Profs use 'flawed' Harvard study to push 'implicit,' 'explicit' racism theory

The researchers then used county-level data for COVID-19 cases and deaths, the number of black residents, and racial attitudes. They measured both implicit and explicit racism using Harvard University’s Project Implicit, which collects “bias and prejudice data” from people around the world.

A 2017 Heritage Foundation report from statistician Althea Nagai explained that the project’s “Implicit Association Test,” which the professors utilized in their study, is "flawed" in spite of extensive mainstream media coverage. In fact, “there are many scientific critics of this test, and it is far from settled science.”

Nagai points out that an individual’s test score may vary from trial to trial, pointing to its lack of reliability. Room for error is introduced when test data is measured in milliseconds. There are a “wide variety of other explanations” for differences when measured in milliseconds.

Additionally, “the IAT could tap into a fear of being called a racist instead of being an unconscious racist” for some test takers.

Nevertheless, Cunningham and Wigfall concluded that “aggregate measures of explicit racial attitudes and implicit racial bias provided additional explanatory evidence.” Specifically, “the relationship between the percent of Black county residents and COVID-19 cases was stronger when explicit racial attitudes and implicit racial attitudes, respectively, were high relative to when they were low.”