IDEAS home Printed from https://ideas.repec.org/a/eee/respol/v47y2018i6p1007-1017.html

The gender gap in early career transitions in the life sciences

Author

Listed:
  • Lerchenmueller, Marc J.
  • Sorenson, Olav

Abstract

We examined the extent to which and why early career transitions have led to women being underrepresented among faculty in the life sciences. We followed the careers of 6,336 scientists from the post-doctoral fellowship stage to becoming a principal investigator (PI) – a critical transition in the academic life sciences. Using a unique dataset that connects individuals’ National Institutes of Health funding histories to their publication records, we found that a large portion of the overall gender gap in the life sciences emerges at this transition. Women become PIs at a 20% lower rate than men. Differences in “productivity” (publication records) can explain about 60% of this differential. The remaining portion appears to stem from gender differences in the returns to similar publication records, with women receiving less credit for their citations.

Suggested Citation

  • Lerchenmueller, Marc J. & Sorenson, Olav, 2018. "The gender gap in early career transitions in the life sciences," Research Policy, Elsevier, vol. 47(6), pages 1007-1017.
    • Handle: RePEc:eee:respol:v:47:y:2018:i:6:p:1007-1017
    DOI: 10.1016/j.respol.2018.02.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0048733318300404
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.respol.2018.02.009?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Goldin, Claudia D. & Rouse, Cecilia, 2000. "Orchestrating Impartiality: The Impact of “Blind†Auditions on Female Musicians," Scholarly Articles 30703974, Harvard University Department of Economics.
    2. Jacob, Brian A. & Lefgren, Lars, 2011. "The impact of NIH postdoctoral training grants on scientific productivity," Research Policy, Elsevier, vol. 40(6), pages 864-874, July.
    3. Jevin D West & Jennifer Jacquet & Molly M King & Shelley J Correll & Carl T Bergstrom, 2013. "The Role of Gender in Scholarly Authorship," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-6, July.
    4. Pierre Azoulay & Joshua S. Graff Zivin & Gustavo Manso, 2011. "Incentives and creativity: evidence from the academic life sciences," RAND Journal of Economics, RAND Corporation, vol. 42(3), pages 527-554, September.
    5. Lutter, Mark & Schröder, Martin, 2016. "Who becomes a tenured professor, and why? Panel data evidence from German sociology, 1980–2013," Research Policy, Elsevier, vol. 45(5), pages 999-1013.
    6. Heather Sarsons, 2017. "Recognition for Group Work: Gender Differences in Academia," American Economic Review, American Economic Association, vol. 107(5), pages 141-145, May.
    7. Helen Shen, 2013. "Inequality quantified: Mind the gender gap," Nature, Nature, vol. 495(7439), pages 22-24, March.
    8. Brooks, Chris & Fenton, Evelyn M. & Walker, James T., 2014. "Gender and the evaluation of research," Research Policy, Elsevier, vol. 43(6), pages 990-1001.
    9. Cecilia Rouse & Claudia Goldin, 2000. "Orchestrating Impartiality: The Impact of "Blind" Auditions on Female Musicians," American Economic Review, American Economic Association, vol. 90(4), pages 715-741, September.
    10. Danielle Li, 2017. "Expertise versus Bias in Evaluation: Evidence from the NIH," American Economic Journal: Applied Economics, American Economic Association, vol. 9(2), pages 60-92, April.
    Full references (including those not matched with items on IDEAS)

    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. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.
    2. 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.
    3. Adnan, Wifag & Arin, K. Peren & Charness, Gary & Lacomba, Juan A. & Lagos, Francisco, 2022. "Which social categories matter to people: An experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 125-145.
    4. Vollaard, Ben & van Ours, Jan C., 2022. "Bias in expert product reviews," Journal of Economic Behavior & Organization, Elsevier, vol. 202(C), pages 105-118.
    5. Mallory Avery & Andreas Leibbrandt & Joseph Vecci, 2023. "Does Artificial Intelligence Help or Hurt Gender Diversity? Evidence from Two Field Experiments on Recruitment in Tech," Monash Economics Working Papers 2023-09, Monash University, Department of Economics.
    6. Laura Hospido & Carlos Sanz, 2019. "Gender gaps in the evaluation of research: evidence from submissions to economics conferences (Updated March 2020)," Working Papers 1918, Banco de España, revised Mar 2020.
    7. Li, Meiling & Wang, Yang & Du, Haifeng & Bai, Aruhan, 2024. "Motivating innovation: The impact of prestigious talent funding on junior scientists," Research Policy, Elsevier, vol. 53(9).
    8. Marciano Siniscalchi & Pietro Veronesi, 2020. "Self-image Bias and Lost Talent," NBER Working Papers 28308, National Bureau of Economic Research, Inc.
    9. Menzel, Andreas & Woodruff, Christopher, 2021. "Gender wage gaps and worker mobility: Evidence from the garment sector in Bangladesh," Labour Economics, Elsevier, vol. 71(C).
    10. Laura Hospido & Carlos Sanz, 2021. "Gender Gaps in the Evaluation of Research: Evidence from Submissions to Economics Conferences," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 590-618, June.
    11. Graddy-Reed, Alexandra & Lanahan, Lauren & Eyer, Jonathan, 2019. "Gender discrepancies in publication productivity of high-performing life science graduate students," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    12. Nobel Prize Committee, 2023. "Scientific Background to the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2023," Nobel Prize in Economics documents 2023-2, Nobel Prize Committee.
    13. Sansone, Dario, 2019. "Pink work: Same-sex marriage, employment and discrimination," Journal of Public Economics, Elsevier, vol. 180(C).
    14. Chaojiang Wu & Erjia Yan & Yongjun Zhu & Kai Li, 2021. "Gender imbalance in the productivity of funded projects: A study of the outputs of National Institutes of Health R01 grants," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(11), pages 1386-1399, November.
    15. Ginsburgh, Victor & Radermecker, Anne-Sophie & Tommasi, Denni, 2019. "The effect of experts’ opinion on prices of art works: The case of Peter Brueghel the Younger," Journal of Economic Behavior & Organization, Elsevier, vol. 159(C), pages 36-50.
    16. Andreas Leibbrandt & John A. List, 2018. "Do Equal Employment Opportunity Statements Backfire? Evidence From A Natural Field Experiment On Job-Entry Decisions," NBER Working Papers 25035, National Bureau of Economic Research, Inc.
    17. Tsou, Meng-Wen & Yang, Chih-Hai, 2019. "Does gender structure affect firm productivity? Evidence from China," China Economic Review, Elsevier, vol. 55(C), pages 19-36.
    18. Bernardus Van Doornik & David Schoenherr & Janis Skrastins, 2025. "Escaping Death: individual mobility and female mortality," Working Papers Series 621, Central Bank of Brazil, Research Department.
    19. Heather Savigny, 2017. "Cultural Sexism is Ordinary: Writing and Re-Writing Women in Academia," Gender, Work and Organization, Wiley Blackwell, vol. 24(6), pages 643-655, November.
    20. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • J44 - Labor and Demographic Economics - - Particular Labor Markets - - - Professional Labor Markets and Occupations
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

    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:respol:v:47:y:2018:i:6:p:1007-1017. 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: http://www.elsevier.com/locate/respol .

    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.