Longitudinal Latent Models and the Potential for Equity in a Post-Race Consciousness Policy Environment

• In Event: AERA Roundtable Session Saturday 3:45 pm - Gold 4
  In Roundtable Session: RT2: Quantitative Advances and Approaches to Research on Inclusion, Equity, Educational Disparities and Student Success

Abstract

The 2024 Supreme Court decision in the Students for Fair Admissions v. Harvard case eliminates race-conscious college admissions, challenging efforts to advance equity in higher education through affirmative action. This paper explores how equity can still be meaningfully assessed without relying on explicit racial categories. It introduces longitudinal latent class analysis (LLCA)—a statistical method underused in education research—as a tool for identifying equity-relevant student subgroups based on academic and experiential trajectories over time. Drawing on quantitative critical race (QuantCrit) and intersectionality theories, the paper examines NCES HSLS data to show how LLCA can support data-driven, legally aligned equity strategies. This approach offers higher education institutions a way to continue equity-focused research and policy development in a post-race consciousness admissions landscape.

Author

• Tafadzwa Tivaringe, Spencer Foundation