Learning Facts About Migration: Politically Motivated Learning of Polarizing Information About Refugees

Abstract

Information processing during heated debates on asylum and immigration may often be influenced by prejudice rather than a desire to learn facts. In this article, we investigate how people process empirical evidence on the consequences of refugee arrivals through a novel survey experiment that disentangles politically motivated learning from other forms of learning and expressive responding. Specifically, we ask respondents to interpret a 2×2 table about the relationship between asylum seekers and crime rates. Crucially, respondents are randomly allocated to evaluate a conclusion that triggers their identity-protective stakes or not. In addition, we test for motivated responding as an alternative explanation by randomly providing some respondents with a response format that motivates them to report their inference truthfully. We find that information processing changes substantially when new information challenges existing asylum attitudes. Politically motivated learning is strongest among voters with strong negative prior attitudes towards asylum seekers. Our results also indicate that expressive responding can only partially account for this gap in correctly reported inferences. Our research has important implications for research on the consequences of refugee migration, theories of motivated reasoning, and survey methodology.