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Main Author: Puelz, David
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2602.18484
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author Puelz, David
author_facet Puelz, David
contents Whether and how race is used in selective admissions remains a central question in higher education and civil rights law. In Students for Fair Admissions v. Harvard (2023), the Supreme Court held that race-based affirmative action in college admissions violates the Equal Protection Clause, purportedly ending the practice. This report examines admissions at a public medical school in the pre-SFFA period. Using applicant-level data on over 11,000 applications to Texas Tech University Health Sciences Center Medical School for the 2021 and 2022 cycles, I relate admission decisions to academic merit (MCAT, GPA, science GPA), race, gender, and situational judgment (Casper) scores. Summary statistics, academic-index decompositions, and logistic regression models provide strong evidence of racial preferences: African American and Hispanic applicants are preferred relative to academically similar White and Asian applicants. Counterfactual and preference-removal analyses quantify the magnitude of these disparities. The findings document the kind of race-based preferences that SFFA was meant to address and establish a baseline for assessing whether admissions practice changed after the decision.
format Preprint
id arxiv_https___arxiv_org_abs_2602_18484
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Racial Preferences at a Texas Medical School
Puelz, David
General Economics
Economics
Whether and how race is used in selective admissions remains a central question in higher education and civil rights law. In Students for Fair Admissions v. Harvard (2023), the Supreme Court held that race-based affirmative action in college admissions violates the Equal Protection Clause, purportedly ending the practice. This report examines admissions at a public medical school in the pre-SFFA period. Using applicant-level data on over 11,000 applications to Texas Tech University Health Sciences Center Medical School for the 2021 and 2022 cycles, I relate admission decisions to academic merit (MCAT, GPA, science GPA), race, gender, and situational judgment (Casper) scores. Summary statistics, academic-index decompositions, and logistic regression models provide strong evidence of racial preferences: African American and Hispanic applicants are preferred relative to academically similar White and Asian applicants. Counterfactual and preference-removal analyses quantify the magnitude of these disparities. The findings document the kind of race-based preferences that SFFA was meant to address and establish a baseline for assessing whether admissions practice changed after the decision.
title Racial Preferences at a Texas Medical School
topic General Economics
Economics
url https://arxiv.org/abs/2602.18484