High cost of bias: Diminishing marginal returns on NIH grant funding to institutions

Abstract

16Scientific output is not a linear function of amounts of federal grant support to individual 17 investigators. As funding per investigator increases beyond a certain point, productivity 18 decreases. This study reports that such diminishing marginal returns also apply for National 19Institutes of Health (NIH) research project grant funding to institutions. Analyses of data (2006-20 2015) for a representative cross-section of institutions, whose amounts of funding ranged from 21 $3 million to $440 million per year, revealed robust inverse correlations between funding (per 22 institution, per award, per investigator) and scientific output (publication productivity and citation 23 impact productivity). Interestingly, prestigious institutions had on average 65% higher grant 24 application success rates and 50% larger award sizes, whereas less-prestigious institutions 25 produced 65% more publications and had a 35% higher citation impact per dollar of funding. 26These findings suggest that implicit biases and social prestige mechanisms (e.g., the Matthew 27 effect) have a powerful impact on where NIH grant dollars go and the net return on taxpayers' 28 investments. They support evidence-based changes in funding policy geared towards a more 29 equitable, more diverse and more productive distribution of federal support for scientific 30 research. Success rate/productivity metrics developed for this study provide an impartial, 31 empirically based mechanism to do so. 32 33 Keywords 34 35 Science policy; peer review; bias; implicit bias; social prestige mechanisms; Matthew effect 36 37Call-Out Quotes 38 39 "Giving the lion's share of grant dollars to a small minority of institutions seems 40 counterproductive and wasteful-whether or not the disparities in funding are driven by bias." 41 42 "A more egalitarian distribution of funding among institutions would yield greater collective gains 43 for the research enterprise and the taxpayers who support it." 48 types of investigators supported, and the regions in which research is conducted. Multiple 49 levels of diversity increase the likelihood of scientific breakthroughs and maximize the return on 50 taxpayers' investments in federally sponsored research (Lorsch, 2015; Peifer, 2017a). 51Unfortunately, there are barriers to maximizing diversity. 53A landmark study in Science reported that black investigators are much less likely to get their 54 National Institutes of Health (NIH) research grant applications funded than white applicants, 55 even after for controlling for other factors (Ginther et al., 2011). There are also large differences 56 in success rates for investigators grouped by age (Levitt & Levitt, 2017). While there does not 57 seem to be a gender gap for new NIH grants, female applicants have lower success rates than 58 their male counterparts for competitive renewals (Kaatz et al., 2016; Magua et al., 2017; 59 Pohlhaus et al., 2011). There are also large differences in success rates for investigators 60 grouped by state (Wahls, 2016). The differences in suc...

The National Institutes of Health needs to better balance funding distributions among US institutions

“…There are clear reasons for the heavily skewed allocations of research dollars among institutions. Proximate causes include large differences in grant application success rates, funding rates (the percentage of applicants who get funded in a given fiscal year), and mean award sizes (5). In each case, these differences favor prestigious institutions over lower-profile institutions.…”

“…They apply when award data are parsed by NIH institute, for "elite" investigators, and by human versus nonhuman model systems (12,24,25). They apply for unbalanced allocations of NIH funding to investigators grouped by institution and by state (5,6). They also apply globally for research support from other funding agencies and in different nations (11,13,26,27).…”

“…diverse set of minds and approaches is vital to harnessing the complete intellectual capital of the nation" (1). These systemic problems stem, in part, from unequal access to NIH grant support among investigators grouped by race (2), gender (3), age (4), institution (5), and state (6).…”

Scientific Utopia: III. Crowdsourcing Science

“…Early advantages in doctoral institution rank, professional connections, and grant funding accumulate benefits over time (Bol, De Vaan, & van de Rijt, in press;Clauset, Arbesman, & Larremore, 2015). Grant funding is overallocated to elite universities, and returns on investment would be greater if the funds were distributed more evenly (Wahls, 2018). At the other end of the academic hierarchy, early career researchers from less well-known institutions, underrepresented demographic groups, and countries that lack economic resources may never have a fair chance to compete (Petersen, Jung, Yang, & Stanley, 2011;Wahls, 2018).…”

“…Grant funding is overallocated to elite universities, and returns on investment would be greater if the funds were distributed more evenly (Wahls, 2018). At the other end of the academic hierarchy, early career researchers from less well-known institutions, underrepresented demographic groups, and countries that lack economic resources may never have a fair chance to compete (Petersen, Jung, Yang, & Stanley, 2011;Wahls, 2018). Academic fields are generally talent rich, such that globally distributed CROWDSOURCING SCIENCE 8 projects can recruit individuals with advanced training and much to offer, yet too few resources to enact the vertical model competitively on their own.…”