When researchers submit proposals to the National Institutes of Health to get funding, they don’t indicate their race or ethnicity. But black researchers are a third less likely than other equally-qualified researchers to receive NIH funding.
That’s according to a study by KU economics professor Donna Ginther, who researched the topic for the Institutes in 2008. In an interview with KCUR’s Susan Wilson, Ginther says the medical community needs researchers who better reflect the demographics of the population.
On why the funding discrepancy is a big deal:
“Diversity gives a different perspective on issues related to science. So an example, the first knee replacement. The artificial knee was developed by men; and they put artificial knees for men in women. Well, women’s physical structure is different and it took a woman joining the team to point out that these knees are not going to work for women. So if you get a diversity of perspectives, you get a diversity of approaches to science, and it leads to better science. So, if everybody who’s doing science is white and male, and there are issues related race, ethnicity, and gender, and that’s not reflected in the experiences of scientists, you’re going to get a very narrow perspective on science relative to something that will embrace the diversity of the population.”
On how the study was conducted:
“NIH said, ‘Here’s our data. These are all of the applications’ for RO1 Grants from 2000-2006. And as we put the study together, we added more information about the researchers’ education background, the research background, to try to understand those factors that would account for the success or lack of success, in receiving NIH funding…[T]hen we analyzed it and…you had this gap in the raw data. And if we could explain this by training and education and research productivity, then pinpointing the factors that affected the gap would allow you to have better policy to address [it]. Well, we found the gap, and weren’t really able to explain it. And at that point, we presented the results to NIH leadership and they thought it would be a good idea to get this information out in the open so that they could start affecting policy.”
On the factors she considered to explain the gap in the findings:
“We looked at their educational background, whether or not they received NIH training, their affiliation, the number of publications and citations they had…[T]hey were good predictors for receiving NIH funding for the whole group, but they didn’t really explain why black and Asian applicants were less likely to receive funding. We were able to explain the Asian difference…But, black researchers were 13 percentage points less likely than whites to get funding. We were able to explain about a third of that…still making them 1/3 less likely than whites.”
On whether black researchers use methods or subjects, different from researchers of other races
“It was a very complicated problem. We know that if you have human subjects in your research, the funding hurdle is higher. But for blacks using human subjects in medical schools, [they] were disadvantaged. So if you were…a black MD using human subjects, you were disadvantaged to a black MD not using human subjects…So there is some evidence that the topics that black researchers do may influence their funding probabilities, but if you look at the whole scope of what NIH funds, we tried to sort of narrow down and see if there were race ethnicity differences in topics, but we weren’t really able to discern that, those patterns, in the time that we had, and as a result, it’s a topic for future research.”
On explanations of the gap and recommendations to remedy the discrepancy
“There are two potential and unpalatable explanations. The first is that there’s bias in the review process, and the second is that the proposals are not of high enough quality to be funded. And there are two different approaches to addressing these explanations…The way you treat the symptom of bias in the review process is what NIH is doing, which is experimenting with having anonymous reviews…to see if [bias] is playing a role in the review process."
“And last year, the National Science Foundation experimented with this…and the proposals with names attached turned out to be reviewed different than the proposals without the names…it could be that it’s removing ethnic sounding names…you know, there’s…a halo effect…meaning if you are from a prestigious institution, then you’re treated differently than if you’re from a less prestigious institution. So let’s say for example, you’re from Johns Hopkins, one of the premiere medical schools in the country…because you’re at Hopkins you’re given more of a boost. And actually we see that in our data. If you’re at a top ranked institution, you’re significantly more likely to get funded. Now the question is, is it that Johns Hopkins is more able to pick the best scientists or is it the fact that they’re at Johns Hopkins that improves their outcomes. We don’t know. These are just correlations; they’re not causal."
On the scarcity of grant dollars and its correlation to race
“My perspective is, it’s not race ethnicity. It’s about leveling the playing field, giving everybody the opportunity to be successful, and letting them compete on science…It’s about sort of this tacit knowledge, these rules…that unless someone takes you aside and tells you, you’re not gonna know. There’s a lot of evidence that says people tend to mentor those who look like them…If there are very few black researchers, who is going mentor the new researchers coming in? Just equipping everyone with the same opportunity to be successful, giving them the knowledge and the know-how about how to do the NIH grant correctly will help to level the playing field, and making everybody better at writing their science.”
On her follow-up study
“There was some information missing from our study. We didn’t have any information on their post-doctoral experience; we didn’t have any information on whether or not they’d received awards. So we went back and pulled a sample of 2400 of the resumes, the bio-sketches, from the NIH applications and we coded all of that information on the bio-sketches, including their publications. In the previous study, we were very conservative about matching the publications to the authors. In the new study, we can get all of the measures of citations and associated information on all of those publications in the bio-sketches. And once we control for actual number of publications, we actually did explain more of the gap...In the new study we explain about half of the gap, so this is very preliminary. The goal is to explain the gap with variables that we observe in order to be more precise in how you implement a policy to improve outcomes."