GENDER DIAGNOSTICITY - A NEW BAYESIAN-APPROACH TO GENDER-RELATED INDIVIDUAL-DIFFERENCES

Gender diagnosticity refers to the Bayesian probability that an individual is predicted to be male or female on the basis of some set of gender-related diagnostic indicators. We computed gender diagnostic probabilities from occupational preference ratings made by 117 male and 110 female subjects. Subjects also completed the Personal Attributes Questionnaire and the Bem Sex-Role Inventory and were assessed on a number of gender-related criterion variables. Gender diagnostic probabilities proved to be factorially distinct from PAQ and BSRI masculinity and femininity and generally displayed greater predictive utility than did masculinity and femininity. Unlike existing scales, gender diagnosticity measures are not based on gender stereotypes, and they do not reify gender-related individual differences or freeze them into specific constructs such as instrumental or expressive traits. Furthermore, they are well suited to developmental and cross-cultural research.