A missed opportunity: how signal detection theory can advance research on prejudice detection

Subtle, everyday prejudice continues to affect outcomes in work, education, counseling, and health care. A critical step toward mitigating these effects is the ability to recognize prejudice when it occurs, yet individuals often disagree about whether a given incident reflects bias. Existing quantitative approaches to studying prejudice detection often confound two distinct processes: accuracy in distinguishing prejudiced from non-prejudiced events and general tendencies to label ambiguous events as prejudiced or not. Signal Detection Theory (SDT) offers a methodological framework that separates these processes, thereby improving measurement validity and enabling novel empirical inquiry. This paper provides accessible guidance for applying SDT's methods to the quantitative study of prejudice detection, including stimulus design, analytic procedures, and available software tools. By introducing SDT's methods into prejudice detection research, this paper provides a rigorous framework for separating detection accuracy from response tendencies, thereby improving measurement validity and enabling novel theoretical inquiry into the identification of subtle prejudice.