MOSAIC: A Model of Stereotyping Through Associated and Intersectional Categories

Despite increased awareness of a wide range of demographics, existing theory fails to adequately explain how the stereotypes associated with multiple demographic categories (e.g., Black, female, gay, Muslim) combine to influence evaluations of employees. We present MOSAIC, a Model of Stereotyping through Associated and Intersectional Categories, to explain how stereotypes from various demographic categories influence the expectations for, and visibility of, employees. Extending intersectionality research to management scholarship, MOSAIC introduces the concept of an associated demographic category, defined as a category that bears an implicit cognitive link to another demographic category, to make sense of outcomes that were previously seen as anomalies and theoretically reconcile patterns of advantage and disadvantage that individuals experience (e.g., why Black women face less backlash for assertiveness but are less likely to be promoted and earn considerably less than White women). MOSAIC proposes that perceivers integrate the stereotypes from individuals' foundational, intersectional, and associated categories, and that this integration generates amplified or diluted stereotypes. This integrated stereotype content then yields proscriptive, prescriptive, and visibility templates and expectations that explain how bias emerges. As such, MOSAIC advances micro-level explanations for how and why particular configurations of demographic categories yield predictable patterns of stereotypes, expectations, and evaluations.