Regional intergroup bias
Journal
Advances in Experimental Social Psychology
Type
journal article
Date Issued
2022
Author(s)
Abstract
Recent advances in large-scale data collection have created new opportunities for psychological scientists who study intergroup bias. By leveraging big data, researchers can aggregate individual measures of intergroup bias into regional estimates to predict outcomes of consequence. This small-but-growing area of study has already impacted the field with well-powered research identifying relationships between regional intergroup biases and societally-important, ecologically-valid outcomes. In this chapter, we summarize existing regional intergroup bias research and review relevant theoretical perspectives. Next, we present new and recent evidence that cannot be explained by existing theory, and offer a new perspective on regional intergroup bias that highlights aggregation as changing its’ qualitative nature relative to individual intergroup bias. We conclude with a discussion of some of the important challenges that regional intergroup bias research will need to address in moving forward, focusing on issues of prediction and causality; constructs, measures, and data sources; and levels of analysis.
Language
English
HSG Classification
contribution to scientific community
Refereed
Yes
Volume
66
Start page
281
End page
337
Division(s)