Understanding Discrimination: Outcome-Relevant Information Does Not Mitigate Discrimination.

People experience discrimination across a variety of domains, including at work and in dealings with public institutions, but what makes some individuals discriminate against others? Two dominant scholarly approaches—"statistical" and "taste-based"—offer different explanations. Statistical discrimination models imply that discrimination occurs because of incomplete information (informational bias), whereas taste-based discrimination models emphasize more elusive and deep-rooted cognitive biases. Adding new insights into whether discrimination is "statistical" or "taste-based," this article examines how providing information that reduces informational bias affects discrimination. Using a preregistered survey experimental design, a representative sample of Danish residents (n = 2,024) are exposed to three unique vignettes, each involving a choice of service provider (general practitioner, babysitter, and house cleaner). Relating to gender and nativity stereotypes, we manipulate the gender of the general practitioners and the babysitters, and the country of origin of the house cleaners. Moreover, we manipulate exposure to rating cues about the service providers' task performance, thus mitigating informational bias to some extent. Contrasting the expectations of statistical discrimination models, the performance ratings cues do not mitigate discrimination. Across all three vignettes, the participants exhibit stereotypical preferences, and the performance rating cues do not affect these discriminatory biases. [ABSTRACT FROM AUTHOR]