Gender differences in individual variation in academic grades fail to fit expected patterns for STEM

Fewer women than men pursue careers in science, technology, engineering and mathematics (STEM), despite girls outperforming boys at school in the relevant subjects. According to the ‘variability hypothesis’, this over-representation of males is driven by gender differences in variance; greater male variability leads to greater numbers of men who exceed the performance threshold. Here, we use recent meta-analytic advances to compare gender differences in academic grades from over 1.6 million students. In line with previous studies we find strong evidence for lower variation among girls than boys, and of higher average grades for girls. However, the gender differences in both mean and variance of grades are smaller in STEM than non-STEM subjects, suggesting that greater variability is insufficient to explain male over-representation in STEM. Simulations of these differences suggest the top 10% of a class contains equal numbers of girls and boys in STEM, but more girls in non-STEM subjects.Men are over-represented in the STEM (science, technology, engineering and mathematics) workforce even though girls outperform boys in these subjects at school. Here, the authors cast doubt on one leading explanation for this paradox, the ‘variability hypothesis’.

[1]  L. R. Taylor,et al.  Aggregation, Variance and the Mean , 1961, Nature.

[2]  B. Mccandless,et al.  Teachers' marks, achievement test scores, and aptitude relations with respect to social class, race, and sex. , 1972 .

[3]  W McClure,et al.  The role of competition. , 1981, Bulletin of the New York Academy of Medicine.

[4]  S. Shields.  The Variability Hypothesis: The History of a Biological Model of Sex Differences in Intelligence , 1982, Signs: Journal of Women in Culture and Society.

[5]  Jacob Cohen,et al.  Statistical Power Analysis For The Behavioral Sciences Revised Edition , 1987 .

[6]  Alan Feingold,et al.  Gender differences in variability in intellectual abilities: A cross-cultural perspective , 1994 .

[7]  L. Hedges,et al.  Sex differences in mental test scores, variability, and numbers of high-scoring individuals. , 1995, Science.

[8]  G. Smith,et al.  Bias in meta-analysis detected by a simple, graphical test , 1997, BMJ.

[9]  Jessica Gurevitch,et al.  THE META‐ANALYSIS OF RESPONSE RATIOS IN EXPERIMENTAL ECOLOGY , 1999 .

[10]  Julian R. Betts,et al.  The Determinants of Undergraduate Grade Point Average: The Relative Importance of Family Background, High School Resources, and Peer Group Effects , 1999 .

[11]  Laurie A. Rudman,et al.  Reactions to counterstereotypic behavior: the role of backlash in cultural stereotype maintenance. , 2004, Journal of personality and social psychology.

[12]  Aldo Rustichini,et al.  Gender and competition at a young age , 2004 .

[13]  Matthew W. Ohland,et al.  Identifying Factors Influencing Engineering Student Graduation: A Longitudinal and Cross‐Institutional Study , 2004 .

[14]  Ulrich Trautwein,et al.  Academic self-concept, interest, grades, and standardized test scores: reciprocal effects models of causal ordering. , 2005, Child development.

[15]  Angela L. Duckworth,et al.  Self-discipline gives girls the edge : Gender in self-discipline, grades, and achievement test scores , 2006 .

[16]  Louis Roussos,et al.  An Investigation into the Dimensionality of TOEFL Using Conditional Covariance-Based Nonparametric Approach , 2007 .

[17]  R. Zwick,et al.  New Perspectives on the Correlation of SAT Scores, High School Grades, and Socioeconomic Factors , 2007 .

[18]  R. Zwick,et al.  New Perspectives on the Correlation of Scholastic Assessment Test Scores , High School Grades , and Socioeconomic Factors , 2007 .

[19]  D. Geary,et al.  PSYCHOLOGICAL SCIENCE IN THE PUBLIC INTEREST The Science of Sex Differences in Science and Mathematics , 2022 .

[20]  Laurie A. Rudman,et al.  Backlash effects for disconfirming gender stereotypes in organizations , 2008 .

[21]  I. Deary,et al.  Sex Differences in Variability in General Intelligence: A New Look at the Old Question , 2008, Perspectives on psychological science : a journal of the Association for Psychological Science.

[22]  F. Schmidt.  Meta-Analysis , 2008 .

[23]  Andrew M. Penner,et al.  Gender Differences in Extreme Mathematical Achievement: An International Perspective on Biological and Social Factors1 , 2008, American Journal of Sociology.

[24]  D. Moher,et al.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement , 2009, BMJ : British Medical Journal.

[25]  D. Moher,et al.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. , 2009, Journal of clinical epidemiology.

[26]  H. Marsh,et al.  A Meta-Analytic Path Analysis of the Internal/External Frame of Reference Model of Academic Achievement and Academic Self-Concept , 2009 .

[27]  Muriel Niederle,et al.  Explaining the Gender Gap in Math Test Scores: The Role of Competition , 2010 .

[28]  Janet Shibley Hyde,et al.  Cross-national patterns of gender differences in mathematics: a meta-analysis. , 2010, Psychological bulletin.

[29]  Wolfgang Viechtbauer,et al.  Conducting Meta-Analyses in R with the metafor Package , 2010 .

[30]  Matthew C. Makel,et al.  Sex differences in the right tail of cognitive abilities: A 30 year examination , 2010 .

[31]  M. Linn,et al.  New trends in gender and mathematics performance: a meta-analysis. , 2010, Psychological bulletin.

[32]  D. Moher,et al.  Nonalcoholic Fatty Liver Disease and Acute Ischemic Stroke , 2010 .

[33]  Shinichi Nakagawa,et al.  Methodological issues and advances in biological meta-analysis , 2012, Evolutionary Ecology.

[34]  J. Lakin.  Sex differences in reasoning abilities: Surprising evidence that male–female ratios in the tails of the quantitative reasoning distribution have increased , 2013 .

[35]  Sarah Kenny,et al.  Not Lack of Ability but More Choice , 2013, Psychological science.

[36]  L. Engqvist,et al.  THE VARIABILITY IS IN THE SEX CHROMOSOMES , 2013, Evolution; international journal of organic evolution.

[37]  David B. Mustard,et al.  Noncognitive Skills and the Gender Disparities in Test Scores and Teacher Assessments: Evidence from Primary School , 2013, The Journal of Human Resources.

[38]  S. Ceci,et al.  Breadth-Based Models of Women’s Underrepresentation in STEM Fields: An Integrative Commentary on Schmidt (2011) and Nye et al. (2012) , 2014, Perspectives on psychological science : a journal of the Association for Psychological Science.

[39]  David Lester Neumann,et al.  Sex Differences in Mathematics and Science Achievement: A Meta-Analysis of National Assessment of Educational Progress Assessments. , 2014 .

[40]  J. Fletcher,et al.  The Flynn effect: a meta-analysis. , 2014, Psychological bulletin.

[41]  Susan D. Voyer,et al.  Gender differences in scholastic achievement: a meta-analysis. , 2014, Psychological bulletin.

[42]  Kerrie Mengersen,et al.  Meta‐analysis of variation: ecological and evolutionary applications and beyond , 2015 .

[43]  Miranda C. Richmond,et al.  Sex differences in ability tilt: Support for investment theory , 2015 .

[44]  Andrei Cimpian,et al.  Expectations of brilliance underlie gender distributions across academic disciplines , 2015, Science.

[45]  Michael T. French,et al.  What You Do in High School Matters: High School GPA, Educational Attainment, and Labor Market Earnings as a Young Adult , 2015 .

[46]  S. Spencer,et al.  Stereotype Threat. , 2016, Annual review of psychology.

[47]  Catherine Riegle-Crumb,et al.  Do They Stay or Do They Go? The Switching Decisions of Individuals Who Enter Gender Atypical College Majors , 2016, Sex roles.

[48]  Christian Monseur,et al.  Gender differences in variability and extreme scores in an international context , 2016, Large-scale Assessments in Education.

[49]  Bart H. H. Golsteyn,et al.  What grades and achievement tests measure , 2016, Proceedings of the National Academy of Sciences.

[50]  Hadas Mandel.  The role of occupational attributes in gender earnings inequality, 1970-2010. , 2016, Social science research.

[51]  Joseph R. Cimpian,et al.  Have Gender Gaps in Math Closed? Achievement, Teacher Perceptions, and Learning Behaviors Across Two ECLS-K Cohorts , 2016 .

[52]  Shinichi Nakagawa,et al.  Nonindependence and sensitivity analyses in ecological and evolutionary meta‐analyses , 2017, Molecular ecology.

[53]  Ming-Te Wang,et al.  Gender Gap in Science, Technology, Engineering, and Mathematics (STEM): Current Knowledge, Implications for Practice, Policy, and Future Directions , 2017, Educational psychology review.

[54]  Cindy E. Hauser,et al.  The gender gap in science: How long until women are equally represented? , 2018, PLoS biology.

[55]  J. Gore,et al.  An Integrated Analysis of School Students’ Aspirations for STEM Careers: Which Student and School Factors Are Most Predictive? , 2018 .

[56]  Shannon M. Pruden,et al.  Sex differences in brain correlates of STEM anxiety , 2019, npj Science of Learning.