Evidence map›Paper›PMID 28281870›Full record

ArticleJournal of women's health (2002)2017

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.

Wairimu Magua, Xiaojin Zhu, Anupama Bhattacharya, Amarette Filut, Aaron Potvien, Renee Leatherberry, You-Geon Lee, Madeline Jens, Dastagiri Malikireddy, Molly Carnes and 1 more

Abstract read
In one paragraph

Article in Journal of women's health (2002), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
27.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 125 citations in OpenAlex.

  1. Exploring Gender Bias in Six Key Domains of Academic Science: An Adversarial Collaboration.Psychological science in the public interest : a journal of the American Psychological Society · 2023
    Pooled it
  2. Effect of a Workshop to Break the Bias Habit for Internal Medicine Faculty: A Multisite Cluster Randomized Controlled Study.Academic medicine : journal of the Association of American Medical Colleges · 2023
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  14. Engagement patterns with female and male scientists on Facebook.Public understanding of science (Bristol, England) · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 2 institutions in 1 country.

Wairimu Magua1 Department of Population Health Sciences, University of Wisconsin-Madison , Madison, Wisconsin.
Xiaojin Zhu2 Department of Computer Science, University of Wisconsin-Madison , Madison, Wisconsin.
Anupama Bhattacharya3 Center for Women's Health Research, University of Wisconsin-Madison , Madison, Wisconsin.
Amarette Filut3 Center for Women's Health Research, University of Wisconsin-Madison , Madison, Wisconsin.
Aaron Potvien4 Department of Statistics, University of Wisconsin-Madison , Madison, Wisconsin.
Renee Leatherberry3 Center for Women's Health Research, University of Wisconsin-Madison , Madison, Wisconsin.
You-Geon Lee6 Wisconsin Center for Education Research, University of Wisconsin-Madison , Madison, Wisconsin.
Madeline Jens3 Center for Women's Health Research, University of Wisconsin-Madison , Madison, Wisconsin.
Dastagiri Malikireddy3 Center for Women's Health Research, University of Wisconsin-Madison , Madison, Wisconsin.
Molly Carnes3 Center for Women's Health Research, University of Wisconsin-Madison , Madison, Wisconsin.
Anna Kaatz3 Center for Women's Health Research, University of Wisconsin-Madison , Madison, Wisconsin.
University of Wisconsin–Madison · USUniversity of Wisconsin Health · US

Funding

Exploring the Science of Scientific Review-Admin SupplementR01GM111002 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI CARNES, MOLLY L., DEVINE, PATRICIA G · 2013 to 2017
$3.9M
NIGMS NIH HHS R01 GM111002
6 · The paper itself

Abstract

backgroundWomen 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.

methodsWe 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.

resultsText 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.

conclusionsResults 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.

Indexed as

Biomedical ResearchData MiningLinguisticsNational Institutes of Health (U.S.)Peer Review, ResearchResearch Support as TopicSexismAwards and PrizesFemaleHumansMaleQualitative ResearchSex FactorsUnited StatesWisconsinWritinggender differencesNIH fundingwomen's career advancement

Identifiers

PMID28281870
PMCPMC5446598
OpenAlexW2602549869

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.