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Racial Preferences at a Texas Medical School

David Puelz

Abstract

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.

Racial Preferences at a Texas Medical School

Abstract

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.
Paper Structure (12 sections, 12 figures, 18 tables)

This paper contains 12 sections, 12 figures, 18 tables.

Table of Contents

  1. Introduction
  2. Data and Methods
  3. Data
  4. Methods
  5. Summary Statistics of Admission Rates
  6. Admission Rates and Observable Characteristics
  7. Academic Index
  8. The Role of Race in Admissions
  9. Regressions
  10. Conclusion
  11. Race Variable Definition
  12. Admitted Sample Summary Statistics

Figures (12)

  • Figure 1: Distributions of the academic index deciles across racial categories.
  • Figure 2: Predicted probability of admission for males with varying quantiles of MCAT, GPA, science GPA, and casper score using model 5.
  • Figure 3: Percentage change in admit cohort composition when racial preferences/penalties are removed.
  • Figure 4: MCAT score by race. Boxes represent the inner-quartile-range (25th to 75th quantiles), and the solid black line represents the median.
  • Figure 5: MCAT score by gender. Boxes represent the inner-quartile-range (25th to 75th quantiles), and the solid black line represents the median.
  • ...and 7 more figures