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Educational choice has greater effects on sex ratios of college STEM majors than has the greater male variance in general intelligence (g)

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  • Li, Dai
  • Wang, Yizhen
  • Li, Lantian

Abstract

In STEM fields other than biological sciences (math-intensive STEM), there is a greater ratio of males to females (M:F ratio) than that of the general population. The Ability Distribution Hypothesis suggests that this is mainly due to greater male variance in g. Others hypothesize that this is due to sex differences in occupational interests. There has not been an empirical study to evaluate which kind of differences has greater effects on the M:F ratios in math-intensive STEM fields. To fill the gap, we examine the test scores, application for majors and final admissions in a complete dataset of college entrance. We study the M:F ratios of four math-intensive STEM majors: Economics, Engineering, Computer Science and Physical sciences and Math. In summary, we find that greater male variance exists in total test scores; greater male variance partially explains the female underrepresentation in the upper tails of total test scores; men appear to have stronger interests in Engineering and Computer Science than women, while women appear to have stronger interests in Economics and to a lesser extent Physical sciences and Math than men; compared to sex differences in test scores, sex differences in major-choosing appear to have stronger effects on the M:F ratios of math-intensive STEM majors.

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  • 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).
    • Handle: RePEc:eee:intell:v:96:y:2023:i:c:s0160289622001003
    DOI: 10.1016/j.intell.2022.101719
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    References listed on IDEAS

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    1. 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.
    2. Yan Chen & Ming Jiang & Onur Kesten, 2020. "An empirical evaluation of Chinese college admissions reforms through a natural experiment," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(50), pages 31696-31705, December.
    3. Wai, Jonathan & Hodges, Jaret & Makel, Matthew C., 2018. "Sex differences in ability tilt in the right tail of cognitive abilities: A 35-year examination," Intelligence, Elsevier, vol. 67(C), pages 76-83.
    4. Coyle, Thomas R., 2020. "Sex differences in tech tilt: Support for investment theories," Intelligence, Elsevier, vol. 80(C).
    5. Gijsbert Stoet & David C Geary, 2013. "Sex Differences in Mathematics and Reading Achievement Are Inversely Related: Within- and Across-Nation Assessment of 10 Years of PISA Data," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-10, March.
    6. Shulamit Kahn & Donna Ginther, 2017. "Women and STEM," NBER Working Papers 23525, National Bureau of Economic Research, Inc.
    7. Yan Chen & Onur Kesten, 2017. "Chinese College Admissions and School Choice Reforms: A Theoretical Analysis," Journal of Political Economy, University of Chicago Press, vol. 125(1), pages 99-139.
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    1. Chang Xu & Futao Xiang & Ruiqi Duan & Cristina Miralles-Cardona & Xinxin Huo & Junwei Xu, 2023. "An Analysis of Factors Influencing Chinese University Students’ Major Choice from the Perspective of Gender Differences," Sustainability, MDPI, vol. 15(18), pages 1-13, September.

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