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Delving Further into the Funding Gap Between White and Black Researchers

As is now well known, black scientists are less successful than their white counterparts in obtaining support from NIH R01 awards as designated Principal Investigators (PIs) (see here and here). Though recent NIH efforts are showing promise to enhance diversity in the biomedical workforce (see this post), much work is still needed to address the funding gap.

In a paper recently published in Science Advances, we delved into the underlying factors associated with this funding gap. We identified three decision points where disparate outcomes arose between white and black researchers: 1) the decision to bring applications to discussion during peer review study section meetings; 2) impact score assignments for those applications brought to discussion; and (3) a previously unstudied factor, topic choice – that is what topic the investigators chose to study.

We analyzed 157,549 R01 applications, both new and renewals, from fiscal years 2011-2015. We confirmed previous findings that black researchers submit fewer applications as PIs than white researchers. Applications with black scientists as PIs were brought to discussion in peer review only 77% as frequently as applications from white researcher PI’s (Figure 1).  

Figure 1 illustrates the funding gap between black and white scientists at each stage of the R01 application and review process. Horizontal red (top) and blue (bottom) funnels represent black and white researchers, respectively.  Arrows on the left indicate the number of R01 applications from black and white researchers in FYs 2011-2015. Charts depict the number of applications that were submitted, discussed, and funded per applicant. Comparative rates of discussion, funding of discussed applications, and overall funding rates are presented on the top right.
Figure 1

When applications from black researchers were discussed in study section, they received worse impact scores— 38.4 + 13.4 vs 35.2 + 12.6.  Combining lower submission rates, lower discussion rates, and worse impact, black scientists receive R01 funding only half as often as their white peers (Figure 1).

We found a number of differences in the characteristics of applications according to the race of the designated PI.  Black scientists were more likely to propose research involving human subjects and less likely to propose work involving animal models.

We next used an informatics method called “word2vec” to bin the 157,549 applications into 150 topic clusters, which roughly aligns with the number of standing study sections at NIH.  We can describe these clusters by word chains like “retina photoreceptor retinal cone MeSH_Photoreceptor_Cells_Vertebrate rod photoreceptor cells retinal degeneration” or “practice provider clinician care education evidence-based healthcare recommendation medical psychosocial.”  Figure 2 shows word clouds associated with the topic clusters with the highest number of applications from black PIs (panel A) and with clusters in which there were no applications from black PIs (panel B).  Note that the words in panels A and B are clearly qualitatively different.

A closer look at Figure 2 shows that black applicants were more likely to be associated with topics like health disparities, disease prevention and intervention, socioeconomic factors, healthcare, lifestyle, psychosocial, adolescent, and risk (panels A and C). Generally speaking, applications with these terms were less likely to be funded than topics linked like neuron, corneal, cell, and iron (panel B).

Figure 2 shows topic clusters most and least commonly proposed by black scientists. Panel A shows topic clusters with the highest number of applications from AA/B scientists; note featured words like HIV, intervention, patient, treatment, and behavior.  Panel B shows topic clusters with no applications from black scientists; note featured words like neuron, corneal, prion, cell, and iron. Word clouds are placed in a clockwise orientation relative to the order shown in Figure 3A from the original paper. Cluster numbers are presented alongside overall award rate (cluster number/award rate).  Panel C shows the distribution of applications and awards among black scientists.
Figure 2

Figure 3 summarizes the word2vec topic cluster data for all applications.  Panel A shows the topics in descending order of proportion of applications designating black PIs.  Panel B shows the number of applications for each topic (presented in the same order as in panel A).  A third of the applications from black scientists mapped to only eight of the 150 topic clusters, which tended to experience lower success rates (panel C). These lower-success topic clusters tended to focus on community and population-level research. Of note, applications from white researchers in these lower-success topic clusters were also less likely to be funded, although not to the same degree as those from black researchers.

Figure 3  visualizes the Distribution of applications from black scientists across topics. Three charts are displayed. The X axis represents   the cluster number, while the Y axis is either the percentage of applications from  black scientists Red bars), number of applications (orange bars) or awardee rate (blue bars).
Figure 3

We performed a series of multivariable analyses and found that after controlling for variables like applicants’ prior success, topic selection accounted for 21 percent of the funding gap observed between black and white researchers.

We briefly discussed potential implications of our findings – including the need to encourage a more diverse applicant pool, the potential value of mentoring systems to help investigators navigate the NIH system, and the possibility for NIH institutes and centers to consider discretionary funding for topics that may be under-appreciated by review but align with strategic priorities.


3 thoughts on “Delving Further into the Funding Gap Between White and Black Researchers

  1. The article was indeed thought-provoking and enlightenig with statistically significant powered-analyses of the NIH USA grants-applicants’ pools, primarily Blacks- vs Whites- Americans, endeavoring to address the public health-oriented research with successful target-driven federal grants/budgetary approvals, including extensions and/or renewals!
    Future research snapshots would prove beneficial for applicants with enhanced understanding of funding scores, etc.
    Indeed, a crisp update.

  2. Hello Dr. Lauer,
    Thank you for conducting this important study . One factor that is not mentioned, but implied, is bias of reviewers in the grant review process. Increase in applications from Black researchers will not address this issue. Rather, the ability of those participating in the review to decide which applications “merit” consideration should be closely monitored if not abandoned completely. Likewise, the NIH system of selection of grant reviewers from the pool of funded researchers only serves to perpetuate the exclusion of those who have historically been under-funded. We must find a system that includes all scientists who are active in research and abandon any system that allows individual biais to dominate (i.e., the grant triage process).

  3. This is a wonderful first step for Black Scientist. As I was reading the article I noticed in the last paragraph “a potential to encourage a more diverse group.” I would hope since this started out as a study to fill the gap between white and black scientist, this will cater more to black scientist than in other diverse group because when “diverse groups” are added in Black Scientist seems to get lost in the whole ideal and loss out of receiving RO1’s. Maybe at some other point NIH can encourage other diverse groups.

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