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

Background: 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 an...

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Detalhes bibliográficos
Publicado no:J Womens Health (Larchmt)
Main Authors: Magua, Wairimu, Zhu, Xiaojin, Bhattacharya, Anupama, Filut, Amarette, Potvien, Aaron, Leatherberry, Renee, Lee, You-Geon, Jens, Madeline, Malikireddy, Dastagiri, Carnes, Molly, Kaatz, Anna
Formato: Artigo
Idioma:Inglês
Publicado em: Mary Ann Liebert, Inc. 2017
Assuntos:
Women's Careers in Biomedical Sciences: Reducing Barriers and Transforming CultureGuest Editor: Amparo C. VillablancaGuest Co-Editors: Deborah Helitzer; Phyllis Carr
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5446598/
https://ncbi.nlm.nih.gov/pubmed/28281870
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1089/jwh.2016.6021
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