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Do Female Role Models Reduce the Gender Gap in Science? Evidence from French High Schools

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  • Breda, Thomas

    (Paris School of Economics)

  • Grenet, Julien

    (Paris School of Economics)

  • Monnet, Marion

    (University of Burgundy)

  • Van Effenterre, Clémentine

    (University of Toronto)

Abstract

This paper, based on a large-scale field experiment, tests whether a one-hour exposure to external female role models with a background in science affects students' perceptions and choice of field of study. Using a random assignment of classroom interventions carried out by 56 female scientists among 20,000 high school students in the Paris Region, we provide the first evidence of the positive impact of external female role models on student enrollment in STEM fields. We show that the interventions increased the share of Grade 12 girls enrolling in selective (male-dominated) STEM programs in higher education, from 11 to 14.5 percent. These effects are driven by high-achieving girls in mathematics. We find limited effects on boys' educational choices in Grade 12, and no effect for students in Grade 10. Evidence from survey data shows that the program raised students' interest in science-related careers and slightly improved their math self-concept. It sharply reduced the prevalence of stereotypes associated with jobs in science and gender differences in abilities, but it made the underrepresentation of women in science more salient. Using machine learning methods, we leverage the diversity of role model profiles to document substantial heterogeneity in the effectiveness of role models and shed light on the channels through which they can influence female students' choice of study. Results suggest that emphasis on the gender theme is less important to the effectiveness of this type of intervention than the ability of role models to convey a positive and more inclusive image of STEM careers.

Suggested Citation

  • Breda, Thomas & Grenet, Julien & Monnet, Marion & Van Effenterre, Clémentine, 2020. "Do Female Role Models Reduce the Gender Gap in Science? Evidence from French High Schools," IZA Discussion Papers 13163, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp13163
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    Cited by:

    1. Boneva, Teodora & Buser, Thomas & Falk, Armin & Kosse, Fabian, 2021. "The Origins of Gender Differences in Competitiveness and Earnings Expectations: Causal Evidence from a Mentoring Intervention," IZA Discussion Papers 14800, Institute of Labor Economics (IZA).
    2. Gordon B. Dahl & Dan-Olof Rooth & Anders Stenberg, 2024. "Intergenerational and Sibling Spillovers in High School Majors," American Economic Journal: Economic Policy, American Economic Association, vol. 16(3), pages 133-173, August.
    3. Ho Fai Chan & Benno Torgler, 2020. "Gender differences in performance of top cited scientists by field and country," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2421-2447, December.
    4. Laura Pagani & Giovanni Pica, 2021. "A Peer Like Me? Early Exposure to High Achievers in Math and Later Educational Outcomes," Development Working Papers 476, Centro Studi Luca d'Agliano, University of Milano.
    5. Grosch, Kerstin & Häckl, Simone & Kocher, Martin G., 2022. "Closing the gender STEM gap," Department of Economics Working Paper Series 329, WU Vienna University of Economics and Business.
    6. Patricia Palffy & Patrick Lehnert & Uschi Backes‐Gellner, 2023. "Social norms and gendered occupational choices of men and women: Time to turn the tide?," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 62(4), pages 380-410, October.
    7. Bertrand,Marianne & Crepon,Bruno Jacques Jean Philippe & Marguerie,Alicia Charlene & Premand,Patrick, 2021. "Do Workfare Programs Live Up to Their Promises ? Experimental Evidence from Côte d’Ivoire," Policy Research Working Paper Series 9611, The World Bank.
    8. Judith M. Delaney & Paul J. Devereux, 2021. "Gender and Educational Achievement: Stylized Facts and Causal Evidence," Working Papers 202103, School of Economics, University College Dublin.
    9. Grosch, Kerstin & Haeckl, Simone & Kocher , Martin G., 2022. "Closing the gender STEM gap. A large-scale randomized-controlled trial in elementary schools," UiS Working Papers in Economics and Finance 2022/4, University of Stavanger.
    10. Thomas Breda & Elyès Jouini & Clotilde Napp, 2023. "Gender differences in the intention to study math increase with math performance," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    11. Agurto, M. & Bazan, M. & Hari, S. & Sarangi, S., 2021. "Women in Engineering: The Role of Role Models," GLO Discussion Paper Series 975, Global Labor Organization (GLO).
    12. Judith M. Delaney & Paul J. Devereux, 2022. "Gender Differences in STEM Persistence after Graduation," Economica, London School of Economics and Political Science, vol. 89(356), pages 862-883, October.
    13. Fruttero,Anna & Muller,Noel & Calvo-Gonzalez,Oscar, 2021. "The Power and Roots of Aspirations : A Survey of the Empirical Evidence," Policy Research Working Paper Series 9729, The World Bank.
    14. Thomas Breda & Elyès Jouini & Clotilde Napp, 2023. "Gender differences in the intention to study math increase with math performance," PSE-Ecole d'économie de Paris (Postprint) halshs-04155403, HAL.
    15. Delfino, Alexia, 2021. "Breaking Gender Barriers: Experimental Evidence on Men in Pink-Collar Jobs," IZA Discussion Papers 14083, Institute of Labor Economics (IZA).
    16. Thomas Breda & Elyès Jouini & Clotilde Napp, 2023. "Gender differences in the intention to study math increase with math performance," Post-Print halshs-04155403, HAL.
    17. Sulema Torres-Ramos & Nicte Selene Fajardo-Robledo & Lourdes Adriana Pérez-Carrillo & Claudia Castillo-Cruz & Patricia del R. Retamoza-Vega & Verónica M. Rodríguez-Betancourtt & Cristina Neri-Cortés, 2021. "Mentors as Female Role Models in STEM Disciplines and Their Benefits," Sustainability, MDPI, vol. 13(23), pages 1-19, November.

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    More about this item

    Keywords

    role models; gender gap; STEM; stereotypes; choice of studies;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • I24 - Health, Education, and Welfare - - Education - - - Education and Inequality
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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