Measuring Automatic Cognition: Advancing Dual-Process Research in Sociology

Andrew Miles, Raphael Charron-Chenier, Cyrus Schleifer

Research output: Contribution to journalArticlepeer-review

46 Scopus citations

Abstract

Dual-process models are increasingly popular in sociology as a framework for theorizing the role of automatic cognition in shaping social behavior. However, empirical studies using dual-process models often rely on ad hoc measures such as forced-choice surveys, observation, and interviews whose relationships to underlying cognitive processes are not fully established. In this article, we advance dual-process research in sociology by (1) proposing criteria for measuring automatic cognition, and (2) assessing the empirical performance of two popular measures of automatic cognition developed by psychologists. We compare the ability of the Brief Implicit Association Test (BIAT), the Affect Misattribution Procedure (AMP), and traditional forced-choice measures to predict process-pure estimates of automatic influences on individuals’ behavior during a survey task. Results from three studies focusing on politics, morality, and racial attitudes suggest the AMP provides the most valid and consistent measure of automatic cognitive processes. We conclude by discussing the implications of our findings for sociological practice.

Original languageEnglish (US)
Pages (from-to)308-333
Number of pages26
JournalAmerican Sociological Review
Volume84
Issue number2
DOIs
StatePublished - Apr 1 2019

Keywords

  • automatic cognition
  • dual-process models
  • measurement
  • practical consciousness

ASJC Scopus subject areas

  • Sociology and Political Science

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