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Publications as predictors of racial and ethnic differences in NIH research awards

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  • Donna K Ginther
  • Jodi Basner
  • Unni Jensen
  • Joshua Schnell
  • Raynard Kington
  • Walter T Schaffer

Abstract

This research expands efforts to understand differences in NIH funding associated with the self-identified race and ethnicity of applicants. We collected data from 2,397 NIH Biographical Sketches submitted between FY 2003 and 2006 as part of new NIH R01 Type 1 applications to obtain detailed information on the applicants’ training and scholarly activities, including publications. Using these data, we examined the association between an NIH R01 applicant’s race or ethnicity and the probability of receiving an R01 award. The applicant’s publication history as reported in the NIH biographical sketch and the associated bibliometrics narrowed the black/white funding gap for new and experienced investigators in explanatory models. We found that black applicants reported fewer papers on their Biosketches, had fewer citations, and those that were reported appeared in journals with lower impact factors. Incorporating these measures in our models explained a substantial portion of the black/white funding gap. Although these predictors influence the funding gap, they do not fully address race/ethnicity differences in receiving a priority score.

Suggested Citation

  • Donna K Ginther & Jodi Basner & Unni Jensen & Joshua Schnell & Raynard Kington & Walter T Schaffer, 2018. "Publications as predictors of racial and ethnic differences in NIH research awards," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-24, November.
  • Handle: RePEc:plo:pone00:0205929
    DOI: 10.1371/journal.pone.0205929
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    References listed on IDEAS

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    1. Jonah B. Gelbach, 2016. "When Do Covariates Matter? And Which Ones, and How Much?," Journal of Labor Economics, University of Chicago Press, vol. 34(2), pages 509-543.
    2. Adam Eyre-Walker & Nina Stoletzki, 2013. "The Assessment of Science: The Relative Merits of Post-Publication Review, the Impact Factor, and the Number of Citations," PLOS Biology, Public Library of Science, vol. 11(10), pages 1-8, October.
    3. Francine D. Blau & Janet M. Currie & Rachel T. A. Croson & Donna K. Ginther, 2010. "Can Mentoring Help Female Assistant Professors? Interim Results from a Randomized Trial," American Economic Review, American Economic Association, vol. 100(2), pages 348-352, May.
    4. Yang, Jiansheng & Vannier, Michael W. & Wang, Fang & Deng, Yan & Ou, Fengrong & Bennett, James & Liu, Yang & Wang, Ge, 2013. "A bibliometric analysis of academic publication and NIH funding," Journal of Informetrics, Elsevier, vol. 7(2), pages 318-324.
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    Cited by:

    1. Sarah Shandera & Jes L Matsick & David R Hunter & Louis Leblond, 2021. "RASE: Modeling cumulative disadvantage due to marginalized group status in academia," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-20, December.
    2. Norbert L. W. Wilson & Lurleen M. Walters & Tara Wade & Kenesha Reynolds, 2024. "The distribution of competitive research grants from the National Institute for Food and Agriculture: A comparison of 1862 land grant universities, 1890 land grant universities, and other institutions," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 46(1), pages 76-94, March.
    3. Rubin, Amir & Rubin, Eran & Segal, Dan, 2023. "Editor home bias?," Research Policy, Elsevier, vol. 52(6).
    4. Laurie E Risner & Xenia K Morin & Evelyn S Erenrich & Philip S Clifford & Jeffrey Franke & Imogen Hurley & Nancy B Schwartz, 2020. "Leveraging a collaborative consortium model of mentee/mentor training to foster career progression of underrepresented postdoctoral researchers and promote institutional diversity and inclusion," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-23, September.

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