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The unjust killings of George Floyd, Breonna Taylor, and Ahmaud Arbery, amplified by the health disparities of the COVID-19 pandemic and the ethnic disparities of the political climate, have shined a spotlight on historical and ongoing institutional racism in America. Many professional scientific organizations, such as the American Association for the Advancement of Science, March For Science, the Society for the Study of Evolution, Society for Neuroscience, and Sigma Xi have published statements opposing it. But statements have little impact unless actions result from them. Determining the most effective actions requires understanding the concept of institutional racism.
Institutional racism means that established structures within a society are infused with racial/racist ideology and practices. This includes the “enterprise” of science, which can be separated from the “method” of science. The scientific method is an objective means to better understand nature, whereas the...
If you would like to sign on to this open letter, please email Editor in Chief Bob Grant (rgrant@the-scientist.com) to add your name and affiliation to a list of signatories that will appear on this page. |
De jure segregation was still in place when African American scientists began to enter historically white research universities in noticeable numbers in the mid-20th century. Ironically, many of these institutions owed their start directly to profits generated by the slave trade. The majority of those in the first wave of black scientists, however, received their undergraduate degrees at historically black universities—institutions that were not founded from black perspectives or agendas, but rather more as social palliatives to help maintain America’s system for separation of the races and white supremacy.
In the early 1970s, acknowledging that there was a great disparity between the percentage of RSMs in the US workforce (13 percent) and their representation in science careers (2 percent), the scientific community began to intervene. Federal science funding agencies spent ~$1.5 billion on RSM-focused STEM programs from 1972 to 1992, in what were then called affirmative action programs, including the National Institutes of Health’s Minority Biomedical Research Support and Minority Access to Research Careers (MARC) programs, from which one of us (E.D.J.) directly benefited.
Although well-intentioned and producing some individual success stories, these programs did not achieve broader success in diversifying the scientific work force. Problems included insufficient oversight and assessment, poor commitment from leading faculty, inconsistent funding, lack of comprehension of behavioral/psychological impacts on student learning, recruitment of many unprepared students, and insufficient attention to the entire K–12-through-university pipeline. The oversight/assessment issue has been largely solved, and progress has been made in other arenas. But more work is needed.
Helping to stymie this progress, in the 1990s the US Supreme Court made it harder to demonstrate that discrimination against racial minorities was taking place, and more difficult to demonstrate that affirmative action policies were not harming white Americans. Ideological justifications for “race-blindness” in admissions and lawsuits claiming supposed “reverse discrimination” followed. While most of these complaints came against professional law and medical school programs, they affected other government programs in STEM. It is notable that MARC now stands for Maximizing Access to Research Careers.
We would be naive to think that racial/racist ideology is not playing a role in maintaining this injustice. This raises the question: What can people of good will do about this?
Colorblind racism and implicit bias continue to influence science careers. Colorblind racism argues that non-racial factors such as economics, naturally occurring phenomena, and the cultural attitudes of RSMs are the main cause of their social subordination. Closely aligned to colorblind racism is implicit bias. This occurs when an individual has a preference for (or aversion to) specific groups of people. This often results from ascribing stereotypes to a group without conscious knowledge of doing so. It has been argued that implicit bias plays a significant role in hindering RSMs’ success in science. In 2015, data indicated that from 1985 to 2013, RSMs were 10 to 22 percent less likely to receive a Research Award 01 (R01) grant from the NIH. This report ignited a firestorm of controversy, especially since there is still little data available to address whether this resulted from the implicit bias of reviewers or other factors. If one asks RSM researchers, most will agree from their experience that implicit bias against them has either harmed their career or made it more difficult.
One 2019 study presented data that seemingly countered that perception. Researchers reviewed a sample of R01 grant applications using a well-established implicit bias testing experimental protocol and found no evidence of racial bias, but did find gender bias. However, the “ethnic name” methods of this experiment can be questioned. For example, the use of supposed “black-sounding” names—“Darnell,” “LaToya”—may not be fully capturing the means by which RSM researchers are discriminated against. Clearly more studies are required before we can accurately assess whether this force is currently working against RSM success in the science community. Another recent study demonstrated ongoing disparities in NIH R01 awards and linked this to the practice of combining criterion scores into impact scores that disadvantaged black applicants.
Some fields are making progress towards improving diversity and inclusion in the scientific community over the last two decades. This progress has been slow, but noticeable. As noted, E.D.J. received important help from such diversity programs, but this assistance was necessary to counter the obstacles he faced in science as an African American. As reported by one of us (J.G.), the outstanding results of the BEACON (Bio/computational Evolution in Action CONsortium) Center for the Study of Evolution in Action, a National Science Foundation Science and Technology Center, are directly tied to the executive committee’s intentional mission to address diversity and inclusion. BEACON’s leadership team included three RSMs and four women in a group of 13 individuals. Progress has also come in the form of organizations such as National Research Mentoring Network, the Annual Biomedical Research Conference for Minority Students, The Black Women in Computational Biology Network, and the coalescence of groups united by social media, such as #BlackInSTEM.
Changing the demography of the scientific community may also allow us to transform the enterprise of science. Specifically, there is a crucial need to address how racial/racist ideology persists within our research programs. Examples of how racist ideology influences the biomedical and behavioral sciences are well studied but probably less known. Other cases of racial bias are beginning to emerge in other disciplines, such as computer science, where one would have hardly thought this was possible. There is now a growing literature revealing how racial bias inherent in data training sets used in artificial intelligence (AI) can introduce racial bias in AI’s outcomes.
The killing of George Floyd has revealed a deep and recalcitrant racism within American society. It permeates all of our institutions. The demography of science still lags behind the representation of RSMs in society. We would be naive to think that racial/racist ideology is not playing a role in maintaining this injustice. This raises the question: What can people of good will do about this?
Some of the answers are obvious, such as taking a stand against societal assaults on the wellbeing of RSM communities. However, others may not be so obvious, such as examining the practices within your own institution that may still harbor implicit bias against RSMs; rethinking the notion that a colorblind approach is the best way to train students and treat colleagues; deeply listening to and learning from your colleagues from RSM communities; and examining your own work and practice for any implicit racial bias. Certainly, scientists alone cannot transform societies mired in racism, but we can and must do our part to help.
Joseph Graves is a professor of biological sciences at North Carolina A&T State University and a fellow of the American Association for the Advancement of Science. Erich D. Jarvis is a professor in the Laboratory of Neurogenetics of Language at the Rockefeller University and is an investigator at the Howard Hughes Medical Institute. They are both members of The Scientist’s editorial advisory board. You can find them on twitter @gravesjl55 and @erichjarvis.
If you would like to sign on to this open letter, please email Editor in Chief Bob Grant (rgrant@the-scientist.com) to add your name and affiliation to a list of signatories that will appear on this page.
* This commentary uses color-scheme language throughout to describe racial/ethnic groups. This is because most readers are not used to thinking about the social definitions of race and the various anthropological titles and arbitrary euphemisms associated with them. Thus, we use the principle of parallelism for racial/ethnic terms, privileging no group over the others, as described in the preface of J.L. Graves, 2005.
Resources
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3. J.L. Graves, “African Americans in evolutionary science: Where we have been and what’s next,” Evol Ed Outreach 12:18, 2019.
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5. P. Dray, At the Hands of Persons Unknown: The Lynching of Black America, Random House, 2002.
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7. L.M. Harris et al., (eds.), Slavery and the University: Histories and Legacies, University of Georgia Press, 2019.
8. W.E.B. Du Bois, “The Field and Function of the Negro College” (1933), in The Education of Black People: Ten Critiques, 1906—1960, ed. H. Aptheker, Monthly Review Press, 1973.
9. C. Sims, “What went wrong: Why programs failed,” Science, 258:1185–87, 1992.
10. J.J. Snyder et al. “Peer-led team learning helps minority students succeed,” PLOS Biol, 14:e1002398, 2016.
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13. D. O’neil Green, “Fighting the battle for racial diversity: A case study of Michigan’s institutional response to Gratz and Grutter,” Educ Policy,18:733–51, 2004.
14. J.L. Graves, “Why the nonexistence of biological races does not mean the nonexistence of racism,” Am Behav Sci, 59:1474–95, 2015.
15. J.L. Eberhardt et al., “Looking deathworthy: Perceived stereotypicality of black defendants predicts capital-sentencing outcomes,” Psychol Sci, 17:383–86, 2006.
16. E. Check Hayden, “Racial bias continues to haunt NIH grants,” Nature, 527:286–87, 2015.
17. P.S. Forscher et al., “Little race or gender bias in an experiment of initial review of NIH R01 grant proposals,” Nat Hum Behav, 3:257–64, 2019.
18. C. Kolehmainen, M. Carnes, “Who resembles a scientific leader-Jack or Jill? How implicit bias could influence research grant funding,” Circulation, 137:769–70, 2018.
19. W. Banzhaf et al., (eds.), Evolution in Action—Past, Present, and Future, Springer International Publishing, 2020, pp. 3–18.
20. L.E. Gómez, N. López (eds.), Mapping “Race”: Critical Approaches to Health Disparities Research, Rutgers University Press, 2013.
21. J. Zou, L. Schiebinger, “AI can be sexist and racist—it’s time to make it fair,” Nature, 559:324–26, 2018.
22. E.A. Erosheva et al., “NIH peer review: Criterion scores completely account for racial disparities in overall impact scores,” Sci Adv, 6:eaaz4868, 2020.
23. E.D. Jarvis, “Surviving as an underrepresented minority scientist in a majority environment,” Mol Biol of the Cell, 26:3692–96, 2017.
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