Admissions Priorities and Campus Diversity: Insights from the Common Data Set
Abstract
Legacy preference is the practice of favoring college applicants with family ties to alumni. Critics argue that it reproduces advantage across generations. Yet a basic question remains open: do institutions that publicly report considering legacy enroll different shares of underrepresented racial and ethnic minority students? No centralized dataset has linked comparable admissions-priority reports to enrollment composition. The Common Data Set offers a way to build one. In it, institutions rate the importance of admissions criteria on a shared scale and report enrollment counts by race and ethnicity. We build such a dataset for highly selective institutions over 2010–2022, linking stated priorities to enrollment outcomes. Institutions that report considering legacy status have first-year enrollment shares of underrepresented students about 6 to 8 percentage points lower than institutions that do not. This estimate is net of sector and other reported priorities. The adjusted gap exceeds the unadjusted difference because raw comparisons conflate legacy emphasis with the public–private divide. The association is statistically significant at conventional levels in the primary specification and a balanced subsample. It is stable in sign and magnitude across control constructions, functional forms, and observed institutional covariates. Because the sample is modest and unobserved characteristics remain uncontrolled, we interpret the pattern as a descriptive association, not a causal effect of legacy policy. Treating reported priorities as standardized organizational signals yields a replicable framework for tracking how stated priorities align with enrollment composition. The issue has taken on heightened importance after Students for Fair Admissions v. Harvard.
Fields of Study & Subjects
Higher Education Research Studies
Medical Education and Admissions
Higher Education Governance and Development
Publication details
- Publication date
- 2 January 2026
- Document type
- Preprint