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

Author

Listed:
  • R. E. O’Dea

    (University of New South Wales
    Australian National University)

  • M. Lagisz

    (University of New South Wales)

  • M. D. Jennions

    (Australian National University)

  • S. Nakagawa

    (University of New South Wales)

Abstract

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.

Suggested Citation

  • R. E. O’Dea & M. Lagisz & M. D. Jennions & S. Nakagawa, 2018. "Gender differences in individual variation in academic grades fail to fit expected patterns for STEM," Nature Communications, Nature, vol. 9(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-06292-0
    DOI: 10.1038/s41467-018-06292-0
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    Cited by:

    1. Adele H. Marshall & Mariangela Zenga & Aglaia Kalamatianou, 2020. "Academic Students’ Progress Indicators and Gender Gaps Based on Survival Analysis and Data Mining Frameworks," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 151(3), pages 1097-1128, October.
    2. Merryn McKinnon & Christine O’Connell, 2020. "Perceptions of stereotypes applied to women who publicly communicate their STEM work," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-8, December.
    3. Speer, Jamin D., 2023. "Bye bye Ms. American Sci: Women and the leaky STEM pipeline," Economics of Education Review, Elsevier, vol. 93(C).
    4. Antonio De Nicola & Gregorio D’Agostino, 2021. "Assessment of gender divide in scientific communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 3807-3840, May.
    5. Dominique Cappelletti & Maria Vittoria Levati & Matteo Ploner, 2022. "Math ability, gender stereotypes about math ability, and educational choices. Combining experimental and survey data," Working Papers 07/2022, University of Verona, Department of Economics.
    6. Mike Thelwall & Tamara Nevill, 2019. "No evidence of citation bias as a determinant of STEM gender disparities in US biochemistry, genetics and molecular biology research," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1793-1801, December.
    7. Marshall, Lydia & Moore, Rhiannon, 2022. "Does school effectiveness differentially benefit boys and girls? Evidence from Ethiopia, India and Vietnam," International Journal of Educational Development, Elsevier, vol. 88(C).
    8. Christine O’Connell & Merryn McKinnon, 2021. "Perceptions of Barriers to Career Progression for Academic Women in STEM," Societies, MDPI, vol. 11(2), pages 1-20, March.
    9. Paul A. Longley & Justin Dijk & Tian Lan, 2021. "The geography of intergenerational social mobility in Britain," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
    10. Roberto Sánchez-Cabrero & Amaya Arigita-García & David Gil-Pareja & Ana Sánchez-Rico & Fernando Martínez-López & Leonor Sierra-Macarrón, 2022. "Measuring the Relation between Academic Performance and Emotional Intelligence at the University Level after the COVID-19 Pandemic Using TMMS-24," Sustainability, MDPI, vol. 14(6), pages 1-13, March.
    11. Natsuki Arai & Shian Chang & Biing-Shen Kuo, 2021. "Introductory Economics: Gender, Majors, and Future Performance," Papers 2106.10091, arXiv.org.
    12. Hartshorn, Jessica A. & Brockerhoff, Eckehard G. & Klapwijk, Maartje J. & Marzano, Mariella & Ganley, Rebecca J. & Darr, Molly N., 2023. "Attracting and retaining women in forest entomology and forest pathology," Forest Policy and Economics, Elsevier, vol. 154(C).
    13. Goulas, Sofoklis & Griselda, Silvia & Megalokonomou, Rigissa, 2020. "Comparative Advantage and Gender Gap in STEM," IZA Discussion Papers 13313, Institute of Labor Economics (IZA).
    14. Sandsør, Astrid Marie Jorde, 2020. "Jack-of-all-subjects? The association between individual grade variance and educational attainment," Economics of Education Review, Elsevier, vol. 75(C).
    15. Li, Dai & Wang, Yizhen & Li, Lantian, 2023. "Educational choice has greater effects on sex ratios of college STEM majors than has the greater male variance in general intelligence (g)," Intelligence, Elsevier, vol. 96(C).
    16. Alberto Álvarez Terán & Camilo Palazuelos & Trinidad Dierssen-Sotos & Jessica Alonso-Molero & Javier Llorca & Inés Gómez-Acebo, 2022. "Evolution of Medical Students’ Perception of the Patient’s Right to Privacy," IJERPH, MDPI, vol. 19(17), pages 1-15, September.
    17. Cortes, Patricia & Feng, Ying & Guida-Johnson, Nicolás & Pan, Jessica, 2023. "Automation and Gender: Implications for Occupational Segregation and the Gender Skill Gap," IZA Discussion Papers 16695, Institute of Labor Economics (IZA).

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