On Bias in Detecting Bias: A Signal Detection Analysis of Attributions to Gender Discrimination

Discrimination is the unjust treatment of people based on their group membership, and detecting discrimination is a necessary first step in countering it. Attributions to discrimination have often been conceptualized in terms of Signal Detection Theory (SDT), with researchers speculating about the role of sensitivity (i.e., observers’ ability to recognize discrimination) and response bias (i.e., their tendency to judge that discrimination is present) in observers’ judgments. Here, we take a first step toward moving beyond conceptual applications to empirical SDT analyses of attributions to discrimination across five studies examining judgments about gender discrimination in corporate pay raise decisions. We find that prototypes (Studies 1 to 3) and their alignment with the actual pattern of decisions (Studies 2 to 4) inform observers’ response bias, reflecting differences in their attribution of unfair outcomes to discrimination (Study 5). In contrast, the extent of harm caused by discriminatory outcomes exerts a small effect on sensitivity and a large effect on response bias (Studies 1 to 3), which reflects observers’ determination of a fair standard for decisions (Study 5). Theoretically, the present work contributes to the causal analysis of central factors shaping attributions to discrimination. Specifically, we shed light on whether effects of these factors are mediated by response bias or sensitivity, and assess their causal origin in either the application of a merit standard or attributional processing.