IAT response latency reveals implicit prejudice even absent self-reported bias

Evidence

We used IAT software developed by Farnham (1998) to measure implicit racial prejudice (see the Method section). In the critical trials of this test, participants sorted terms representing four concepts (White names, Black names, unpleasant words, and pleasant words) into just two response categories (e.g., White–unpleasant, Black–pleasant; see the Method section). Reaction times to categorize the names and adjectives were recorded. Implicitly prejudiced White participants, who might not self-report being racially prejudiced, usually find the IAT to be more difficult, and thus have increased response latencies, when the two sorting categories are more incongruent with respect to their implicit prejudices (i.e., White–unpleasant, Black–pleasant) than when the two sorting categories are more congruent (i.e., White–pleasant, Black–unpleasant). — Wade C. Rowatt and Lewis M. Franklin, Christian Orthodoxy, Religious…, 26

Categorization

• DEFINE: Explains the mechanism of the race-IAT measure — sorting-into-congruent-vs-incongruent-categories and the latency proxy for implicit bias.
• XREF: Directly serves the reading purpose on whether professed conviction diverges from implicit measured bias; connects to Rowatt & Franklin’s self-report vs IAT comparisons throughout the study. — connects to: The implicit association test measures bias via response latency on concept-sorting tasks. — Wade C. Rowatt and Lewis M. Franklin, Christian Orthodoxy, Religious…, 25; Implicit measures reveal prejudice that explicit self-report instruments cannot capture — John F. Dovidio, Peter Glick, Laurie A. Rudman, On the Nature of Prejudice: Fifty Years…, 759; Implicit prejudice measures are not clearly more valid than survey measures — Christopher Tarman and David O. Sears, The Conceptualization and Measurement…, 223 (+4 more)

Related

• Implicit measures reveal prejudice that explicit self-report instruments cannot capture (similarity 0.90)
• The implicit association test measures bias via response latency on concept-sorting tasks. (similarity 0.90)
• Implicit and explicit prejudice are distinct and can diverge within the same person (similarity 0.84)
• The IAT measures group patterns, not individual bias levels (similarity 0.84)
• Implicit attitude measures reveal prejudice explicit self-reports miss (similarity 0.82)
• Implicit prejudice measures are not clearly more valid than survey measures (similarity 0.82)
• Implicit measures reveal attitudes people cannot or will not report (similarity 0.82)
• Automatic stereotypic associations operate preconsciously and independently of self-reported prejudice (similarity 0.80)
• Implicit measures are required to study nonconscious gender stereotypes (similarity 0.80)
• Laboratory models of unconscious cognition enabled research on implicit social cognition (similarity 0.79)
• Automatic race stereotypes operate regardless of self-reported prejudice (similarity 0.79)
• Implicit racial bias operates outside conscious awareness and explicit beliefs (similarity 0.78)
• Explicit and implicit attitudes operate on different levels and need different measures. (similarity 0.78)

Broader Connections

• Implicit measures reveal prejudice that explicit self-report instruments cannot capture #corroborates (0.95) — John F. Dovidio, Peter Glick, Laurie A. Rudman, On the Nature of Prejudice, 759
• Implicit prejudice measures are not clearly more valid than survey measures #contradicts (0.90) — Christopher Tarman and David O. Sears, The Conceptualization and Measurement…, 223
• Implicit and explicit prejudice are distinct and can diverge within the same person #expands (0.85) — John F. Dovidio, Peter Glick, Laurie A. Rudman, On the Nature of Prejudice, 2170
• Automatic race stereotypes operate regardless of self-reported prejudice #corroborates (0.85)
• Implicit social cognition research reveals prejudice operating below conscious awareness #expands (0.80)
• The IAT measures group patterns, not individual bias levels #qualifies (0.80) — Joseph Avery, Jim Sidanius, Joel Cooper, Gregory Davis, Amanda N., Bias in the Law, 1367