. Our solutions help these institutions expand their reach and impact, contributing to a more equitable educational landscape.

Products and Services:

Tutoring Buddy: A digital platform that provides personalized tutoring and mentorship, leveraging advanced technology to offer support in various subjects and skills at different educational levels. This solution is designed to be accessible on low-bandwidth internet and compatible with a wide range of devices.
Culturally Relevant Content: Our educational materials are developed with cultural relevance in mind, incorporating diverse perspectives and examples that resonate with learners from various backgrounds. This approach not only enhances engagement but also helps learners see the relevance of their education to their lives and communities.
Community Engagement and Support: We actively engage with underserved and underrepresented communities through partnerships with local organizations, providing ongoing support and resources to help learners navigate their educational journey. This includes mentorship programs, community study groups, and career counseling services.

Delivery Method: Our educational support services are delivered through a digital solution that ensures ease of access for learners, regardless of their location or the devices they own. This platform is designed to be intuitive, user-friendly, and secure, with a focus on privacy.

Market Need: Marginalized communities often face significant barriers to accessing quality education, including financial constraints, limited access to technology, and a lack of culturally relevant content. Our services address these challenges by providing flexible, accessible, and relevant educational support, empowering learners to overcome obstacles and achieve their full potential.

Revenue Model: We generate revenue through subscription-based models tailored to the needs of our clients. This includes:

Per User Subscription: For larger organizations that prefer a scalable solution based on the number of employees using the service.
Flat Fee Subscription: For organizations seeking a comprehensive solution for all their employees, offering unlimited access to our services.

Do you primarily provide products or services directly to individuals, to other organizations, or to the government?

What is your plan for becoming financially sustainable, and what evidence can you provide that this plan has been successful so far.

Our approach to achieving financial sustainability is strategically designed to leverage a combination of self-funding, external fundraising, in-kind contributions, revenue from sales, and a carefully managed cost structure. This multifaceted strategy ensures a solid financial foundation, enabling us to expand our educational support services to marginalized communities while maintaining affordability and accessibility.

Financial Overview:

· Self-Funding: We have invested $115,000 of our own funds into the organization. This initial investment demonstrates our commitment to our mission and provides us with the flexibility to develop our core offerings without immediate external pressures.

· Friends and Family Round: We have successfully raised $35,000 through a friends and family funding round. This support underscores the belief in our mission by those closest to us and provides essential early-stage capital to fuel our growth.

· In-Kind Development Service: A significant boost to our development efforts has come from $618,000 worth of in-kind development services. This contribution has allowed us to build and refine our digital solution, significantly reducing our upfront costs for technology development.

· Intern Work: We have received $230,000 in grants to cover intern work, investing in the next generation of professionals while efficiently scaling our operations. This approach not only supports our growth but also aligns with our educational mission by providing real-world experience to emerging talents.

· Revenue from Sales: Our services have generated $125,000 in sales, validating the demand for our offerings and our ability to deliver value to our customers. This revenue is a critical component of our financial strategy, providing us with the resources to reinvest in our mission.

Strategic Plans for Growth:

· Pipeline Development: We are actively working our pipeline with the potential to scale to $2.5 million by December 2024. This growth trajectory is based on expanding our service offerings, entering new markets, and securing additional contracts with educational institutions and government agencies.

· Cost Management: Our unique organizational structure is designed to keep costs low. By not giving away our product for free, we ensure that we can cover our expenses while still offering competitive pricing. This approach allows us to maintain financial health and invest in areas that will drive further growth.

· Sustainable Revenue Model: Our revenue model is built on selling high-quality educational services directly to consumers, educational institutions, and government.

This model ensures a steady income stream while allowing us to maintain control over our pricing and product development.

Evidence of Success and Future Outlook:

The combination of self-funding, external fundraising, in-kind contributions, and revenue from sales has positioned us well for future growth. Our ability to manage costs effectively, coupled with a strategic focus on expanding our service offerings and market presence, sets the stage for significant scaling by the end of 2024.

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Justice Dashboard

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The 7 most promising categories of justice innovations, that have the potential to increase access to justice for millions of people around the world.

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Rules of procedure, public-private partnerships, creative sourcing of justice services, and new sources of revenue and investments can help in creating an enabling regulatory and financial framework.

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A committed group of leaders can drive change and innovation in justice systems and support the creation of an enabling environment.

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Problem-Solving Courts in the US

Trend Report 2021 – Delivering Justice / Case Study: Problem-Solving Courts in the US

Author: Isabella Banks , Justice Sector Advisor

Introduction

Problem-solving courts are specialised courts that aim to treat the problems that underlie and contribute to certain kinds of crime (Wright, no date). “Generally, a problem-solving court involves a close collaboration between a judge and a community service team to develop a case plan and closely monitor a participant’s compliance, imposing proper sanctions when necessary” (Ibid). In the past three decades, problem-solving courts have become a fixture in the American criminal justice landscape, with over 3,000 established nationwide. All 50 states have appointed a statewide drug court coordinator, and at least 13 have introduced the broader position of statewide problem-solving court coordinator (Porter, Rempel and Mansky 2010; J. Lang, personal communication, October 28, 2020).

What does it mean for a court to be problem-solving?

Although a number of different types of problem-solving courts exist across the US, they are generally organised around three common principles: problem-solving, collaboration, and accountability (Porter, Rempel and Mansky 2010, p. iii.).

Problem-solving courts are focused on solving the underlying problems of those who perpetrate or are affected by crime. This includes reducing recidivism as well as rehabilitating participants (with the exception of domestic violence courts, as elaborated below), victims and the broader community (Ibid. p. iii.).

Problem-solving courts are also characterised by interdisciplinary collaboration among stakeholders in and outside of the criminal justice system. Dedicated staff who have been assigned to the problem-solving court work together to develop court policies and resolve individual cases in a relatively non-adversarial way. Ongoing collaboration between court staff and public agencies, service providers and clinical experts is also essential for providing appropriate treatment to problem-solving court participants (Ibid. p. 38). Because problem-solving courts aim to address the impact of crime on the community and increase public trust in justice, they also have frequent contact with community members and organisations and regularly solicit local input on their work (Ibid. p. 39).

Problem-solving courts aim to hold individuals with justice system involvement, service providers and themselves accountable to the broader community. For individuals with justice system involvement, this means holding them accountable for their criminal behaviour by promoting and monitoring their compliance with court mandates. In order to comply, problem-solving court participants must understand what is expected of them, regularly appear for status hearings, and have clear (extrinsic and intrinsic) incentives to complete their mandates.

For service providers, this means providing services based on a coherent, specified and effective model, and accurately and regularly informing the court about participants’ progress. Problem-solving courts are also responsible for assessing the quality of service delivery and making sure models are adhered to (Ibid. p. 43-44).

Lastly and perhaps most fundamentally, problem-solving courts must hold themselves to “the same high standards expected of participants and stakeholders” (Ibid. p. 44-45). This means monitoring implementation and outcomes of their services using up-to-date data.

What does problem-solving justice look like in practice?

Problem-solving justice comes in different forms. The original, best known, and most widespread problem-solving court model is the drug court. The first drug was created in 1989, after a judge in Miami Dade county became frustrated seeing the same drug cases cycling through her court and began experimenting with putting defendants into treatment (P. Hora, personal communication, October 16, 2020). This approach (elaborated in the sections that follow) gradually gained traction, and there are now over 3,000 drug courts across the US (Strong and Kyckelhahn 2016).

This proliferation of drug courts helped stimulate the emergence of three other well-known problem-solving court models: mental health, domestic violence and community courts (Porter, Rempel and Mansky 2010, p. iii.). Mental health courts are similar to drug courts in that they focus on rehabilitation, but different in that they aim for the improved social functioning and stability of their participants rather than complete abstinence (Ibid. p. 51). Domestic violence courts are unique in that they do not universally embrace participant treatment and rehabilitation as an important goal. Instead, many – thought not all – are primarily focused on victim support and safety and participant accountability and deterrence (Ibid. p. 52).

Community courts “seek to address crime, public safety, and quality of life problems at the neighbourhood level. Unlike other problem-solving courts…community courts do not specialise in one particular problem. Rather, the goal of community courts is to address the multiple problems and needs that contribute to social disorganisation in a designated geographical area. For this reason, community courts vary widely in response to varying local needs, conditions, and priorities” (Lee et al. 2013). There are now over 70 community courts in operation around the world (Lee et al. 2013, p.1). Some are based in traditional courthouses, while others work out of storefronts, libraries or former schools. Though they typically focus on criminal offences, some community courts extend their jurisdiction to non-criminal matters to meet specific needs of the communities they serve as well (Ibid. p. 1.). Regardless of location and jurisdiction, all community courts take a proactive approach to community safety and experiment with different ways of providing appropriate services and sanctions (Wright n.d.).

Other less common problem-solving models include veterans courts, homeless courts, reentry courts, trafficking courts, fathering courts, and truancy courts (Ibid).

The principles and practices of problem-solving justice can also be applied within non-specialised courts that already exist. In a 2000 resolution that was later reaffirmed in 2004, the Conference of Chief Justices and Conference of State Court Administrators advocated for, “Encourag[ing], where appropriate, the broad integration over the next decade of the principles and methods of problem-solving courts into the administration of justice to improve court processes and outcomes while preserving the rule of law” (Porter, Rempel and Mansky 2010, p. 3). Key features of a problem-solving approach to justice – which will be elaborated in the sections that follow – include: individualised screening and problem assessment; individualised treatment and service mandate; direct engagement of the participant; a focus on outcomes; and system change (Ibid. p. iv).

Problems and impacts

How and to what extent have problem-solving courts measured and mapped the following as a first step towards people-centred justice.

The most prevalent justice problems within the population served
The justice problems with greatest impact on the population served
The justice problems that are most difficult to resolve and therefore tend to remain ongoing
The groups most vulnerable to (systemic and daily) injustices within the population served

As their name suggests, problem-solving courts emerged to address the most prevalent, impactful, and difficult to resolve justice problems within the populations they serve. The first drug (and Drinking While Driving or DWI) courts were created as a response to the increase in individuals with substance use disorders in the criminal justice system and their levels of recidivism. Similarly, mental health courts “seek to address the growing number of [individuals with mental health needs] that have entered the criminal justice system” (Wright n.d.). As one interviewee put it, “The biggest mental health provider [in Los Angeles] is the county jail” (B. Taylor, personal communication, October 5, 2020).

Drug and mental health problems are among the most common issues faced by individuals responsible for both minor and more serious crime. These issues are difficult to resolve because judges – who have historically had little understanding of treatment and addiction – are inclined to hand down harsh sentences when defendants relapse or fail to complete their court mandate (B. Taylor, personal communication, October 5, 2020). This trend was particularly acute in the 1980s, when the war on drugs resulted in draconian sentencing laws that reduced judicial discretion (P. Hora, personal communication, October 16, 2020).

In order to understand and meet the needs of their unique populations, problem-solving courts track measures of problem prevalence and severity. As noted in the first section, early and individualised screening and problem assessment is a key feature of problem-solving justice. The purpose of such screenings is to “understand the full nature of the [participant’s] situation and the underlying issues that led to justice involvement.”

For drug courts, relevant measures of problem severity may include: drug of choice; years of drug use; age of first use; criminal history; and treatment history (Porter, Rempel and Mansky 2010, p. 50). Mental health courts typically assess the nature and severity of their participants’ underlying mental health issues, and may also look at participant stability (in terms of health care, housing, compliance with prescribed medications, and hospitalisations) (Ibid. p. 51).

Domestic violence courts and community courts are somewhat unique in that the primary population they serve include victims and members of the community as well as individuals with justice system involvement. Domestic violence courts focus on assessing the needs of victims of domestic violence in order to connect them with safety planning and other individualised services. Likewise, in addition to identifying the problems that impact individual participants, community courts focus on assessing the problems that impact the underserved (and also often disserved) neighbourhoods where they work. These should be identified through outreach in the relevant community but often include concentrations of lower level crimes – such as vandalism, shoplifting, and prostitution – as well as distrust of traditional justice actors (Ibid. p. 55-56).

Now that technical assistance is broadly available for problem-solving courts across the US, individualised screening and problem assessment has become increasingly data-driven and informed by validated needs assessment tools (B. Taylor, personal communication, October 16, 2020).

Over the years, problem-solving courts have also become more adept at identifying groups within the populations they serve that are particularly vulnerable to injustice. The advancement of brain science, for example, has influenced many problem-solving courts to treat participants under 25 differently and give them an opportunity to age out of crime. Young people transitioning out of foster care are particularly vulnerable to justice involvement given their sudden lack of family support. Trafficked individuals, who used to be treated as criminals, are now widely recognised as victims (Ibid). Specialised problem-solving courts, diversion programs, and training initiatives have emerged to understand the unique needs and vulnerabilities of this population (Wright n.d.).

Problem-solving courts have also become more aware of racial inequities in the populations selected to receive treatment (B. Taylor, personal communication, October 16, 2020). Drug court participants in particular are often disproportionately white, with racial breakdowns that do not mirror the racial breakdowns of those arrested. This is largely a result of eligibility requirements tied to federal drug court funding, which has historically restricted individuals with violent criminal histories from participating. Drug courts have also been accused of cherry-picking participants who were most likely to be successful to improve their numbers and receive more funding. Both of these phenomena have had the effect of excluding disproportionate numbers of people of colour from drug treatment (Ibid). In addition to taking steps to mitigate these inequities, drug courts have increasingly come to recognise that cherry-picking low-risk cases reduces their effectiveness overall (P. Hora, personal communication, October 16, 2020).

Defining + Monitoring Outcomes

How and to what extent have problem-solving courts researched and identified the outcomes that people in the target population expect from justice processes.

In 1993, the first community court was set up in the Midtown neighbourhood of New York City (Lee et al. 2013, p.1). Inspired by the Midtown model, the Red Hook Community Justice Center was established in a particularly disadvantaged area of Brooklyn seven years later. Like the Midtown Court, the goal of the Red Hook Community Justice Center was “to replace short-term jail sentences with community restitution assignments and mandated participation in social services” (Taylor 2016).

In the planning stages however, residents of Red Hook were not happy to learn that a new court was being introduced in their community. Though sustained community outreach, Red Hook court staff were able to change these negative perceptions and convince residents they wanted to do something different. They began by asking the community what outcomes were most important to them (B. Taylor, personal communication, October 5, 2020).

This early engagement helped the Red Hook planners realise that tracking outcomes related to people’s presence in the court would not be enough to assess the court’s impact in the community. They would also need to look at outcomes that were meaningful to residents, asking questions like: How can we disrupt crime hot spots? How safe does the community feel? Do residents feel safe walking to the park, or the train? At what times? (Ibid).

Although the Red Hook community court model has since been replicated in different parts of the world, the experiences of two of these international courts illustrate that identifying the outcomes that community members expect from justice processes can sometimes be a challenge.

In 2005, England opened its first community court: the North Liverpool Community Justice Centre (NLCJC). A 2011 evaluation of the NLCJC acknowledged its innovative approach and “potentially transformative effect on criminal justice” but also noted:

How and why the Centre needs to connect with the public it is charged with serving remains one of the most complex and enduring concerns for staff...how consistently and how effectively the ‘community’ was contributing to the workings of the Centre provided a constant source of uncertainty” (Mair and Millings 2011).

After eight years of operation, the NLCJC was closed in 2013. Observers have since noted that a lack of grassroots community engagement in the planning and operation of the NLCJC was among the primary reasons that it ultimately failed to take hold (Murray and Blagg 2018; J. Lang, personal communication, October 28, 2020).

One year after the NLCJC opened in England, the Neighbourhood Justice Centre (NJC) was piloted in the Collingwood neighbourhood of Melbourne, Australia. At the time, Collingwood had the highest crime rate in Melbourne, high rates of inequality, and a high concentration of services. This combination made it an ideal location for Australia’s first community court.

Modelled on the Red Hook Community Justice Centre in Brooklyn and spearheaded by the State Attorney General at the time, Rob Hulls, the NJC pilot was focused on improving the community’s relationship with the justice system through local, therapeutic and procedural justice. Like Red Hook, it was designed based on evidence and an analysis of gaps in existing justice services. Despite shifting political winds – including “tough-on-crime” rhetoric on the one hand and complaints of more favourable “postcode justice” available only for the NJC’s participants on the other – the NJC managed to secure ongoing state government support (J. Jordens, personal communication, October 19, 2020).

Unlike the NLCJC, the NJC remains in operation today. The procedurally just design of the NJC building and approach of its magistrate, David Fanning, have earned the court significant credibility and legitimacy in the Collingwood community (Halsey and Vel-Palumbo 2018; J. Jordens, personal communication, October 19, 2020). Community and client engagement have continued to be a key feature of the NJC’s work, helping to reduce recidivism and increase compliance with community-based court orders (Halsey and Vel-Palumbo 2018) .

In spite of its success, some observers note that the NJC’s outreach efforts have not gone as far as they could have. Early consultations with a group of community stakeholders regarding the design and governance of the NJC were discontinued in the Centre’s later years. Although the reason for this is unclear and may well have been legitimate, the result was that key representatives of the community lost direct and regular access to NJC leadership over time (J. Jordens, personal communication, October 19, 2020).

These examples illustrate that even under the umbrella of a one-stop-shop community court, identifying expected justice outcomes in the community as a first step towards problem-solving justice – and continuing to do so even after the court is well-established – is not a given. The extent to which this is achieved depends on the approach of the particular court and its efforts to create a reciprocal and collaborative relationship with the surrounding community.

How and to what extent have problem-solving courts determined whether existing justice processes deliver these outcomes and allow people in the target population to move on?

Problem-solving courts generally – and community courts and drug courts in particular – are created with the explicit intention to address gaps in existing justice processes.

Community courts are typically established in communities that have been historically underserved and disproportionately incarcerated to provide a more holistic response to crime and increase trust in the justice system.

In the early days of the Red Hook Community Justice Center, the community’s deep distrust of law enforcement emerged as a key challenge for the Center’s work. Red Hook staff approached this challenge by inviting police officers into the court and showing them the data they had collected on the justice outcomes that residents were experiencing. They helped the officers understand that by not addressing the root causes of crime in the Red Hook community, they were delaying crime rather than stopping it (B. Taylor, personal communication, October 5, 2020).

Over time, the court’s relationship with law enforcement has improved. In 2016, the Justice Center launched its “Bridging the Gap” initiative, which creates a safe space for young people and police officers to get to know each other and discuss difficult topics that offer the chance to explore the other’s perspective (Red Hook Justice News 2016; Sara Matusek 2017).

Similarly, the proliferation of drug courts across the country was a response to high rates of recidivism among individuals with substance use disorders, which persisted in spite of tough-on-crime sentencing practices. During the so-called “war on drugs” in the mid-1980s, judges across the country gradually began to realise that handing down increasingly long sentences to people with substance use disorders was not working.

One such person was the late Honourable Peggy Hora, a California Superior Court judge responsible for criminal arraignments. Like other judges repeatedly confronted with defendants grappling with substance use disorders in the 1980s and 90s, Judge Hora initially felt that incarceration was the only tool available to her. Not much research had been done on incarceration at the time, so its detrimental effects were not yet widely known (P. Hora, personal communication, October 16, 2020).

Determined to understand why the defendants that came before her seemed to be willing to risk everything to access drugs – even their freedom and the right to see their children – Judge Hora took a class on chemical dependency. This experience brought her to the realisation that “everything they were doing was wrong.” She quickly built relationships with people at the National Institute on Drug Abuse and began engaging with drug treatment research at a national level (Ibid).

Judge Hora eventually went on to establish and preside over the nation’s second drug court in Alameda County, California. After learning more about procedural justice and seeing evidence that early drug courts worked and saved money in the long run, she helped promote the model across the country and around the world (Ibid).

How and to what extent have problem-solving courts created a system for monitoring whether new, people-centered justice processes deliver these outcomes and allow people in the target population to move on?

Outcomes monitoring is an essential component of problem-solving justice. As Rachel Porter, Michael Rempel, and Adam Manksy of the Center for Court Innovation set out in their 2010 report on universal performance indicators for problem-solving courts:

It is perhaps their focus on the outcomes generated after a case has been disposed that most distinguishes problem-solving courts from conventional courts. Like all courts, problem-solving courts seek to uphold the due process rights of litigants and to operate efficiently, but their outcome orientation demands that they seek to address the underlying issues that precipitate justice involvement (Porter, Rempel and Mansky 2010, p. 1.).

Measuring and monitoring people-centred outcomes was also key to problem-solving courts’ early success. Because the problem-solving approach was so different from the status quo, showing evidence that it worked was necessary for building political and financial support. This meant clearly articulating the goals of problem-solving courts and finding ways to measure progress towards them (B. Taylor, personal communication, October 14, 2020).

In their report, What Makes a Court Problem-Solving? Porter, Rempel, and Mansky identify universal indicators for each of the three organising principles of problem-solving courts. They include: (under problem-solving) individualised justice and substantive education for court staff; (under collaboration) links with community-based agencies and court presence in community; and (under accountability) compliance reviews, early coordination of information, and court data systems (Porter, Rempel and Mansky 2010, p. 57). Many of these problem-solving principles and practices can be (and are) applied and monitored in traditional courts.

To ensure delivery of individualised justice for example, any court staff can engage the individuals appearing before it by making eye contact, addressing them clearly and directly, and asking if they have any questions about the charges or their mandate (Ibid). This kind of engagement can “radically change the experience of litigants, victims, and families” and “improve the chance of compliance and litigant perceptions of court fairness” (Ibid). Similarly, any court can prioritise and track its use of alternative sanctions – such as community service or drug treatment – and its efforts to link individuals to existing services in the community (Ibid).

The extent to which a particular (problem-solving or traditional) court monitors progress towards these people-centred outcomes depends on its ability to track compliance and behaviour change among participants. This can be achieved through regular compliance reviews, which provide “an ongoing opportunity for the court to communicate with [participants] and respond to their concerns and circumstances” (Ibid. p. 60-61). Investing in electronic data systems that track and coordinate information also makes it easier for a court to monitor its overall impact on case outcomes and improve the quality of its mandates (Ibid).

Successful outcomes monitoring also depends crucially on a court’s ability to develop strong relationships with researchers. Without this, early problem-solving courts like the Red Hook Community Justice Center would not have been able to, for example, quantify the impact of a 7-day jail stay in terms of budget, jail population, and bookings per month. Strong research partnerships also made it possible to compare successful and unsuccessful court participants, which was necessary to assess and improve the quality of the court’s services (B. Taylor, personal communication, October 14, 2020).

Outcomes monitoring at the Red Hook Community Justice Center was not without its challenges, however. Because most people who come before the court are charged with less serious crimes, their treatment mandates are relatively short. The short amount of time the Red Hook staff and service providers have to work with these participants means that outcomes related to individual progress are not likely to show a full picture of the court’s impact. The Red Hook Community Justice Center addressed this by also measuring outcomes related to the court’s impact on the community. What was the effect on social cohesion and stability when someone’s brother, father, or son was allowed to remain in the community instead of being incarcerated? (B. Taylor, personal communication, October 5, 2020).

Another challenge faced by community courts broadly is that traditional outcomes monitoring systems are not well-equipped to acknowledge the reality that everything is connected. Where does one draw the line between service providers and justice providers? If a restorative justice process facilitated under the supervision of the court fails to reconcile the parties in conflict but has a positive impact on the lives of the support people who participate, should it be considered a success or failure?

A former Red Hook staff member involved in the court’s peacemaking initiative shared a story of a young, devout woman with a new boyfriend who mistreated her and who her children strongly disliked. When she tried to throw him out, the boyfriend would use her Christian values against her and convince her to let him stay. Eventually, he punched someone and was arrested on assault charges. His case was referred to a restorative justice circle for resolution. In the circle, the boyfriend was very aggressive and as a result, his case was sent back to court. The woman and her children asked if they could continue meeting in circle without him because they found it helpful (Ibid).

After a series of circle sessions together, the woman came to realise that her abusive boyfriend was using drugs and found the courage to kick him out. In his absence, the woman and her children were able to reconcile and reunite. The woman returned to school and her oldest son found a job. The criminal case that started the process was ultimately unresolved, but from a more holistic and common sense perspective the impact of the circles on the family was positive (Ibid). How should success be measured in this case? This is a challenge that community courts attempting to measure and monitor people-centred justice regularly face.

Evidence-Based Solutions

How and to what extent have problem-solving courts introduced interventions that are evidence-based and consistently deliver the justice outcomes that people in the target population look for.

Problem-solving courts have introduced a number of interventions that have proven to deliver people-centred outcomes for the communities they serve. Although different interventions work for different populations, direct engagement with participants and the delivery of individualised treatments are two key elements of the problem-solving orientation that all problem-solving courts share (Porter, Rempel and Mansky 2010, p. 29-30).

As described in the previous section, direct engagement means that the judge speaks to participants directly and becomes actively engaged in producing positive change in their lives (Ibid. p. 30-31). This effort to ensure that participants feel heard, respected and experience the process as fair is supported by research on procedural justice.

Individualised treatment means that the interventions delivered are tailored to the specific problems of each participant. This requires that the court offer “a continuum of treatment modalities and services to respond to the variety and degrees of need that participants present.” This service plan must be revisited by the court on a regular basis and adjusted depending on the participant’s reported progress (Ibid. p. 29-30).

Despite this shared approach to justice delivery, different problem-solving courts have identified different types of treatments and ways of monitoring whether they work that are unique to the populations they serve.

Community courts like the Red Hook Community Justice Center, for example, generally work with the residents in their neighbourhood to find out what is important to them rather than imposing a predetermined set of solutions.

The Neighbourhood Justice Centre in Melbourne did this through a unique problem-solving process that took place outside of the courtroom and which participants could opt into voluntarily. In a confidential, facilitated discussion based on restorative and therapeutic justice principles, participants were given an opportunity to share their perspective on the problems they were facing and empowered to become collaborators in their own rehabilitation. Important takeaways from this process would be reported back to the court’s magistrate so he could help them move forward – for example by changing their methadone (1) dose or changing the number of treatments they received per week. The collaborative nature of the sessions helped ensure that the treatment plans mandated by the court were realistic for participants. Though the content of these sessions was unpredictable and varied, the co-design process remained constant (J. Jordens, personal communication, October 19, 2020; Halsey and Vel-Palumbo 2018).

With that said, certain interventions have proven to consistently improve outcomes for communities, victims, and individuals with justice system involvement when applied to low-level cases. These include: using (validated) screening and assessment tools (2); monitoring and enforcing court orders (3); using rewards and sanctions; promoting information technology (4); enhancing procedural justice (5); expanding sentencing options (to include community service and shorter interventions that incorporate individualised treatment); and engaging the community (6).

In 2009, the National Institute of Justice funded a comprehensive independent evaluation of the Red Hook Community Justice Center to assess whether it was achieving its goals to reduce crime and improve quality of life in the Red Hook neighbourhood through these interventions (Lee et al. 2013, p. 2.). The evaluation found that:

The Justice Center [had] been implemented largely in accordance with its program theory and project plan. The Justice Center secured the resources and staff needed to support its reliance on alternative sanctions, including an in-house clinic and arrangements for drug and other treatment services to be provided by local treatment providers...The Justice Center’s multi-jurisdictional nature, as well as many of its youth and community programs, evolved in direct response to concerns articulated in focus groups during the planning process, reflecting a stated intention to learn of and implement community priorities (Ibid. p. 4).

Using a variety of qualitative and quantitative research methods, the evaluation also concluded that Red Hook had successfully: changed sentencing practices in a way that minimised incarceration and motivated compliance; provided flexible and individualised drug treatment; sustainably reduced rates of misdemeanour recidivism among young people and adults; and reduced arrests in the community.

In spite of the robust evidence supporting their approach, many community courts experience resistance to their efforts to help participants address underlying issues of substance use and mental disorders through treatment. As Brett Taylor, a Senior Advisor for Problem-Solving Justice and former defence attorney at the Red Hook explains:

Some critics of community courts say that [this] is not the job of courts and should be handled by other entities. In a perfect world, I would agree. However, in the reality of the world today, people with social service needs continue to end up in the courts. Court systems across the country have realised that if defendants with social service needs are not given treatment options, those defendants will be stuck in the revolving door of justice and continue to clog the court system....Although it may not comport with the vision of success that many defence attorneys had upon entering this work, I can tell you that nothing beats seeing a sober, healthy person approach you on the street and hearing, ‘Thank you for helping me get my life back on track’ (Taylor 2016, p. 25).

In contrast to the broad and community-based approach to treatment taken by community courts, drug courts focus specifically on providing drug treatment. In the words of Judge Peggy Hora, drug treatment is “painful and difficult.” Because of this, drug courts start with external changes as their goal, but ultimately aim for internal change. This means appropriately matching participants with evidence-based treatment and using neutral language that assists, supports, and encourages participants along the way. Because relapse is such a common feature of recovery, drug courts focus on keeping people in appropriate treatment as long as necessary for them to eventually graduate from the program (P. Hora, personal communication, October 16, 2020).

Drug court treatments have become increasingly evidence-based since the 1990s due to a growing movement toward performance measurement in the non-profit sector:

The emergence of drug courts as a reform of courts’ traditional practice of treating drug-addicted offenders in a strictly criminal fashion coincided with renewed interest in performance measurement for public organisations. The argument for measuring the performance of drug courts is compelling because they are a recent reform that must compete with existing priorities of the judicial system for a limited amount of resources. This makes it incumbent upon drug courts to demonstrate that the limited resources provided to them are used efficiently and that this expenditure of resources produces the desired outcomes in participants (Rubio et al. 2008, p. 1).

This movement was further strengthened by the development of a cutting edge performance measurement methodology known as the “balanced scorecard.” Created for the business sector, the balanced scorecard method aims to go beyond traditional measures of success and get a more balanced picture of performance by incorporating multiple perspectives. This method was adapted to create CourTools, a set of ten performance measures designed to evaluate a small set of key functions of trial courts (Ibid. p. 2).

Because “the nature of addiction and the realities of substance use treatment require extended times to disposition for drug court participants,” many of the performance measures developed for conventional trial courts (such as reduced time to disposition) are not directly applicable to drug courts. However, the increased application of performance measurement to courts and the creation of CourTools in particular helped make way for the development of the first set of nationally recommended performance measures for Adult Drug Courts in 2004 (Ibid. p. 4).

Developed by a leading group of scholars and researchers brought together by the National Drug Court Institute (NDCI) and published for the first time in 2006, these included four key measures of drug court performance: retention; sobriety, in-program recidivism; and units of service (Ibid. p. 5).

Retention refers to the amount of time drug court participants remain in treatment. “Longer retention not only indicates success in treatment but also predicts future success in the form of lower post treatment drug use and re-offending” (Ibid. p. 5). Sobriety – both during and after treatment – is another important goal of drug courts. “As the participant proceeds through the program, a trend of decreasing frequency of failed [drug] tests should occur. Research has shown that increasing amounts of time between relapses is associated with continued reductions in [drug] use” (Rubio et al. 2008, p. 5). In-program recidivism is the rate at which drug court participants are re-arrested during the course of their participation. This is expected to be lowered through a combination of “judicial supervision, treatment, and rewards and sanctions” unique to drug courts (Ibid. p.5; US Government and Accountability Office, 2005). Finally, units of service refers to the dosages in which drug court treatment services – including, but not limited to substance use treatment – are delivered. These are usually measured in terms of days or sessions of service provided (Rubio et al. 2008, p. 5).

Since their development, these four measures of drug court performance have been actively promoted by leading technical assistance providers like the Center for Court Innovation (CCI) and the National Center for State Courts (NCSC) (Ibid. p. 6). They have since been adopted and adapted by a number of states across the US. The NCSC facilitates this process, but decisions about what specifically to measure are made by the advisory committee convened by the state-level agency responsible for drug courts (Ibid). Additional performance measures used by some states relate to, for example: accountability, social functioning, processing, interaction with other agencies, compliance with quality standards, and juvenile drug court measures, family drug court measures, and domestic violence drug court measures (Ibid. p. 10).

In 2007, the NCSC surveyed statewide drug court coordinators from across the country about their use of state-level performance measurement systems (SPMS). Out of 45 states that completed the surveys, 58% were using a SPMS in their drug courts. Most of these were adult drug courts (Ibid. p. 14). Although the frequency with which these states reported performance measurement data varied from quarterly to annually, the majority did provide data to a central agency (Ibid. p. 15).

The development and widespread use of SPMS have helped drug courts deliver treatments that are increasingly evidence-based in the sense of consistently delivering the outcomes that their participants need. However, the NCSC survey found that the state-level performance measures used were not entirely balanced in that they typically focused more on the effectiveness of drug courts than their efficiency, productivity, or procedural satisfaction (Ibid. p. 20). The NCSC therefore recommended that a more balanced, national and uniform set of drug court performance measures be developed to measure performance more holistically and facilitate comparisons of performance across states (Ibid. p. 18).

How and to what extent have problem-solving courts used outcome-based monitoring (discussed in the previous section) to continuously improve these interventions and replace interventions that have proven ineffective?

Because of their problem-solving orientation and focus on outcomes, problem-solving courts are by their nature adaptive and capable of developing new treatment modalities to meet different kinds of needs. As Brett Taylor, Senior Advisor for Problem-Solving at the Center for Court Innovation put it, “the problem-solving court environment creates a space in which there is more room for creativity. If you were to redesign the justice system now, there wouldn’t be only courts you could go to, there would be different justice mechanisms and modalities available to treat different levels of issues. Perhaps that is why new modalities develop within problem-solving courts” (B. Taylor, personal communication, October 19, 2020).

A clear example of this creative and outcomes-based approach to improvement was the way the problem-solving dialogue process developed at the Neighbourhood Justice Center (NJC) was adapted over time to meet changing demands in the community. As Jay Jordens, a Neighbourhood Justice Office at the NJC who introduced the process explains: “different problems would arise that would demand a re-design of the court’s approach” (J. Jordens, personal communication, October 19, 2020).

For example, the NJC began to notice that people responsible for family violence were participating in problem-solving dialogues without sharing this part of their history. In response, the NJC developed a tailored problem-solving process for people who were respondents to a family violence order in which this part of their past would be addressed from the start. The NJC also began facilitating support meetings for victims of family violence, including for example parents who were being mistreated by their children. The process was designed to solicit feedback about the new approach after victims had tried it. Eventually, it earned the support of the police in the community because it consistently delivered outcomes for a unique population (Ibid).

A second adaptation of the problem-solving process at the NJC was made when court staff noticed that many young people were opting out. Many of the court-involved young people in the Collingwood community were refugees from South Sudan who were experiencing the effects of intergenerational trauma. Realising that the process as it was originally imagined was too interrogative for this population, the NJC began holding circles with the young person, their mother, and one or two support workers. A facilitator would begin by asking humanising questions of everyone in the circle. Although the young person would often pass when it was their turn to speak, participating in the circle gave them an opportunity to listen, relax, and improve their relationships with the adults sitting in the circle with them. These problem-solving circles were designed to prioritise safety concerns and would often result in an agreement among the participants to get external support and/or attend family therapy.

Jay Jordens notes that such adaptations were possible in spite of, not because of, an operational framework of specialisation within the court that made collaboration a choice rather than an expectation among Centre staff. “We aren’t there yet where these processes are intuitive,” he explained, “we still need to actively facilitate them” (Ibid).

Because of their systematic approach to outcomes monitoring and performance measurement, drug courts have made a number of improvements to the treatment they provide as well. First and foremost, they have learned to avoid net widening: “the process of administrative or practical changes that result in a greater number of individuals being controlled by the criminal justice system” (Leone n.d.).

Specifically, drug courts have learned that putting the wrong people in the wrong places results in bad outcomes. An example of this is cherry picking the easiest cases for drug treatment: a common practice among drug courts in the early years of their development that later proved to be harmful. Evidence has shown that drug courts are most effective when they focus on treating high-risk, high-needs participants who are most likely to reoffend (P. Hora, personal communication, October 16, 2020). Cherry picking low-risk cases in order to inflate measures of success means putting them in more intensive treatment than they need and failing to appropriately match treatments with risk. Over time, this entraps people in the criminal justice system unnecessarily and reduces drug courts’ potential to meaningfully reduce crime (B. Taylor, personal communication, October 19, 2020).

Cherry picking low-risk cases for drug treatment has also resulted in racially biased outcomes. Because of the ways racial bias is embedded in the American criminal justice system, young white defendants have historically been more likely to be assessed as low-risk and eligible for specialised treatment than participants of colour. Participants of colour who were selected for drug court programming also tended to flunk out or leave voluntarily at higher rates than white participants.

In response to these trends, drug courts developed a toolkit on equity and inclusivity to examine the data and understand why this was happening. They introduced HEAT (Habilitation Empowerment Accountability Therapy), a new drug treatment modality geared towards young black men which was recently evaluated with very positive results. They have also worked harder generally to ensure that treatments are culturally appropriate for the different populations they serve.

Drug courts have also become more sophisticated at treating different kinds of drug addiction. The Matrix Model, for example, was developed to engage a particularly difficult population – stimulant (methamphetamine and cocaine) users – in treatment. Previously considered “untreatable” by many drug courts, stimulant users treated using the Matrix Model have shown statistically significant reductions in drug and alcohol use, risky sexual behaviors associated with HIV transmission, and improved psychological well-being in a number of studies (P. Hora, personal communication, October 16, 2020; National Institute of Drug Abuse 2020).

Drug court judges who once took a “blaming and shaming” approach have shifted towards a more people-centred one, as evidenced by changes in the language used to describe participants. In response to research in the medical sector demonstrating that people who are described as addicts receive lower quality care and fewer prescriptions, drug courts have increasingly replaced the term “addiction” with “substance use disorder” (P. Hora, personal communication, October 16, 2020).

In line with this shift, attitudes towards medically assisted drug treatment have also changed dramatically over the years. Whereas most drug courts previously did not allow the use of methadone in treatment, the field has now clearly adopted medically assisted treatment after finding that it was consistent with improved graduation rates, among other outcomes. Though not universally accepted, it is now considered a best practice supported by decades of research (Ibid).

On a more systematic level, a 2007 analysis of performance measurement data collected by the state of Wyoming provides an example of how drug courts have started to use this data to improve the quality of their treatments and overall impact. Based on results related to the key measures of drug court performance introduced in the previous section – retention, sobriety, in-program recidivism and units of service – the NCSC made a number of programmatic recommendations for drug courts across the state. First, they suggested that drug courts aim to support participants’ education and employment-related needs, as both attainment of a diploma and employment at admission to treatment were associated with increased graduation rates. They also recommended that additional resources be made available for young participants of colour, who were found to have higher rates of positive drug tests and recidivism than young white participants (Rubio et al. 2008, p. 17).

Innovations + Delivery Models

How and to what extent have problem-solving courts scaled their people-centered service delivery model to deliver justice outcomes for a larger population.

Many problem-solving courts across the US continue to start in the way the first problem-solving courts did: with judges deciding to do things differently. With that said, the proliferation of problem-solving courts across the country can be traced to three primary factors: science and research; technical assistance; and changes in legal education.

Research has helped bring problem-solving courts to scale by showing that the problem-solving approach to justice, if properly implemented, can be effective. Research on procedural justice and advancements in understanding of the science of addiction have been particularly important in this respect. Increased awareness of major studies in these areas have helped the field shift towards evidence-based working and helped legal professionals learn from past mistakes. More and more judges realise that relapse is part of recovery, and that mandated treatment within a drug court structure delivers positive outcomes for participants (B. Taylor, personal communication, October 19, 2020).

Once a number of problem-solving courts had been established around the country, technical assistance providers emerged to help them take a data-driven approach. This means working with communities to look at the numbers and identify the biggest crime problems they are struggling with and introducing a problem-solving court that is responsive to those issues. It also means using screening and needs assessment tools to make informed sentencing decisions and match participants to appropriate treatments. Technical assistance has helped problem-solving courts increase their impact and effectiveness and over time deliver outcomes for larger populations (Ibid).

As problem-solving courts like the Red Hook Community Justice Center have become better known, law students and young legal professionals have become more aware of and enthusiastic about problem-solving justice as an alternative to adversarial ways of working (Ibid). This represents a significant shift from the early days of problem-solving courts, when judges and lawyers alike were reluctant to embrace non-conventional conceptions of their roles as legal professionals. Prosecutors called problem-solving courts “hug-a-thug” programs. Defence attorneys resisted the idea of a court being a cure-all for their clients. Judges insisted that they “weren’t social workers” and shouldn’t be doing this kind of work (P. Hora, personal communication, October 16, 2020). Service providers were concerned too: they feared that involving the justice system in treatment would ruin their client relationships.

Over time, judges have come to see that their roles could expand without violating something sacrosanct about being a judge. In 2000, the Conference of Chief Justices and Conference of State Court Administrators adopted a resolution supporting the use of therapeutic justice principles. Since then, experience presiding over a drug court has come to be seen as a positive in judicial elections (Ibid).

Despite early concerns that problem-solving courts were “soft on crime,” prosecutors and defense attorneys have largely come on board as well. Research has demonstrated that when problem-solving courts acknowledge their gaps in knowledge and defer to service providers for clinical expertise, they can be successful in supporting treatment. As a result of advances in research, the emergence of problem-solving technical assistance, and important cultural shifts, drug and mental health courts are now widely recognised as appropriate and welcome additions to the field (Ibid). This acceptance has facilitated their spread nationally and as far as Australia and New Zealand.

Court numbers are not the only relevant measure for evaluating the extent to which problem-solving courts have successfully scaled, however. In addition to horizontal scaling of courts across the country, vertical integration of problem-solving principles and practices within particular jurisdictions is an important indicator of problem-solving courts’ spread and influence (J. Lang, personal communication, October 28, 2020).

As explained in the introduction, the principles and practices of problem-solving justice can be and are increasingly applied by traditional justice actors and in existing, non-specialised courts. Police departments across the country are learning that they can divert defendants to treatment from the get-go, without necessarily waiting for a case to be processed through the courts (Ibid). A prominent example of police-led diversion is LEAD (Law Enforcement Assisted Diversion) in Seattle, “a collaborative community safety effort that offers law enforcement a credible alternative to booking people into jail for criminal activity that stems from unmet behavioural needs or poverty” (Law Enforcement Assisted Diversion, n.d.). The Seattle LEAD model was externally evaluated and found to deliver a range of positive outcomes for individuals with justice system involvement and the community (LEAD National Support Bureau n.d.-a). The model has been replicated successfully and is now operating in over thirty-nine counties in the US (LEAD National Support Bureau n.d.-b).

Cases that do reach court are also increasingly diverted outside of it. Prosecutors and judges who are not operating within a problem-solving court can nevertheless apply problem-solving principles by linking defendants to services and making use of alternative sentences in lieu of jail time. This “problem-solving orientation” has allowed problem-solving justice to be applied in more instances and settings without necessarily setting up new problem-solving courts. One indication that problem-solving courts have already scaled “horizontally” in the US – and that this “vertical” scaling is the latest trend – is the fact that the US government’s drug courts funding solicitation in 2020 no longer includes a category for the creation of a new drug court (J. Lang, personal communication, October 28, 2020).

Evidence of this trend towards vertical scaling can be found as far away as Australia. As a specific alternative to horizontal replication, the Neighbourhood Justice Centre (NJC) has developed resources to support judges at the Melbourne Magistrates Court to adopt a problem-solving approach to their work. Over time, this court has become a “laboratory of experimentation” for problem-solving principles and practices as well as other complementary technologies (i.e. therapeutic or procedural justice approaches) that need to be tested before broader roll-out. In a similar vein, New York City’s courts have carried the innovative principles and practices of community courts into centralised courthouses in Brooklyn and the Bronx rather than creating more Red Hooks (Ibid).

How and to what extent have problem-solving courts funded their service delivery model in a sustainable way?

Drug courts have been successful in obtaining large and sustainable streams of federal funding due to the strong research partnerships they developed from the start. Early data collection and evaluation persuaded funders that the problem-solving approach would deliver positive outcomes and save money by reducing incarceration costs. The fact that Florida Attorney General Janet Reno – who set up the nation’s first drug court in 1989 – worked with Assistant Public Defender Hugh Rodham (7) in Miami Dade County also helped make drug courts a success and capture the attention of the federal government early on.

Importantly, federal funding for drug courts was often conditional upon their participation in rigorous evaluations. This demonstrated the effectiveness of the drug court model in a way that may not have been possible had the drug courts had to fund the research themselves, and justified their continued funding (P. Hora, personal communication, October 16, 2020). In recent years, states and counties have become a significant source of funding for drug courts as well (J. Lang, personal communication, October 28, 2020).

Although the federal government has also helped fund other types of problem-solving courts, drug courts are by far the most sustainably funded. Only recently has the government made it possible for community courts to apply for direct funding, or indirect funding as subgrantees of the Center for Court Innovation. The long-term funding for many community courts is provided by local municipalities (Ibid). Funding community courts is a unique challenge because in addition to standard line items like project director and case worker salaries, they must find a way to cover less conventional expenses support for community volunteers and circle participants (often in the form of food, which the government is not willing to fund) (B. Taylor, personal communication, October 19, 2020).

Direct federal funding for other kinds of problem-solving courts is very limited. What funding has been made available to them has gone primarily towards research and the establishment of state-level coordinators and problem-solving court infrastructure. This has helped to increase awareness of the problem-solving principles and practices at the state level and encouraged their application in different areas (P. Hora, personal communication, October 16, 2020).

Private foundations have supported various aspects of problem-solving justice initiatives in certain parts of the country, but have not yet committed to doing so in a sustained way (J. Lang, personal communication, October 28, 2020).

To what extent have problem-solving courts leveraged the following sustainable financing strategies: public-private partnerships and smart (user) contributions?

Community courts in New York – including the Red Hook Community Justice Center and the Midtown Community Court – have benefitted from public-private partnerships to the extent that their planning and operations have been led by the Center for Court Innovation, a public-private partnership between the New York court system and an NGO. Over the years, these courts have also partnered with local “business improvement districts” to supervise community service mandates and offer employment opportunities to program graduates (Ibid).

Some treatment courts do also charge a nominal participant fee, which can range from $5-$20 per week (Wallace 2019). These user contributions can be used for grant matching, among other things. Charging people for their participation in problem-solving programming is generally not regarded as good practice, however (J. Lang, personal communication, October 28, 2020).

More broadly, problem-solving courts and community courts in particular can be said to be financially sustainable in that they often save taxpayer money (Wallace 2019). Although it takes time to realise the benefits of the upfront costs of creating and running a drug court for example, research has demonstrated that once established, the associated cost savings range from more than $4,000-$12,000 per participant (Office of National Drug Court Policy 2011). The Red Hook Community Justice Center alone was estimated to have saved local taxpayers $15 million per year (primarily) in victimisation costs that were avoided as a result of reduced recidivism (Halsey and de Vel-Palumbo 2018). The cost savings associated with problem-solving courts have helped them to continue to be competitive applicants for federal, state and local, and sometimes private grant funding over the years and in spite of changing political winds (Wallace 2019).

Enabling environment

How and to what extent have regulatory and financial systems created/enabled by the government supported problem-solving courts and made it possible for this service/activity to scale?

Most if not all states in the US have allowed drug courts to become part of state legislation, which makes possible their continued operation (P. Hora, personal communication, October 16, 2020).

How and to what extent have the outcomes-based, people-centered services delivered by problem-solving courts been allowed to become the default procedure?

Problem-solving courts have not been allowed to become the default procedure in that adversarial courts and procedures remain the standard way of responding to crime in the US. In the words of Judge Hora, “There is no question that the number of people served is growing, but this remains only a drop in the bucket. For every person served there are 6-7 who aren’t” (Ibid). However, the expanding presence of problem-solving courts has helped the justice sector shift away from the excessively punitive state sentencing laws and tough-on-crime rhetoric of the late 1980s towards a more restorative and evidence-based way of working (B. Taylor, personal communication, October 5, 2020).

Problem-solving courts have enabled cultural change by demonstrating to lawyers and judges that defendants do better when they are able to access treatment, while at the same time allowing these traditional legal players to act as intermediaries and retain a gatekeeping role. As discussed in previous sections, police, prosecutors, and judges alike have grown increasingly comfortable with diverting cases from the adversarial track to community-based treatment (Ibid).

It is a paradox that the US has developed and spread the problem-solving courts model as the country with the highest incarceration rates in the world. Former Senior Advisor of Training and Technical Assistance at the Center for Court Innovation, Julius Lang, speculates that this punitive backdrop is what has allowed alternatives to incarceration to flourish in the US and become so highly developed. At the same time, countries with lower baseline penalties that have set up problem-solving courts, such as Canada and Australia, have developed creative means of engaging defendants who need treatment since there is less of a threat of incarceration (J. Lang, personal communication, October 28, 2020).

How and to what extent have problem-solving courts stimulated (or benefitted from) investment into justice research and development?

Problem-solving courts have both stimulated and benefited from investment into justice research and development. As discussed in the previous sections, the success of problem-solving courts in the US can be attributed in large part to their strong research partnerships.

From the start, “problem-solving courts always took responsibility for their own research and their own outcomes” (Ibid). Problem-solving justice initiatives run by the Center for Court Innovation, for example, always worked directly with researchers. This produced a huge amount of evaluation literature, which was important for securing the buy-in and funding necessary to continue operating (B. Taylor, personal communication, October 14, 2020).

The fact that federal funding has incentivised high-quality evaluations has also gone a long way to build a foundation of evidence demonstrating drug courts’ effectiveness (P. Hora, personal communication, October 16, 2020).

Leadership + Pathways

How and to what extent have justice sector leaders’ skills and collaborations enabled/hindered problem-solving courts to increase access to justice by delivering the outcomes people need at scale.

Strong leadership has been essential to problem-solving courts’ ability to deliver the treatment outcomes people need at scale. Without the leadership of visionary judges and other leaders aiming to do things differently, they would never have come into existence in the first place.

Because of the tendency to maintain the status quo, individual problem-solving courts also rarely get off the ground without a strong champion. The reason for this can be traced to problem-solving principles and practices themselves: the goal is not to force people to change, but to make them change because they want to. In the same way, effective leaders can persuade system actors that problem-solving justice is the way to achieve common goals (B. Taylor, personal communication, October 14, 2020).

Community courts in particular require strong leadership. This can sometimes pose problems for the courts’ long-term stability. For example, a community court in North Liverpool was championed by prominent national politicians. Their leadership was important for the court’s establishment and initial funding, but changes in national leadership and the lack of local support were major factors in the court’s ultimate closure (J. Lang, personal communication, October 28, 2020).

As mentioned above, community courts may struggle when their early champions move on. To avoid this and prepare for the eventual departure of the personalities who are driving change, it is important to put the courts’ internal ways of working into writing. As previously discussed, it is also necessary to obtain evidence that the court’s approach works, as this is a more important driver of funding than good leadership in the long-run (B. Taylor, personal communication, October 5, 2020).

Mid-level leadership within problem-solving courts also matters. Since staff are often employed and supervised by various partner agencies – rather than the director of the project as a whole – it is particularly important that they be selected with care, trained in the project’s mission, policies and practices, and incentivised to work as part of a single team (J. Jordens, personal communication, October 19, 2020).

How and to what extent have problem-solving courts contributed to/benefited from new high-level strategies or pathways towards people-centred justice in the US?

High-level strategies at the state level and in the form of technical assistance have benefitted problem-solving courts significantly by facilitating their replication. This is particularly true of drug courts, for which state-wide coordination mechanisms were set up at an early stage.

Recognising that substance use disorder was a major problem, and persuaded by the same research as federal legislators, state officials began to set up mechanisms that would allow them to receive federal drug court funding. This also allowed them to strategise about which counties would most benefit from drug courts (or other problem-solving courts), and which standards to impose.

Together, state-wide coordination mechanisms created an infrastructure for the improvement and replication of drug courts nationwide, and made it easier to apply problem-solving practices and principles in new settings. Whereas trainings on brain science and what’s working in treatment used to be reserved for drug court judges, there are now few states that do not include them in judicial training for all new judges. The same can be said for trainings for prosecutors, defence attorneys, and service providers (P. Hora, personal communication, October 16, 2020).

The emergence of technical assistance providers specialising in problem-solving justice such as the Center for Court Innovation, Justice System Partners, the National Center for State Courts, and the Justice Management Institute have also helped problem-solving courts to coordinate and replicate in strategic ways. By developing listservs and organising conferences, these organisations have enabled people in various problem-solving courts to support each other across state and international lines. Over time, these efforts have created shared principles and legitimacy around the movement for problem-solving justice (J. Lang, personal communication, October 28, 2020).

To what extent have problem-solving courts contributed to/played a role in a broader paradigm shift towards people-centered justice?

As mentioned in the introduction, a fifth key feature of the problem-solving orientation is system change. By educating justice system stakeholders about the nature of behavioural problems that often underlie crime and aiming to reach the maximum number of cases within a given jurisdiction, problem-solving courts seek to make broader impact within the justice system and community (Porter, Rempel and Mansky 2010, p. 32-33).

Since the first drug court was set up in 1989, legal professionals have become increasingly aware that many people with social problems end up in the justice system: a system that was never intended to address those problems. Problem-solving courts have contributed to a broader paradigm shift towards people-centred justice to the extent that they have helped these professionals:

Acknowledge this issue;
Recognise that lawyers are not equipped to deal with this issue (American law schools do not prepare them to);
Connect with service providers in the community;
Leverage the coercive power of the justice system in a positive way;
Encourage success in treatment programs using procedural justice.

By taking a collaborative approach to decision-making, delivering individualised justice for each participant while at the same time holding them accountable, educating staff, engaging the broader community, and working to produce better outcomes for people, problem-solving courts have demonstrated what people-centred criminal justice can look like in the US and around the world.

View additional information

(1) Methadone is a synthetic opioid used to treat opioid dependence. Taking a daily dose of methadone in the form of a liquid or pill helps to reduce the cravings and withdrawal symptoms of opioid dependent individuals.

(2) “A screening tool is a set of questions designed to evaluate an offender’s risks and needs fairly quickly…An assessment tool is a more thorough set of questions administered before an offender is matched to a particular course of treatment or service.” Taylor 2016, p. 7.

(3) “The main monitoring tool community courts use is compliance hearings, in which participants are periodically required to return to court to provide updates on their compliance.” Taylor, 2016, p. 9.

(4) “Community courts have promoted the use of technology to improve decision-making. Technology planners created a special information system for the Midtown Community Court to make it easy for the judge and court staff to track defendants…Information that’s reliable, relevant, and up-to-date is essential for judges to make the wisest decisions they can.” Taylor 2016, p. 12-13.

(5) In community courts, “judges often speak directly to the offender, asking questions, offering advice, issuing reprimands, and doling out encouragement. This reflects an approach known as procedural justice…Its key components, according to Yale Professor Tom Tyler, are voice, respect, trust/neutrality, and understanding.” Taylor 2016, p. 15.

(6) “Community courts emphasize working collaboratively with the community, arguing that the justice system is stronger, fairer, and more effective when the community is invested in what happens inside the courthouse.” Taylor 2016, p. 22.

(7) Hugh Rodham was the brother of Hillary Clinton, who would become the First Lady a few years later.

View References

Amanda Cissner and Michael Rempel. (2005). The State of Drug Court Research: Moving Beyond ‘Do They Work?’ , Center for Court Innovation.

Brett Taylor. (2016). Lessons from Community Courts: Strategies on Criminal Justice Reform from a Defense Attorney . Center for Court Innovation, p. 3.

Cheryl Wright, (n.d.). Tackling Problem-Solving Issues Across the Country . National Center for State Courts (NCSC).

Cynthia Lee, Fred Cheesman, David Rottman, Rachael Swaner, Suvi Lambson, Michael Rempel and Ric Curtis. (2013). A Community Court Grows in Brooklyn: A Comprehensive Evaluation of the Red Hook Community Justice Center . National Center for State Courts, Center for Court Innovation, p.1.

David Wallace. (2019). Treatment Court: Is Yours Sustainable? (Part Four) . Justice Speakers Institute.

David Wallace. (2019). Treatment Court: Is Yours Sustainable? (Part One) . Justice Speakers Institute.

Dawn Marie Rubio, Fred Cheesman and William Federspiel. (2008). Performance Measurement of Drug Courts: The State of the Art . National Center for State Courts, Volume 6, p. 1.

George Mair and Matthew Millings. (2011). Doing Justice Locally: The North Liverpool Community Justice Centre . Centre for Crime and Justice Studies.

Halsey and de Vel-Palumbo. (2018). Courts As Empathetic Spaces: Reflections on the Melbourne Neighbourhood Justice Centre . Griffith Law Review, 27(4).

Interview with Brett Taylor, Senior Advisor for Problem-Solving Justice, Center for Court Innovation, October 5, 2020.

Interview with Brett Taylor, Senior Advisor for Problem-Solving Justice, Center for Court Innovation, October 14, 2020.

Interview with Brett Taylor, Senior Advisor for Problem-Solving Justice, Center for Court Innovation, October 16, 2020.

Interview with Brett Taylor, Senior Advisor for Problem-Solving Justice, Center for Court Innovation, October 19, 2020.

Interview with Jay Jordens, Education Program Manager – Therapeutic Justice, Judicial College of Victoria, October 19, 2020.

Interview with Judge Peggy Hora, President, Justice Speakers Institute, October 16, 2020.

Interview with Julius Lang, Senior Advisor, Training and Technical Assistance, Center for Court Innovation, October 28, 2020.

Law Enforcement Assisted Diversion (LEAD) , King County.

LEAD National Support Bureau, (n.d.). Evaluations .

LEAD National Support Bureau. (n.d.). LEAD: Advancing Criminal Justice Reform in 2020 .

Mark Halsey and Melissa de Vel-Palumbo. (2018). Courts As Empathetic Spaces: Reflections on the Melbourne Neighbourhood Justice Centre . Griffith Law Review 27 (4).

Matthew Leone, Net widening , Encyclopaedia of Crime and Punishment, SAGE Reference.

National Institute of Drug Abuse (2020). The Matrix Model (Stimulants) , Principles of Drug Addiction Treatment: A Research-Based Guide

Office of National Drug Court Policy. (2011). Drug Courts: A Smart Approach to Criminal Justice .

Rachel Porter, Michael Rempel and Adam Mansky. (2010). What Makes a Court Problem-Solving? Universal Performance Indicators for Problem-Solving Justice . Center for Court Innovation, p. 1

Red Hook Justice News. (2016). Bridging the Gap: Youth, Community and Police .

Sarah Matusek. (2017). Justice Center celebrates Bridging the Gap birthday . The Red Hook Star Revue.

Sarah Murray and Harry Blagg. (2018). Reconceptualising Community Justice Centre Evaluations – Lessons from the North Liverpool Experience . Griffith Law Review 27 (2).

Suzanne Strong and Tracey Kyckelhahn. (2016). Census of Problem-Solving Courts, 2012 . Bureau of Justice Statistics.

US Government and Accountability Office, 2005.

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Problem-Solving Courts: Fighting Crime by Treating the Offender

Courts designed to stop crime by treating substance use disorders and other serious problems underlying criminal conduct are known as problem-solving courts (PSCs). Implicit in that designation is broad recognition among justice stakeholders that traditional criminal courts, rooted in adversarial prosecution and punishment, were not working for certain classes of those who commit crimes, their victims, or society at large.

What began as a creative justice-delivery alternative, born of necessity in the late 1980s and 1990s when the crack cocaine epidemic [1] was overwhelming court dockets and filling prisons with unreformed drug offenders, is now a fixture of the American criminal justice system. Adult treatment drug courts alone account for over 1,600 of the more than 3,100 PSCs in the United States. Initially isolated, specialized dockets for managing high volumes of drug cases, drug courts today represent a national movement fortified by extensive research on what works and an active, collaborative practitioner community.

For NIJ, working to define, refine, and assist PSCs has been a research priority for a quarter of a century, since it sponsored an evaluation of the nation’s inaugural PSC, the Miami-Dade County Felony Drug Court, in 1993. What began as a narcotics docket evolved, with the aid of NIJ research, into a proliferation of drug-court program ideas emanating from courts and researchers. Comparative scientific research identified the best of those ideas, leading to PSC models, said Linda Truitt, the NIJ senior social scientist who coordinates the Institute’s drugs and crime research portfolio.

Now new urgency is infusing the drug court movement, as the nationwide opioid crisis exacts an unprecedented toll and the rates of drug overdose deaths increase for all age groups. [2] A presidential commission in November 2017 called for a comprehensive federal assault on opioids, with millions of dollars in new funding committed to enhancing the drug treatment and rehabilitative services of adult drug courts and other PSCs. [3] The commission also called on all 93 federal judicial jurisdictions to establish federal drug courts, noting that as of 2015 only 27 federal district courts were operating as drug courts.

Read the related article “Identifying New Illicit Drugs and Sounding the Alarm in Real Time”

At the opioid commission’s urging, new federal dollars are also flowing to veterans treatment courts, a prominent PSC category on a steep growth trajectory over the past decade. The Department of Veterans Affairs reports that more than 550 court dockets are now dedicated to former and active-duty service members who are facing criminal charges, some of whom have life-threatening substance use disorders. [4]

The PSC model, like research on the courts’ development and impact, is dynamic at its core. The model, while theoretically grounded, must be sufficiently flexible to accommodate varying needs across jurisdictions as well as shifts in populations, drug use, resources, and other factors. Thus, a fundamental duality has characterized the evolution of the nation’s drug courts, said Truitt. Communities balance grassroots development of drug courts tailored to a unique set of local needs against a commitment to a known and sustainable program model.

“These two dynamics are not at odds in successful problem-solving courts where monitoring and assessment are routine,” Truitt said. Over time and across jurisdictions, a general set of practices evolves, creating a new program model. NIJ is charged with objectively examining new models, strengthening their components through applied research, and working with other federal agencies and research partners to develop and recommend best practices. [5]

Research amassed and analyzed through NIJ research grants and other sources suggests that drug courts are generally beneficial in terms of reducing recidivism and drug relapse. As NIJ’s quasi-experimental Multisite Adult Drug Court Evaluation (MADCE) concluded, “Drug courts produce significant reductions in drug relapse … [and] criminal behavior.” [6]

Research has also established, however, that the ultimate question — the extent to which any given drug court is beneficial on balance — has a complex answer that depends on a number of factors, including that court’s targeted offender population; the quality, type, and cost of treatment; and cost-benefit measures that take into account multiple categories of spending and savings that inform success or failure.

A priority for agencies that fund and assist drug courts is ongoing evaluation of the courts’ cost-efficiency. Agencies look at this cost-efficiency in terms of outcomes for addicted persons, benefits for the criminal justice system, return on tax dollars expended, and preservation of fundamental justice values — such as defendants' due process rights — in nontraditional court settings where the degree of discretion accorded to judges is exceptional. Federally supported training of court staff, in turn, focuses largely on ensuring that court standards and practices reflect the latest and best research in the field. Carolyn Hardin, chief of research and training for the National Association of Drug Court Professionals (NADCP), a leading provider of PSC training, said NADCP court trainers work continually to turn knowledge into practice. “Research has identified which elements of drug courts produce the best results,” she said. “Our priority is to train drug courts and other treatment courts on following research-based best practices to improve outcomes like recidivism and save money. We call that ‘fidelity to the model.’”

Genesis of the PSC Philosophy

At its inception, the PSC concept was as simple as it was revolutionary. Problem-solving courts incorporated philosophical elements of community-focused policing, emphasizing treatment over punishment. As New York’s Center for Court Innovation, a leader in PSC development, has noted:

Problem-solving justice traces its roots to community and problem-oriented policing, which encourages officers to identify patterns of crime, address the underlying conditions that fuel crime, and actively engage the community. Today, thousands of problem-solving courts are testing new approaches to difficult cases where social, human, and legal problems intersect. [7]

An inclusive approach, summoning all stakeholders to the table and engaging all of them in the outcomes, has been central to PSC effectiveness. An Office of Justice Programs brochure on drug courts identified elements of a typical drug court team: [8]

Although drug courts vary in target populations and resources, programs are generally managed by a multidisciplinary team including judges, prosecutors, defense attorneys, community corrections, social workers, and treatment service professionals.

Cautionary notes were sounded by NIJ, however, soon after the First National Drug Court Conference in December 1993, where a multitude of divergent early PSC approaches surfaced, suggesting a need for universal norms. An NIJ paper stated, in reference to that conference: [9]

The character of innovation and collaboration between justice and treatment systems was revealed to be broader and deeper than perhaps the simple outline of the original drug court model would have suggested. The diversity and variation in approaches also underscored the critical need for defining the boundaries of what a drug court is and what a drug court is not — in other words, for defining some parameters and basic standards for drug courts.

To rein in the early proliferation of drug court approaches, participants at the first drug court conference adopted a list of 10 elements vital to the success of a drug court. [10] That early objective-setting exercise foreshadowed the 10 key components of drug courts, issued by the federal Drug Courts Program Office in 1997. [11] The key components would serve as parameters for drug court practices, models, and evaluation.

In 1994, Congress broadly committed federal money to expanding state and local drug courts through the Violent Crime Control and Law Enforcement Act. The statute made development of PSC operating norms imperative. The July 1995 “National Institute of Justice Update” from then-NIJ Director Jeremy Travis favorably observed, “The need to establish appropriate drug court standards is particularly important to help ensure that Federal funds are spent on implementing a clearly defined concept.”

Best Practices and Models Emerge

Today’s drug courts are guided by best-practice research substantially driven by NIJ, which managed two seminal adult drug court studies:

A quasi-experimental, longitudinal examination of an adult drug court in Multnomah County (Portland, Oregon), resulting in the 2007 report The Impact of a Mature Drug Court Over 10 Years of Operation: Recidivism and Costs (Multnomah Study).
The Multi-Site Adult Drug Court Evaluation (MADCE), a quasi-experimental evaluation of individuals on probation in 23 adult drug courts and six comparison jurisdictions in eight states.

The Multnomah Study broke ground by establishing that, over a period of at least five years per defendant, drug courts were more economical than traditional criminal court processes. The study looked at 6,500 drug court cases and 4,600 cases processed outside the drug court model, finding that the cost per person in drug courts was $1,392 less than the cost per person through the conventional route. [12] Factors contributing to that economy included saved prison days.

It should be noted that, as quasi-experimental research designs, both the Multnomah Study and MADCE faced inherent limitations on the strength of their findings. Unlike a randomized controlled trial (RCT) — which measures and compares experimental effects on randomly selected treatment groups and control groups in order to precisely gauge an experimental treatment’s impact — quasi-experimental designs typically lack the benefit of random selection of subjects, introducing a risk of biased results, a phenomenon known as selection bias.

For a retrospective study such as Multnomah (looking back 10 years), however, an RCT is not feasible. The investigators in the wide-scope MADCE study noted that their quasi-experimental design offered advantages in that instance, including more generalizable results from multiple sites across the country, and the fact that the large pooled sample and data collection allowed them “to open the ‘black box’ of effective drug court practices far beyond most prior studies.” [13] Moreover, equivalent interview and records information obtained for drug court and the comparison group of individuals on probation were used to match research subjects for statistical controls on individual, court, and jurisdiction factors.

Where RCTs are feasible and a better fit, however, they offer clear advantages over quasi-experimental studies at risk of selection bias.

“Before we can judge a drug court program to be effective, we first must understand the importance of selection,” explained NIJ Director David B. Muhlhausen. “It can be astoundingly difficult to distinguish between what is working and what is not, and nowhere is this predicament truer than when the criminal justice system tries to change human behavior.”

For example, individuals volunteering entry into a drug court program may be more motivated than individuals not seeking the benefits of the program, Muhlhausen said. In other cases, judges may carefully select defendants for drug court participation based on characteristics that they believe will most likely yield beneficial results, he said.

“Such motivational factors and other similar factors are often invisible to those assessing effectiveness,” said Muhlhausen. “Failure to account for these factors can produce a spurious association between drug court participation and recidivism and substance abuse outcomes.”

Muhlhausen added that the limited number of RCTs that did not suffer from high attrition fail to offer clear evidence that drug courts reduce recidivism. He underscored the need to use RCTs to rigorously evaluate drug court programs in the United States to gauge their effectiveness.

MADCE gathered data from 1,157 drug court participants and 627 comparison group of individuals on probation in 29 U.S. jurisdictions over five years, with a final report issued in 2011. MADCE researchers [14] found that drug court participants reported less drug use than comparable individuals convicted of an offense (56% vs. 76%) and were less likely to test positive for drug use (29% vs. 46%). Participants reported less criminal activity after entering drug court (40% vs. 53%), with fewer rearrests (52% vs. 62%) than comparable persons. Moreover, although treatment investment costs were higher for drug court participants, they experienced less recidivism than comparable individuals, and drug courts saved an average of $5,680 to $6,208 per person overall. [15]

In sum, savings associated with avoided victim costs and criminal justice system costs were greater with drug courts than conventional criminal dockets due to fewer crimes, rearrests, and incarcerations (see exhibit 1).

*Difference is statistically significant ( p <0.01).

Source: John Roman, “Cost-Benefit Analysis of Criminal Justice Reforms,” NIJ Journal 272, September 2013, 36.

MADCE data revealed certain limits of drug court effectiveness, pointing to a better return on investment for more serious offenders with drug disorders, as well as the importance of performing appropriate cost-benefit analyses in continuing assessments of drug courts. A MADCE researcher, writing on drug court impact as measured by a detailed bottom-up, cost-benefit analysis method, concluded: [16]

Drug courts prevent many petty crimes and a few serious crimes. In fact, the CBA [cost-benefit analysis] results showed that those few serious crimes drive much of the drug court effect; if we remove those outliers, the benefits of drug courts barely exceed the cost. This finding suggests that although drug courts may reduce recidivism among many types of offenders, drug courts that target serious criminal offenders with a high need for substance abuse treatment will produce the most effective interventions and a maximum return on investment.

Today, the critical MADCE insight that drug courts are better off targeting certain types of individuals committing crime is a point of emphasis for federally contracted drug court trainers and a best practice for drug courts generally. Hardin of the NADCP said:

Fifteen to twenty years ago we knew drug courts should serve offenders with substance use disorders, and we trained courts on identifying and serving this population. Well, now the research is very clear. Drug courts are most effective when serving high-risk, high-need offenders. Today, we train jurisdictions on what that means. We say, "Okay, if you’re going to be doing drug court, your target population has to be based on the research. This means offenders who are assessed to be both at high risk of reoffending and in high need of services. So what does that look like in your community?"

The steady refinement of a drug court model anchored in research-based principles can only take drug courts as far as local policy and resource choices permit, NIJ’s Truitt cautioned. Thus, while the model is informed by research establishing what drug courts do best — targeting high-risk, high-need, drug-using individuals committing crimes to efficiently curb recidivism and relapse — not all drug courts do so.

“If the target population is relatively high in risk and need,” Truitt said, “then the program should yield differences in relapse, recidivism, and other outcomes that translate into lower criminal justice costs and other public costs. That return on investment will not be achieved unless the program is fully implemented, the most burdensome population is targeted, and local resources are compatible with targeted offender risk, need, and responsivity considerations.”

In 2012, key information from NIJ-supported research was gathered and translated into practice terms under a joint Adult Drug Court Research to Practice Initiative (R2P) with the Bureau of Justice Assistance (BJA). The R2P program — a collaboration of those Department of Justice branches working with research and practice experts — identified seven program design features for adult drug courts: [17]

Screening and assessment: Legal and behavior screening, and assessment of risk, needs, and responsivity.
Target population: The specific offender subgroup(s) the program is designed to serve.
Procedural and distributive justice: Fair process and equitable outcomes, and the perception of them, through graduated sanctions and incentives, full information regarding compliance, and meaningful responses to participants.
Judicial interaction: Decisions based on frequent and respectful interactions with defendants and a clear understanding of program resources.
Monitoring: Community-based surveillance and supervision to manage compliance, including drug testing.
Treatment and other services: Alcohol and other drug treatment in addition to employment and other rehabilitative services.
Relapse prevention, aftercare, and community integration: Identifying triggers and supports to prevent relapse.

Since the inception of drug courts, the literature in the field has stressed the importance of continual monitoring (by court management) and evaluation (by objective outside entities). [18] The perceived need for vigilance reflects the importance of both keeping a close watch on public spending and striking an appropriate balance between defendants’ legal rights and drug court judges’ discretionary authority.

See “Due Process and the Role of Judges”

A Research Road Map for Veterans Treatment Courts

As part of the federal response to the nation’s opioid emergency, funding in the treatment court field has surged. The president’s fiscal year 2018 opioid budget provided $75 million for adult treatment drug courts, up from $43 million in FY 2017, and $20 million for veterans treatment courts, up from $7 million in 2017. Both are funded under the Adult Drug Court Discretionary Grant Program. A primary conduit of federal financial support for various types of problem-solving courts is BJA, which in turn funds many of NIJ’s PSC research projects.

Like drug court practitioners who were empowered by the findings of the drug court multisite study a few years ago, veterans treatment court professionals await research now in development that is designed to illuminate best practices in that venue. The first phase is NIJ’s Multisite Evaluation of Veterans Treatment Courts, which gathers information about process and participant outcomes from eight veterans courts. The study is funded by BJA and coordinated with the Department of Veterans Affairs and the Substance Abuse and Mental Health Services Administration of the Department of Health and Human Services.

Sean Clark, the national coordinator of the Veterans Justice Outreach program at the Department of Veterans Affairs, regards the NIJ evaluation as a vital step for defining the future of veterans treatment courts. Currently, he said, veterans court trainers are “extrapolating from what works in [adult] treatment courts that are not veteran-specific. Building that body of research and that knowledge base about veterans treatment courts in particular is the key first step to be able to say, ‘This is what needs to happen next.’”

According to Truitt, who manages the project, the study’s assessment of implementation and intermediate outcomes of diverse veterans treatment courts explores target populations and key issues (e.g., violent offending and mental and physical health), adherence to problem-solving principles, and service access and delivery. Looking ahead, NIJ is developing plans for an impact and cost evaluation of veterans treatment courts using RCTs and other rigorous research designs, she said. That next phase of research will examine unique program elements, such as veteran peer-to-peer mentoring and use of remote technologies to leverage treatment and supervision.

Clark at the Department of Veterans Affairs said one critical research need the veterans multisite study is expected to address is for screening tools to better identify those veterans who would benefit most from placement in a veterans treatment court.

Problem-solving courts have evolved from a novel outlier to a ubiquitous feature of the American justice landscape, with more than 3,000 drug courts and other PSCs nationwide.

“Moving forward, more scientifically rigorous RCTs are needed to confirm whether drugs courts are, in fact, as effective as the quasi-experimental evaluations indicate,” cautions NIJ’s Muhlhausen.

NIJ research will continue to objectively examine new models, strengthen new components by applying research-based principles, and collaborate with federal and other research partners on recommendations for practice.

About This Article

This article was published as part of NIJ Journal issue number 281 , released October 2019.

[note 1] “The Treatment Court Movement,” National Association of Drug Court Professionals; and Lauren Kirschner, “Remembering the Drug Court Revolution,” Pacific Standard, April 24, 2014.

[note 2] Centers for Disease Control and Prevention, Drug Overdose Deaths in the United States, 1999–2017 , National Center for Health Statistics Data Brief 329, November 2018.

[note 3] The President’s Commission on Combating Drug Addiction and the Opioid Crisis , Final report, November 2017, 16.

[note 4] Barbara Goldberg, “Opioid abuse crisis takes heavy toll on U.S. Veterans,” Reuters, November 10, 2017.

[note 5] Other PSC categories that have benefited from NIJ research are mental health courts, adult reentry courts, and tribal courts.

[note 6] Shelli B. Rossman, John K. Roman, Janine M. Zweig, Michael Rempel, and Christine H. Lindquist, “ The Multi-Site Adult Drug Court Evaluation: Executive Summary ,” Final report to NIJ, December 2011, 5, award number 2003-DC-BX-1001, NCJ 237108.

[note 7] “Problem-Solving Justice,” Center for Court Innovation.

[note 8] U.S. Department of Justice, Office of Justice Programs (NIJ, BJA, OJJDP), “ Drug Courts ,” May 2018.

[note 9] “ Justice and Treatment Innovation: The Drug Court Movement. A Working Paper of the First National Drug Court Conference, December 1993 ,” Final report to NIJ, award number OJP-94-076M, October 1994, 36, NCJ 149260.

[note 10] Bureau of Justice Assistance and National Association of Drug Court Professionals, Defining Drug Courts: The Key Components , Drug Courts Resource Series, 1997 (reprinted 2004), NCJ 205621. The key components are (1) Drug courts integrate alcohol and other drug treatment services with justice system case processing; (2) Using a nonadversarial approach, prosecution and defense counsel promote public safety while protecting participants’ due process rights; (3) Eligible participants are identified early and promptly placed in the drug court program; (4) Drug courts provide access to a continuum of alcohol, drug, and other related treatment and rehabilitation services; (5) Abstinence is monitored by frequent alcohol and other drug testing; (6) A coordinated strategy governs drug court responses to participants’ compliance; (7) Ongoing judicial interaction with each drug court participant is essential; (8) Monitoring and evaluation measure the achievement of program goals and gauge effectiveness; (9) Continuing interdisciplinary education promotes effective drug court planning, implementation, and operations; (10) Forging partnerships among drug courts, public agencies, and community-based organizations generates local support and enhances drug court program effectiveness.

[note 11] Rachel Porter, Michael Rempel, and Adam Mansky, What Makes a Court Problem-Solving? Universal Performance Indicators for Problem-Solving Courts, submitted to the State Justice Institute (New York: Center for Court Innovation, February 2010), 9.

[note 12] Michael W. Finnegan, Shannon Carey, and Anton Cox, “ Impact of a Mature Drug Court Over 10 Years: Recidivism and Costs, ” Executive Summary, Final report to U.S. Department of Justice, award number 2005M073, IV, July 2007, NCJ 219225.

[note 13] Rossman, Roman, Zweig, Rempel, and Lindquist, “ The Multi-Site Adult Drug Court Evaluation: Executive Summary .”

[note 14] Research for the Multi-Site Adult Drug Court Evaluation was performed by the Urban Institute, the Center for Court Innovation, and the Research Triangle Institute.

[note 15] Rossman, Roman, Zweig, Rempel, and Lindquist, “ The Multi-Site Adult Drug Court Evaluation: Executive Summary .”

[note 16] John Roman, “ Cost-Benefit Analysis of Criminal Justice Reforms ,” NIJ Journal 272, September 2013, 36.

[note 17] Bureau of Justice Assistance and National Institute of Justice, “ Seven Program Design Features: Adult Drug Court Principles, Research, and Practice ,” Research to Practice fact sheet, January 2012, NCJ 248701.

[note 18] American University, “Challenges and Solutions to Implementing Problem-Solving Courts from the Traditional Court Management Perspective,” Bureau of Justice Assistance National Training and Technical Assistance Project, June 2008, 8, award number 2005-DD-BX-K053.

About the author

Paul A. Haskins is a social science writer and contractor with Leidos.

Cite this Article

Are ‘Forever Chemicals’ a Forever Problem?

The environmental protection agency says “forever chemicals” must be removed from tap water. but they lurk in much more of what we eat, drink and use..

This transcript was created using speech recognition software. While it has been reviewed by human transcribers, it may contain errors. Please review the episode audio before quoting from this transcript and email [email protected] with any questions.

From “The New York Times,” I’m Sabrina Tavernise. And this is “The Daily.”

[THEME MUSIC]

This month for the first time, the Environmental Protection Agency began to regulate a class of synthetic chemicals, known as forever chemicals, in America’s drinking water. But the chemicals, which have been linked to liver disease and other serious health problems, are in far more than just our water supply. Today, my colleague Kim Tingley explains.

It’s Wednesday, April 17.

So Kim, any time the EPA announces a regulation, I think we all sort of take notice because implicit in it is this idea that we have been exposed to something — something bad, potentially, lead or asbestos. And recently, the EPA is regulating a type of chemical known as PFAS So for those who don’t know, what are PFAS chemicals

Yeah, so PFAS stands for per and polyfluoroalkyl substances. They’re often called forever chemicals just because they persist so long in the environment and they don’t easily break down. And for that reason, we also use them in a ton of consumer products. They’re in makeup. They’re in carpet. They’re in nonstick cookware. They’re in food packaging, all sorts of things.

Yeah, I feel like I’ve been hearing about these chemicals actually for a very long time. I mean, nonstick pans, Teflon — that’s the thing that’s in my mind when I think PFAS.

Absolutely. Yeah, this class of chemicals has been around for decades. And what’s really important about this is that the EPA has decided, for the first time, to regulate them in drinking water. And that’s a ruling that stands to affect tens of millions of people.

So, help me understand where these things came from and how it’s taken so long to get to the point where we’re actually regulating them.

So, they really actually came about a long time ago. In 1938, DuPont, the people who eventually got us to Teflon, they were actually looking for a more stable kind of refrigerant. And they came upon this kind of chemical, PFAS. The thing that all PFAS chemicals have is a really strong bond between carbon atoms and fluorine atoms. This particular pairing is super strong and super durable.

They have water repellent properties. They’re stain resistant. They’re grease resistant. And they found a lot of uses for them initially in World War II. They were using them as part of their uranium enrichment process to do all these kinds of things. And then —

Well, good thing it’s Teflon.

In the 1950s is when they really started to come out as commercial products.

Even burned food won’t stick to Teflon. So it’s always easy to clean.

So, DuPont started using it in Teflon pans.

Cookware never needs scouring if it has DuPont Teflon.

And then another company, 3M also started using a kind of PFAS —

Scotchgard fabric protector. It keeps ordinary spills from becoming extraordinary stains.

— in one of their big products, Scotchgard. So you probably remember spraying that on your shoes if you want to make your shoes waterproof.

Use Scotchgard fabric protector and let your cup runneth over.

Right — miracle product, Scotchgard, Teflon. But of course, we’re talking about these chemicals because they’ve been found to pose health threats. When does that risk start to surface?

Yeah, so it’s pretty early on that DuPont and 3M start finding effects in animals in studies that they’re running in house.

Around the mid ‘60s, they start seeing that PFAS has an effect on rats. It’s increasing the liver and kidney weights of the rats. And so that seems problematic. And they keep running tests over the next decade and a half. And they try different things with different animals.

In one study, they gave monkeys really, really high levels of PFAS. And those monkeys died. And so they have a pretty strong sense that these chemicals could be dangerous. And then in 1979, they start to see that the workers that are in the plants manufacturing, working with these chemicals, that they’re starting to have higher rates of abnormal liver function. And in a Teflon plant, they had some pregnant workers that were working with these chemicals. And one of those workers in 1981 gave birth to a child who had some pretty severe birth defects.

And then by the mid 1980s, DuPont figures out that it’s not just their workers who are being exposed to these chemicals, but communities that are living in areas surrounding their Teflon plant, particularly the one in Parkersburg, West Virginia, that those communities have PFAS in their tap water.

Wow, so based on its own studies, DuPont knows its chemicals are making animals sick. They seem to be making workers sick. And now they found out that the chemicals have made their way into the water supply. What do they do with that information?

As far as we know, they didn’t do much. They certainly didn’t tell the residents of Parkersburg who were drinking that water that there was anything that they needed to be worried about.

How is that possible? I mean, setting aside the fact that DuPont is the one actually studying the health effects of its own chemicals, presumably to make sure they’re safe, we’ve seen these big, regulating agencies like the EPA and the FDA that exist in order to watch out for something exactly like this, a company that is producing something that may be harming Americans. Why weren’t they keeping a closer watch?

Yeah, so it goes kind of back to the way that we regulate chemicals in the US. It goes through an act called the Toxic Substances Control Act that’s administered by the EPA. And basically, it gives companies a lot of room to regulate themselves, in a sense. Under this act they have a responsibility to report to the EPA if they find these kinds of potential issues with a chemical. They have a responsibility to do their due diligence when they’re putting a chemical out into the environment.

But there’s really not a ton of oversight. The enforcement mechanism is that the EPA can find them. But this kind of thing can happen pretty easily where DuPont keeps going with something that they think might really be a problem and then the fine, by the time it plays out, is just a tiny fraction of what DuPont has earned from producing these chemicals. And so really, the incentive is for them to take the punishment at the end, rather than pull it out early.

So it seems like it’s just self-reporting, which is basically self-regulation in a way.

Yeah, I think that is the way a lot of advocacy groups and experts have characterized it to me, is that chemical companies are essentially regulating themselves.

So how did this danger eventually come to light? I mean, if this is in some kind of DuPont vault, what happened?

Well, there’s a couple different things that started to happen in the late ‘90s.

The community around Parkersburg, West Virginia, people had reported seeing really strange symptoms in their animals. Cows were losing their hair. They had lesions. They were behaving strangely. Some of their calves were dying. And a lot of people in the community felt like they were having health problems that just didn’t really have a good answer, mysterious sicknesses, and some cases of cancers.

And so they initiate a class action lawsuit against DuPont. As part of that class action lawsuit, DuPont, at a certain point, is forced to turn over all of their internal documentation. And so what was in the files was all of that research that we mentioned all of the studies about — animals, and workers, the birth defects. It was really the first time that the public saw what DuPont and 3M had already seen, which is the potential health harms of these chemicals.

So that seems pretty damning. I mean, what happened to the company?

So, DuPont and 3M are still able to say these were just a few workers. And they were working with high levels of the chemicals, more than a person would get drinking it in the water. And so there’s still an opportunity for this to be kind of correlation, but not causation. There’s not really a way to use that data to prove for sure that it was PFAS that caused these health problems.

In other words, the company is arguing, look, yes, these two things exist at the same time. But it doesn’t mean that one caused the other.

Exactly. And so one of the things that this class action lawsuit demands in the settlement that they eventually reach with DuPont is they want DuPont to fund a formal independent health study of the communities that are affected by this PFAS in their drinking water. And so they want DuPont to pay to figure out for sure, using the best available science, how many of these health problems are potentially related to their chemicals.

And so they ask them to pay for it. And they get together an independent group of researchers to undertake this study. And it ends up being the first — and it still might be the biggest — epidemiological study of PFAS in a community. They’ve got about 69,000 participants in this study.

Wow, that’s big.

It’s big, yeah. And what they ended up deciding was that they could confidently say that there was what they ended up calling a probable link. And so they were really confident that the chemical exposure that the study participants had experienced was linked to high cholesterol, ulcerative colitis, thyroid disease, testicular cancer, kidney cancer, and pregnancy induced hypertension.

And so those were the conditions that they were able to say, with a good degree of certainty, were related to their chemical exposure. There were others that they just didn’t have the evidence to reach a strong conclusion.

So overall, pretty substantial health effects, and kind of vindicates the communities in West Virginia that were claiming that these chemicals were really affecting their health.

Absolutely. And as the years have gone on, that was sort of just the beginning of researchers starting to understand all the different kinds of health problems that these chemicals could potentially be causing. And so since the big DuPont class action study, there’s really just been like this building and building and building of different researchers coming out with these different pieces of evidence that have accumulated to a pretty alarming picture of what some of the potential health outcomes could be.

OK, so that really kind of brings us to the present moment, when, at last, it seems the EPA is saying enough is enough. We need to regulate these things.

Yeah, it seems like the EPA has been watching this preponderance of evidence accumulate. And they’re sort of deciding that it’s a real health problem, potentially, that they need to regulate.

So the EPA has identified six of these PFAS chemicals that it’s going to regulate. But the concern that I think a lot of experts have is that this particular regulation is not going to keep PFAS out of our bodies.

We’ll be right back.

So, Kim, you just said that these regulations probably won’t keep PFAS chemicals out of our bodies. What did you mean?

Well, the EPA is talking about regulating these six kinds of PFAS. But there are actually more than 10,000 different kinds of PFAS that are already being produced and out there in the environment.

And why those six, exactly? I mean, is it because those are the ones responsible for most of the harm?

Those are the ones that the EPA has seen enough evidence about that they are confident that they are probably causing harm. But it doesn’t mean that the other ones are not also doing something similar. It’s just sort of impossible for researchers to be able to test each individual chemical compound and try to link it to a health outcome.

I talked to a lot of researchers who were involved in this area and they said that they haven’t really seen a PFAS that doesn’t have a harm, but they just don’t have information on the vast majority of these compounds.

So in other words, we just haven’t studied the rest of them enough yet to even know how harmful they actually are, which is kind of alarming.

Yeah, that’s right. And there’s just new ones coming out all the time.

Right. OK, so of the six that the EPA is actually intending to regulate, though, are those new regulations strict enough to keep these chemicals out of our bodies?

So the regulations for those six chemicals really only cover getting them out of the drinking water. And drinking water only really accounts for about 20 percent of a person’s overall PFAS exposure.

So only a fifth of the total exposure.

Yeah. There are lots of other ways that you can come into contact with PFAS. We eat PFAS, we inhale PFAS. We rub it on our skin. It’s in so many different products. And sometimes those products are not ones that you would necessarily think of. They’re in carpets. They’re in furniture. They’re in dental floss, raincoats, vinyl flooring, artificial turf. All kinds of products that you want to be either waterproof or stain resistant or both have these chemicals in them.

So, the cities and towns are going to have to figure out how to test for and monitor for these six kinds of PFAS. And then they’re also going to have to figure out how to filter them out of the water supply. I think a lot of people are concerned that this is going to be just a really expensive endeavor, and it’s also not really going to take care of the entire problem.

Right. And if you step back and really look at the bigger problem, the companies are still making these things, right? I mean, we’re running around trying to regulate this stuff at the end stage. But these things are still being dumped into the environment.

Yeah. I think it’s a huge criticism of our regulatory policy. There’s a lot of onus put on the EPA to prove that a harm has happened once the chemicals are already out there and then to regulate the chemicals. And I think that there’s a criticism that we should do things the other way around, so tougher regulations on the front end before it goes out into the environment.

And that’s what the European Union has been doing. The European Chemicals Agency puts more of the burden on companies to prove that their products and their chemicals are safe. And the European Chemicals Agency is also, right now, considering just a ban on all PFAS products.

So is that a kind of model, perhaps, of what a tough regulation could look like in the US?

There’s two sides to that question. And the first side is that a lot of people feel like it would be better if these chemical companies had to meet a higher standard of proof in terms of demonstrating that their products or their chemicals are going to be safe once they’ve been put out in the environment.

The other side is that doing that kind of upfront research can be really expensive and could potentially limit companies who are trying to innovate in that space. In terms of PFAS, specifically, this is a really important chemical for us. And a lot of the things that we use it in, there’s not necessarily a great placement at the ready that we can just swap in. And so it’s used in all sorts of really important medical devices or renewable energy industries or firefighting foam.

And in some cases, there are alternatives that might be safer that companies can use. But in other cases, they just don’t have that yet. And so PFAS is still really important to our daily lives.

Right. And that kind of leaves us in a pickle because we know these things might be harming us. Yet, we’re kind of stuck with them, at least for now. So, let me just ask you this question, Kim, which I’ve been wanting to ask you since the beginning of this episode, which is, if you’re a person who is concerned about your exposure to PFAS, what do you do?

Yeah. So this is really tricky and I asked everybody this question who I talked to. And everybody has a little bit of a different answer based on their circumstance. For me what I ended up doing was getting rid of the things that I could sort of spot and get rid of. And so I got rid of some carpeting and I checked, when I was buying my son a raincoat, that it was made by a company that didn’t use PFAS.

It’s also expensive. And so if you can afford to get a raincoat from a place that doesn’t manufacture PFAS, it’s going to cost more than if you buy the budget raincoat. And so it’s kind of unfair to put the onus on consumers in that way. And it’s also just not necessarily clear where exactly your exposure is coming from.

So I talk to people who said, well, it’s in dust, so I vacuum a lot. Or it’s in my cleaning products, so I use natural cleaning products. And so I think it’s really sort of a scattershot approach that consumers can take. But I don’t think that there is a magic approach that gets you a PFAS-free life.

So Kim, this is pretty dark, I have to say. And I think what’s frustrating is that it feels like we have these government agencies that are supposed to be protecting our health. But when you drill down here, the guidance is really more like you’re on your own. I mean, it’s hard not to just throw up your hands and say, I give up.

Yeah. I think it’s really tricky to try to know what you do with all of this information as an individual. As much as you can, you can try to limit your individual exposure. But it seems to me as though it’s at a regulatory level that meaningful change would happen, and not so much throwing out your pots and pans and getting new ones.

One thing about PFAS is just that we’re in this stage still of trying to understand exactly what it’s doing inside of us. And so there’s a certain amount of research that has to happen in order to both convince people that there’s a real problem that needs to be solved, and clean up what we’ve put out there. And so I think that we’re sort of in the middle of that arc. And I think that that’s the point at which people start looking for solutions.

Kim, thank you.

Here’s what else you should know today. On Tuesday, in day two of jury selection for the historic hush money case against Donald Trump, lawyers succeeded in selecting 7 jurors out of the 12 that are required for the criminal trial after failing to pick a single juror on Monday.

Lawyers for Trump repeatedly sought to remove potential jurors whom they argued were biased against the president. Among the reasons they cited were social media posts expressing negative views of the former President and, in one case, a video posted by a potential juror of New Yorkers celebrating Trump’s loss in the 2020 election. Once a full jury is seated, which could come as early as Friday, the criminal trial is expected to last about six weeks.

Today’s episode was produced by Clare Toeniskoetter, Shannon Lin, Summer Thomad, Stella Tan, and Jessica Cheung, with help from Sydney Harper. It was edited by Devon Taylor, fact checked by Susan Lee, contains original music by Dan Powell, Elisheba Ittoop, and Marion Lozano, and was engineered by Chris Wood.

Our theme music is by Jim Brunberg and Ben Landsverk of Wonderly.

That’s it for The Daily. I’m Sabrina Tavernise. See you tomorrow.

April 19, 2024 • 30:42 The Supreme Court Takes Up Homelessness
April 18, 2024 • 30:07 The Opening Days of Trump’s First Criminal Trial
April 17, 2024 • 24:52 Are ‘Forever Chemicals’ a Forever Problem?
April 16, 2024 • 29:29 A.I.’s Original Sin
April 15, 2024 • 24:07 Iran’s Unprecedented Attack on Israel
April 14, 2024 • 46:17 The Sunday Read: ‘What I Saw Working at The National Enquirer During Donald Trump’s Rise’
April 12, 2024 • 34:23 How One Family Lost $900,000 in a Timeshare Scam
April 11, 2024 • 28:39 The Staggering Success of Trump’s Trial Delay Tactics
April 10, 2024 • 22:49 Trump’s Abortion Dilemma
April 9, 2024 • 30:48 How Tesla Planted the Seeds for Its Own Potential Downfall
April 8, 2024 • 30:28 The Eclipse Chaser
April 7, 2024 The Sunday Read: ‘What Deathbed Visions Teach Us About Living’

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Featuring Kim Tingley

Produced by Clare Toeniskoetter , Shannon M. Lin , Summer Thomad , Stella Tan and Jessica Cheung

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Engineered by Chris Wood

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The Environmental Protection Agency has begun for the first time to regulate a class of synthetic chemicals known as “forever chemicals” in America’s drinking water.

Kim Tingley, a contributing writer for The New York Times Magazine, explains how these chemicals, which have been linked to liver disease and other serious health problems, came to be in the water supply — and in many more places.

On today’s episode

Kim Tingley , a contributing writer for The New York Times Magazine.

A single water drop drips from a faucet.

Background reading

“Forever chemicals” are everywhere. What are they doing to us?

The E.P.A. issued its rule about “forever chemicals” last week.

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The Daily is made by Rachel Quester, Lynsea Garrison, Clare Toeniskoetter, Paige Cowett, Michael Simon Johnson, Brad Fisher, Chris Wood, Jessica Cheung, Stella Tan, Alexandra Leigh Young, Lisa Chow, Eric Krupke, Marc Georges, Luke Vander Ploeg, M.J. Davis Lin, Dan Powell, Sydney Harper, Mike Benoist, Liz O. Baylen, Asthaa Chaturvedi, Rachelle Bonja, Diana Nguyen, Marion Lozano, Corey Schreppel, Rob Szypko, Elisheba Ittoop, Mooj Zadie, Patricia Willens, Rowan Niemisto, Jody Becker, Rikki Novetsky, John Ketchum, Nina Feldman, Will Reid, Carlos Prieto, Ben Calhoun, Susan Lee, Lexie Diao, Mary Wilson, Alex Stern, Dan Farrell, Sophia Lanman, Shannon Lin, Diane Wong, Devon Taylor, Alyssa Moxley, Summer Thomad, Olivia Natt, Daniel Ramirez and Brendan Klinkenberg.

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Support for more political parties in the U.S. is higher among adults under age 50

With a record share of Americans expressing unfavorable views of both major parties , 37% of Americans wish there were more political parties to choose from, according to a recent Pew Research Center survey.

Pew Research Center conducted this analysis to understand Americans’ views about the prospect of additional political parties, as part of an in-depth study of how Americans view the state of U.S. politics today . For this study, we surveyed 8,480 U.S. adults from July 10 to July 16, 2023.

Everyone who took part in the current survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for this analysis , along with responses, and the survey methodology .

A horizontal stacked bar chart showing that adults younger than 50 are more supportive of additional political parties than those 50 and older.

Yet there is considerable skepticism that having additional parties would make it easier to solve the nation’s problems. About a quarter of adults (26%) say this would make it easier to solve problems, while nearly as many (24%) say it would not.

Americans’ views on the idea of having more political parties differ by age and partisanship: Nearly half (48%) of adults under age 30 and a similar share (46%) of those 30 to 49 say they often wish there were more political parties. That compares with a third of those ages 50 to 64 and just 21% of those 65 and older who say the same.
Democrats and Democratic-leaning independents (44%) are more likely than Republicans and Republican leaners (32%) to say they often wish there were more political parties. In both partisan coalitions, leaners – those who identify as independent or another party but lean toward one of the two major parties – are more likely to wish for additional parties. Democratic leaners are especially likely to say this.

Would more parties help solve the country’s problems?

A horizontal stacked bar chart showing that younger Americans are much more likely than older adults to say having more parties would make it easier to solve the country’s problems.

Just as younger Americans are more likely to express a desire for more parties, they are also more likely to think additional parties would make it easier to solve the country’s problems.

About four-in-ten Americans ages 18 to 29 (39%) say they think more parties would make problem-solving easier. Just 12% of those 65 and older say this.

Party leaners are more likely than partisans to think additional parties would make it easier to solve the country’s problems. But Democratic leaners are more likely than Republican leaners to say this (44% vs. 29%).

Age differences in both parties

Republicans under age 50 are nearly twice as likely as those 50 and older (42% vs. 23%) to say they often wish there were more political parties. And younger Republicans are twice as likely (28% vs. 14%) to say more parties would make problem-solving easier.

A similar pattern emerges for Democrats. While about half (51%) of Democrats under the age of 50 often wish there were more parties to choose from, 31% of those 50 and older say the same. Roughly four-in-ten younger Democrats (41%) say it would be easier to solve the country’s problems with more parties, compared with 20% of older Democrats.

Two horizontal stacked bar charts showing that, in both parties, adults younger than 50 have more positive views of the possible impact of having more political parties.

Could an independent candidate win the presidency?

A horizontal stacked bar chart showing that about two-thirds of U.S. adults say it’s unlikely an independent will win the presidency in next 25 years.

As in past presidential elections, one or more independent candidates could siphon votes from the Republican and Democratic nominees in next year’s election.

However, most Americans are doubtful that an independent candidate could actually win the presidency in the next 25 years.

Only a third of Americans say it’s even somewhat likely an independent will win the presidency during this period, including just 7% who say it is very likely.

There are only modest differences in these views by age and party. About two-thirds in all age groups and in both party coalitions say it’s unlikely an independent candidate will be elected president in the next quarter century.

Note: Here are the questions used for this analysis , along with responses, and the survey methodology .

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2024 presidential primary season was one of the shortest in the modern political era, representative democracy remains a popular ideal, but people around the world are critical of how it’s working, bipartisan support for early in-person voting, voter id, election day national holiday, what do you know about the u.s. government, most popular.

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IMAGES

international guide to problem solving
International Guidelines For Problem Solving
How to solve problems in different countries.
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Problem solving
International problem-solving strategies

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Solving Country Patterns On The Gan Mosaic
Solving one problem at a time. #satire #elementaryschool #schoollunch
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Guess the Country Without the Vowels 🌎🤔
World Map Challenge: Speedrun All 193 Countries
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COMMENTS

How Do Different Cultures Solve Problems?
Explore diverse problem-solving approaches rooted in various cultures. Reflect on your own approach and consider the pros and cons of these methods. Learn how cultural lenses impact group, individual, high-context, low-context, relationship-based, and task-oriented problem-solving. Discover top tips for effective cross-cultural collaboration and inclusive, innovative solutions.
Countries that excel at problem-solving encourage critical thinking
The OECD suggests that those countries where students do best at problem solving, are not only good at teaching the core subjects, but are good at providing learning opportunities that prepare ...
The challenges of problem solving in a divided country
The challenges of problem solving in a divided country. This is the second in a five-part series of essays looking at whether the American project can survive. Read the rest of the essays here ...
PDF Pisa 2015
PISA shows that every country has room for improvement, even the top performers. With high levels of youth unemployment, rising inequality, a significant gender gap, and an urgent need to boost inclusive growth ... mathematics and collaborative problem solving as minor areas of assessment. PISA 2015 also included an assessment of young people ...
The acquisition of problem solving competence: evidence from 41
From a slightly different perspective, the country-specific amount of variance in problem solving scores that is explained by the variation in math and science performance scores (R 2) is strongly associated with the country's problem solving score (r = .77, p < .001), which suggests that the contribution of science and math competence to the ...
PDF 4 how prolemSolving perormance aries within Countries
students exceeds 24 score points on the problem-solving scale. In both countries, however, fewer than 5% of students are enrolled in a vocational study programme (Tables V.4.2 and V.4.4).
The McKinsey guide to problem solving
May 14, 2023 - Leaders today are confronted with more problems, of greater magnitude, than ever before. In these volatile times, it's natural to react based on what's worked best in the past. But when you're solving the toughest business challenges on an ongoing basis, it's crucial to start from a place of awareness.
Problem solving by country
"Problem solving by country" is published by Laurent Laborde. Let's skip past the usual suspects like YouTube, WhatsApp and Instagram.
Seeking Solutions to Global Challenges
By The New York Times. Published Oct. 7, 2021 Updated Oct. 8, 2021. This is an article from World Review: The State of Democracy, a special section that examines global policy and affairs, and is ...
How to master the seven-step problem-solving process
To discuss the art of problem solving, I sat down in California with McKinsey senior partner Hugo Sarrazin and also with Charles Conn. Charles is a former McKinsey partner, entrepreneur, executive, and coauthor of the book Bulletproof Problem Solving: The One Skill That Changes Everything [John Wiley & Sons, 2018].
UNSDG
The global problem-solving paradox. Caption: Munta Hussen, 26, is a mother of two. She lives in afar, Ethiopia. She is getting her first covid-19 vaccine as her son look on. As Secretary-General of the United Nations, I spend much of my time speaking with world leaders and taking the pulse of global trends.
What is Problem Solving? Steps, Process & Techniques
Finding a suitable solution for issues can be accomplished by following the basic four-step problem-solving process and methodology outlined below. Step. Characteristics. 1. Define the problem. Differentiate fact from opinion. Specify underlying causes. Consult each faction involved for information. State the problem specifically.
Cultural Differences and Problem Solving: An Interview with Jerome Vadon
This great image based on stereotypes gives us some fun insights into cultural differences in problem solving. [email protected] +44 0330 027 0207 or +1 (818) 532-6908 ... there is some ideas are very good, and I will probably use them to update some of the actual countries, but again, people does not see often the complexity of this joke ...
Development challenges and solutions
The challenges. UNDP's work, adapted to a range of country contexts, is framed through three broad development settings. These three development challenges often coexist within the same country, requiring tailored solutions that can adequately address specific deficits and barriers. Underpinning all three development challenges is a set of ...
Problem solving in East Africa: A contextual definition
The comparison of the findings of the contextualisation studies on problem-solving skills in the three countries shows significant similarities and only minor differences. It emerges that the search for solutions to a problem or a challenge is the final step in a structured process. Although sometimes implicit, the steps of this process in the ...
Global Issues
AIDS. HIV infections have been reduced by 59% since the peak in 1995, (by 58% among children since 2010) and AIDS-related deaths have fallen by 69% since the peak in 2004 and by 51% since 2010 ...
The global education challenge: Scaling up to tackle the learning
Among global education's most urgent challenges is a severe lack of trained teachers, particularly female teachers. An additional 9 million trained teachers are needed in sub-Saharan Africa by ...
Gender Differences in Collaborative Problem Solving, by Country
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(PDF) Gender Differences in Collaborative Problem-Solving Skills in a
We use cross-country evidence on collaborative problem-solving skills among 15-year-old students from 44 countries (N = 343,326) who participated in the 2015 Programme for International Student ...
Gender differences in collaborative problem-solving skills in a cross
Effective collaborative problem solving comprises cognitive dimensions, in which men tend to outperform women, and social dimensions in which women tend to outperform men. We extend research on between-country differences in gender gaps by considering collaborative problem solving and its association with two indicators of societal-level gender inequality. The first indicator reflects women's ...
Different countries, different customs. Problem solving 3.0 (x-post /r
problem -> try to legalize it -> no 100% support for that -> try and find sollution -> can not agree on legalising or criminalising -> legalise the sale -> keep production illegal -> fund criminal networks this way -> keep this "sollution" for 30 years.
PDF OECD member countries and Associates decided to postpone the PISA 2021
through in solving contextualised problems, remains a key feature of the PISA 2021 framework. It is used to help define the mathematical processes in which students engage as they solve problems - processes that together with mathematical reasoning (both deductive and inductive) will provide the primary reporting dimensions.
List of global issues
A global issue is a matter of public concern worldwide. This list of global issues presents problems or phenomena affecting people around the world, including but not limited to widespread social issues, economic issues, and environmental issues.Organizations that maintain or have published an official list of global issues include the United Nations, and the World Economic Forum.
PISA Scores by Country 2024
PISA test questions don't gauge memorization of facts but demand that students draw on real-world problem-solving skills and knowledge. ... 85 countries are taking part in PISA 2022, intended to take place from 26 July to 16 September 2022. Three key learning subject areas are tested: reading literacy, mathematics, and science. ...
MIT Solve
This issue disproportionately affects millions, with UNESCO estimating that about 258 million children and youth were out of school in 2018, a significant portion of which are in low and middle-income countries. The scale of the problem extends to adults as well, with the Global Education Monitoring Report indicating that 773 million adults ...
Case Study: Problem-Solving Courts in the US
Many problem-solving courts across the US continue to start in the way the first problem-solving courts did: with judges deciding to do things differently. With that said, the proliferation of problem-solving courts across the country can be traced to three primary factors: science and research; technical assistance; and changes in legal education.
Problem-Solving Courts: Fighting Crime by Treating the Offender
Problem-solving justice traces its roots to community and problem-oriented policing, which encourages officers to identify patterns of crime, address the underlying conditions that fuel crime, and actively engage the community. ... including more generalizable results from multiple sites across the country, and the fact that the large pooled ...
Are 'Forever Chemicals' a Forever Problem?
Hosted by Sabrina Tavernise. Featuring Kim Tingley. Produced by Clare Toeniskoetter , Shannon M. Lin , Summer Thomad , Stella Tan and Jessica Cheung. With Sydney Harper. Edited by Devon Taylor ...
Americans' views of having more political parties
About four-in-ten Americans ages 18 to 29 (39%) say they think more parties would make problem-solving easier. Just 12% of those 65 and older say this. Party leaners are more likely than partisans to think additional parties would make it easier to solve the country's problems. But Democratic leaners are more likely than Republican leaners to ...