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Last Place? The Intersection of Ethnicity, Gender, and Race in Biomedical Authorship

Author

Listed:
  • Gerald Marschke
  • Allison Nunez
  • Bruce A. Weinberg
  • Huifeng Yu

Abstract

Applying big data methods to biomedical science articles, we show that women and underrepresented racial and ethnic groups are less likely to be last authors, an indicator of career independence. We leverage the massive size of our data to highlight the importance of intersectionality, the idea that ethnicity, gender, and race are not necessarily additive, but interact to determine experiences and outcomes. In particular, gender gaps are smaller among blacks and Hispanics than among non-Hispanic whites. Our analysis is timely given serious concerns with under-representation of women and minorities in biomedicine and other STEM fields.

Suggested Citation

  • Gerald Marschke & Allison Nunez & Bruce A. Weinberg & Huifeng Yu, 2018. "Last Place? The Intersection of Ethnicity, Gender, and Race in Biomedical Authorship," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 222-227, May.
    • Handle: RePEc:aea:apandp:v:108:y:2018:p:222-27
    Note: DOI: 10.1257/pandp.20181111
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    Citations

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    Cited by:

    1. João M. Fernandes & António Costa & Paulo Cortez, 2022. "Author placement in Computer Science: a study based on the careers of ACM Fellows," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 351-368, January.
    2. Diego Kozlowski & Dakota S Murray & Alexis Bell & Will Hulsey & Vincent Larivière & Thema Monroe-White & Cassidy R Sugimoto, 2022. "Avoiding bias when inferring race using name-based approaches," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-16, March.
    3. Zhang, Ning & He, Guangye & Shi, Dongbo & Zhao, Zhenyue & Li, Jiang, 2022. "Does a gender-neutral name associate with the research impact of a scientist?," Journal of Informetrics, Elsevier, vol. 16(1).
    4. Vasarhelyi, Orsolya & Brooke, Siân, 2022. "Computing Gender," SocArXiv admcs, Center for Open Science.
    5. Ho-Chun Herbert Chang & Feng Fu, 2021. "Elitism in mathematics and inequality," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-8, December.
    6. Wei Cheng & Bruce A. Weinberg, 2021. "Marginalized and Overlooked? Minoritized Groups and the Adoption of New Scientific Ideas," NBER Working Papers 29179, National Bureau of Economic Research, Inc.
    7. Mike Thelwall, 2020. "Female citation impact superiority 1996–2018 in six out of seven English‐speaking nations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(8), pages 979-990, August.
    8. Julian Kolev & Yuly Fuentes-Medel & Fiona Murray, 2019. "Is Blinded Review Enough? How Gendered Outcomes Arise Even Under Anonymous Evaluation," NBER Working Papers 25759, National Bureau of Economic Research, Inc.

    More about this item

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • J15 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination

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