From Kids to Counties: New Directions in Implicit Social Cognition

Abstract

Due to the limitations of self-report measures, psychologists have developed alternative measurement instruments – often called “implicit” measures - that do not rely on reports from participants. Using the most widely used implicit measure - the Implicit Association Test (IAT) - this dissertation contributes to two emerging areas of research: (1) using implicit measures with child participants and (2) testing whether implicit measures are sensitive to features (e.g., racial diversity) that vary across geographic units (e.g., U.S. counties or states). Chapter 2 presents 5 studies demonstrating that a child-adapted version of the IAT has adequate test-retest reliability young children. Results testing whether the IAT was predictive of children’s behavior were more mixed. Chapter 3 shows that Black-White racial attitudes indexed via the Race Attitude IAT are sensitive to differences in the proportion of Black residents across U.S. counties and states. Higher proportions of Black residents were associated with higher levels of pro-White/anti-Black implicit attitudes for White residents, but lower levels of pro-White/anti-Black implicit attitudes for Black residents. Chapter 4 demonstrates that scores from the Race Attitude IAT are independently predicted by contact with Whites, contact with Blacks, and the proportions of Blacks (but not Whites) residing in one’s county. For both White and Black respondents, having contact with Whites (e.g., as a close friend or romantic partner) or living in counties with higher proportions of Blacks was associated with stronger pro-White/anti-Black implicit attitudes, whereas contact with Blacks was associated with weaker pro-White/anti-Black implicit attitudes. Overall, this work suggests that the IAT is not only practical for use with young children, but also useful for testing the effects of features that vary across geographical units.