Situational Models of Implicit Bias

The Bias of Crowds model (Payne et al., 2017) suggests that (implicit) bias is determined by the social, cultural and physical environment. The model is supported by a wide range of research findings, linking implicit bias on a geographical level such as counties or states with differences in the social, cultural, or physical environment. If different environments are associated with different levels of implicit bias, it follows that changes in the environment should causally affect implicit bias. In my first project in this research line we used multi-level analyses and Directed Acyclic Graphs (a causal inference tool) to investigate whether the 2020 BLM protests led to changes in implicit bias over time. We found that there was a massive drop in implicit bias right after the onset of the protests - with implicit bias steadily increasing again once attention to BLM faded ((Primbs, Holland, Lansu, Faure, & Bijlstra, under review)). In a second project, built on an incidental finding in the BLM paper, we show that implicit bias towards racial and ethnic minorities is increased during Christmas ((Primbs, Holland, Peetz, Dudda, Faure, & Bijlstra, under review)). I’m very happy to share that I recently won a grant (together with Paul Connor) to conduct an experimental test of this Christmas effect. Finally, in an on-going project with Keith Payne, Heidi Vuletich, & Nicolas Sommet we are investigating the effects of the removal of confederate monuments on implicit bias.