26 January 2021, BIAS project meeting, Prachi Solanki

Abstract:
A stereotype is a generalization about a class of people but does not necessarily represent every individual with the group (McCauley, Stitt, & Segal, 1980). Category information (i.e., stereotype information) is often used to make probabilistic predictions about people within a particular group. For instance, a probabilistic judgement about Germans would be that, “Germans are more likely than other people to be efficient.” Here we are making a prediction about an individual’s personality (i.e., efficiency) based on their group membership (i.e., German). McCauley and Stitt (1978) suggest that people are accurately Bayesian in their judgements and tend to make probabilistic judgements about people’s personality based on stereotype information. The current project aims to replicate the original McCauley and Stitt (1978) work to test whether stereotype prediction from category information to personality adheres to Bayes’ rule.