1. Are Female Applicants Disadvantaged in National Institutes of Health Peer Review? Combining Algorithmic Text Mining and Qualitative Methods to Detect Evaluative Differences in R01 Reviewers' Critiques
- Author
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Wairimu Magua, Aaron Potvien, Amarette Filut, Dastagiri Reddy Malikireddy, Molly Carnes, Xiaojin Zhu, Anna Kaatz, You-Geon Lee, Renee Leatherberry, Anupama Bhattacharya, and Madeline Jens
- Subjects
Male ,Biomedical Research ,Writing ,Sexism ,Awards and Prizes ,050109 social psychology ,Context (language use) ,Sample (statistics) ,Latent Dirichlet allocation ,03 medical and health sciences ,symbols.namesake ,Sex Factors ,Wisconsin ,0302 clinical medicine ,Text mining ,Research Support as Topic ,Data Mining ,Humans ,0501 psychology and cognitive sciences ,030212 general & internal medicine ,Qualitative Research ,Women's Careers in Biomedical Sciences: Reducing Barriers and Transforming CultureGuest Editor: Amparo C. VillablancaGuest Co-Editors: Deborah Helitzer ,Phyllis Carr ,Medical education ,business.industry ,05 social sciences ,Linguistics ,General Medicine ,United States ,Disadvantaged ,National Institutes of Health (U.S.) ,symbols ,Female ,Psychology ,business ,Social psychology ,Human Females ,Qualitative research ,Career development - Abstract
Women are less successful than men in renewing R01 grants from the National Institutes of Health. Continuing to probe text mining as a tool to identify gender bias in peer review, we used algorithmic text mining and qualitative analysis to examine a sample of critiques from men's and women's R01 renewal applications previously analyzed by counting and comparing word categories.We analyzed 241 critiques from 79 Summary Statements for 51 R01 renewals awarded to 45 investigators (64% male, 89% white, 80% PhD) at the University of Wisconsin-Madison between 2010 and 2014. We used latent Dirichlet allocation to discover evaluative "topics" (i.e., words that co-occur with high probability). We then qualitatively examined the context in which evaluative words occurred for male and female investigators. We also examined sex differences in assigned scores controlling for investigator productivity.Text analysis results showed that male investigators were described as "leaders" and "pioneers" in their "fields," with "highly innovative" and "highly significant research." By comparison, female investigators were characterized as having "expertise" and working in "excellent" environments. Applications from men received significantly better priority, approach, and significance scores, which could not be accounted for by differences in productivity.Results confirm our previous analyses suggesting that gender stereotypes operate in R01 grant peer review. Reviewers may more easily view male than female investigators as scientific leaders with significant and innovative research, and score their applications more competitively. Such implicit bias may contribute to sex differences in award rates for R01 renewals.
- Published
- 2017