IDEAS home Printed from https://ideas.repec.org/a/eee/intell/v80y2020ics0160289620300155.html
   My bibliography  Save this article

Sex differences in tech tilt: Support for investment theories

Author

Listed:
  • Coyle, Thomas R.

Abstract

This study examined sex differences in tech tilt, based on within-subject differences in technical abilities (e.g., mechanical and electrical) and academic abilities (math or verbal) on the Armed Services Vocational Aptitude Battery (ASVAB). The within-subject differences produced two types of tilt: tech tilt (tech > academic), indicating stronger technical abilities, and academic tilt (academic > tech), indicating stronger academic abilities. Tech tilt was correlated with math and verbal abilities on college aptitude tests (SAT, ACT, PSAT) and with jobs and college majors in STEM (science, technology, engineering, and math) and humanities. Males showed a tech tilt bias, and females showed an academic tilt bias. The tilt biases persisted after controlling for general intelligence (g). Tech tilt correlated negatively with academic abilities on the college aptitude tests (SAT, ACT, PSAT), with larger effects for females. In addition, relations of tech tilt with STEM jobs and majors were generally larger (and more often significant) for males, but only for tech tilt based on technical and verbal abilities. The negative relations of tech tilt with academic abilities on the college aptitude tests are consistent with investment theories, which predict that investment in one ability (technical) comes at the expense of competing abilities (academic). The sex differences in tech tilt and STEM support trait complexes involving abilities, interests, and vocational preferences (e.g., people versus things). Future research should examine whether spatial abilities and vocational interests mediate relations of tech tilt with sex and STEM criteria.

Suggested Citation

  • Coyle, Thomas R., 2020. "Sex differences in tech tilt: Support for investment theories," Intelligence, Elsevier, vol. 80(C).
    • Handle: RePEc:eee:intell:v:80:y:2020:i:c:s0160289620300155
    DOI: 10.1016/j.intell.2020.101437
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160289620300155
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.intell.2020.101437?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Coyle, Thomas R., 2019. "Tech tilt predicts jobs, college majors, and specific abilities: Support for investment theories," Intelligence, Elsevier, vol. 75(C), pages 33-40.
    2. Coyle, Thomas R., 2018. "Non-g residuals of group factors predict ability tilt, college majors, and jobs: A non-g nexus," Intelligence, Elsevier, vol. 67(C), pages 19-25.
    3. Peter Arcidiacono & Esteban Aucejo & Ken Spenner, 2012. "What happens after enrollment? An analysis of the time path of racial differences in GPA and major choice," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 1(1), pages 1-24, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Coyle, Thomas R., 2022. "Sex differences in spatial and mechanical tilt: Support for investment theories," Intelligence, Elsevier, vol. 95(C).
    3. Coyle, Thomas R., 2023. "Sex differences in tech tilt and academic tilt in adolescence: Processing speed mediates age-tilt relations," Intelligence, Elsevier, vol. 100(C).
    4. Becker, David & Coyle, Thomas R. & Minnigh, Tyler L. & Rindermann, Heiner, 2022. "International differences in math and science tilts: The stability, geography, and predictive power of tilt for economic criteria," Intelligence, Elsevier, vol. 92(C).
    5. Coyle, Thomas R. & Greiff, Samuel, 2021. "The future of intelligence: The role of specific abilities," Intelligence, Elsevier, vol. 88(C).
    6. Coyle, Thomas R., 2021. "White-Black differences in tech tilt: Support for Spearman's law and investment theories," Intelligence, Elsevier, vol. 84(C).
    7. Coyle, Thomas R., 2022. "Processing speed mediates the development of tech tilt and academic tilt in adolescence," Intelligence, Elsevier, vol. 94(C).
    8. Coyle, Thomas R. & Greiff, Samuel, 2023. "Carbon is to life as g is to _____: A review of the contributions to the special issue on specific abilities in intelligence," Intelligence, Elsevier, vol. 101(C).
    9. Dunkel, Curtis S. & Madison, Guy, 2022. "The possible role of field independence/dependence on developmental sex differences in general intelligence," Intelligence, Elsevier, vol. 91(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Coyle, Thomas R., 2022. "Sex differences in spatial and mechanical tilt: Support for investment theories," Intelligence, Elsevier, vol. 95(C).
    2. Coyle, Thomas R. & Greiff, Samuel, 2021. "The future of intelligence: The role of specific abilities," Intelligence, Elsevier, vol. 88(C).
    3. Becker, David & Coyle, Thomas R. & Minnigh, Tyler L. & Rindermann, Heiner, 2022. "International differences in math and science tilts: The stability, geography, and predictive power of tilt for economic criteria," Intelligence, Elsevier, vol. 92(C).
    4. Becker, David & Coyle, Thomas R. & Rindermann, Heiner, 2024. "Unraveling the nexus: Culture, cognitive competence, and economic performance across 86 nations (2000–2018)," Intelligence, Elsevier, vol. 106(C).
    5. Coyle, Thomas R., 2023. "Sex differences in tech tilt and academic tilt in adolescence: Processing speed mediates age-tilt relations," Intelligence, Elsevier, vol. 100(C).
    6. Ralph Stinebrickner & Todd R. Stinebrickner, 2014. "A Major in Science? Initial Beliefs and Final Outcomes for College Major and Dropout," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(1), pages 426-472.
    7. Aaron Albert & Nathan Wozny, 2024. "The Impact of Academic Probation: Do Intensive Interventions Help?," Journal of Human Resources, University of Wisconsin Press, vol. 59(3), pages 852-878.
    8. Debopam Bhattacharya & Shin Kanaya & Margaret Stevens, 2017. "Are University Admissions Academically Fair?," The Review of Economics and Statistics, MIT Press, vol. 99(3), pages 449-464, July.
    9. Andrews, Rodney J. & Imberman, Scott A. & Lovenheim, Michael F., 2020. "Recruiting and supporting low-income, high-achieving students at flagship universities," Economics of Education Review, Elsevier, vol. 74(C).
    10. Frisancho, Veronica & Krishna, Kala & Lychagin, Sergey & Yavas, Cemile, 2016. "Better luck next time: Learning through retaking," Journal of Economic Behavior & Organization, Elsevier, vol. 125(C), pages 120-135.
    11. Coyle, Thomas R., 2022. "Processing speed mediates the development of tech tilt and academic tilt in adolescence," Intelligence, Elsevier, vol. 94(C).
    12. Nathan D. Martin & Kenneth I. Spenner & Sarah A. Mustillo, 2017. "A Test of Leading Explanations for the College Racial-Ethnic Achievement Gap: Evidence from a Longitudinal Case Study," Research in Higher Education, Springer;Association for Institutional Research, vol. 58(6), pages 617-645, September.
    13. Richard Murphy & Felix Weinhardt, 2020. "Top of the Class: The Importance of Ordinal Rank," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(6), pages 2777-2826.
    14. Thomas Ahn & Peter Arcidiacono & Amy Hopson & James R. Thomas, 2019. "Equilibrium Grade Inflation with Implications for Female Interest in STEM Majors," NBER Working Papers 26556, National Bureau of Economic Research, Inc.
    15. Rajeev Darolia & Cory Koedel & Joyce B. Main & Felix Ndashimye & Junpeng Yan, 2020. "High School Course Access and Postsecondary STEM Enrollment and Attainment," Working Papers 2004, Department of Economics, University of Missouri.
    16. Alon, Sigal & Malamud, Ofer, 2014. "The impact of Israel's class-based affirmative action policy on admission and academic outcomes," Economics of Education Review, Elsevier, vol. 40(C), pages 123-139.
    17. Hinrichs, Peter, 2014. "Affirmative action bans and college graduation rates," Economics of Education Review, Elsevier, vol. 42(C), pages 43-52.
    18. Patnaik, Arpita & Venator, Joanna & Wiswall, Matthew & Zafar, Basit, 2022. "The role of heterogeneous risk preferences, discount rates, and earnings expectations in college major choice," Journal of Econometrics, Elsevier, vol. 231(1), pages 98-122.
    19. Arpita Patnaik & Matthew J. Wiswall & Basit Zafar, 2020. "College Majors," NBER Working Papers 27645, National Bureau of Economic Research, Inc.
    20. Andrés Barrios F., 2018. "Admisión universitaria: el caso del puntaje ranking y la retención de los beneficiados," Estudios Públicos, Centro de Estudios Públicos, vol. 0(150), pages 127-159.

    More about this item

    Keywords

    Tech tilt; Ability tilt; STEM; ASVAB; SAT; ACT; PSAT;
    All these keywords.

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:intell:v:80:y:2020:i:c:s0160289620300155. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.