RACE, ETHNICITY, AND NIH RESEARCH AWARDS

By D. Ginther, W. T. Schaffer, Joshua Schnell, B. Masimore, Faye Liu, Laurel L. Haak, R. Kington. Science, 2011

924 citations recorded by the source corpus.

NIH research project grants from 2000 to 2006 show evidence of racial/ethnic disparities in the probability of receiving an award. We investigated the association between a U.S. National Institutes of Health (NIH) R01 applicant’s self-identified race or ethnicity and the probability of receiving an award by using data from the NIH IMPAC II grant database, the Thomson Reuters Web of Science, and other sources. Although proposals with strong priority scores were equally likely to be funded regardless of race, we find that Asians are 4 percentage points and black or African-American applicants are 13 percentage points less likely to receive NIH investigator-initiated research funding compared with whites. After controlling for the applicant’s educational background, country of origin, training, previous research awards, publication record, and employer characteristics, we find that black applicants remain 10 percentage points less likely than whites to be awarded NIH research funding. Our results suggest some leverage points for policy intervention.

Subfields: Gender Studies, Public Health, Environmental and Occupational Health, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/53490a579031e067a883d70242b15c2806987875

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Citations in the corpus

Ethical Machine Learning in Healthcare (2020, background): “and express dierent opinions about ethical dilemmas in computer science (49). Proposals from white researchers in the US are more likely to be funded by the NIH than proposals from Black researchers (50, 51), which in turns aects what topics are given preference. For example, a higher fraction of NI”
Can Evidence Impact Attitudes? Public Reactions to Evidence of Gender Bias in STEM Fields (2015, background): “Although evidence of bias in STEM fields continues to amass (Ginther et al., 2011; Milkman et al., 2012; Moss-Racusin et al., 2012; Reuben et al., 2014; Steinpreis et al., 1999), the role of such demonstrations of bias in general prejudicereduction pathways—as well as more focused STEM diversity…”
Understanding psychology's resistance to intersectionality theory using a framework of epistemic exclusion and invisibility (2020, positive): “For example, studies have found racial and gender bias such that African-American/Black scientists (Ginther et al., 2011), and African-American and Asian-American women scientists (Ginther, Kahn, & Schaffer, 2016), were less likely to receive R01 awards from the National Institutes of Health.”
Systemic racism and U.S. health care. (2014, background): “One recent study (Ginther et al., 2011) found that black NIH applicants were signi ﬁ cantly less likely than comparable whites to receive research funding.”