Do Patients Want “Diversity” or Competence? | Dr. Stephen Kershnar (E188)

A philosophy professor/lawyer argues that med-school “holistic” + diversity-weighted admissions are less predictive than a numbers-based algorithm—and that the stakes show up downstream in physician quality, access, and patient outcomes. Guest bio: Dr. Steven Kirschner (as stated in your intro) is a distinguished teaching professor of Philosophy at SUNY Fredonia and also an attorney; he authored the 2024 paper “The Diversity Argument for Affirmative Action in Medical School: A Critique” (Journal of Controversial Ideas). Topics discussed: Holistic admissions vs. algorithmic/metrics-based selection The “15% top GPA+MCAT rejected” claim (2019–2022) Medical error estimates and why measurement is messy Predictive validity: MCAT, GPA, boards, and what doesn’t predict Specialty selection, pass/fail exams, and ranking problems DEI/affirmative action post–Supreme Court and “relabeling” effects Workforce shortages, incentives, and productivity (incl. part-time work) Disability accommodations, testing integrity, and gaming incentives Diversity-of-thought vs demographic diversity; “underserved communities” argument The uncomfortable “should patients use demographics as signals?” question Main points: Admissions should prioritize statistically validated predictors (MCAT + GPA, etc.), not interviews/essays/“compelling stories.” Holistic admissions is inconsistent and unvalidated, often functioning like an opaque quota-by-proxy system. Medical error and accountability make physician quality a high-stakes selection problem (even if exact death counts are disputed). If underserved-service is the goal, subsidize it directly (pay, loan forgiveness, tuition incentives) rather than indirectly via admissions preferences. Credential changes (e.g., pass/fail) can make it harder to sort candidates for competitive specialties. Workforce shortages strengthen the case for optimizing for long-run productivity and retention, not symbolic criteria. The taboo question: whether individuals should use group-level stats as a decision heuristic when individual-level info is limited. Top 3 quotes: “The number one error is that we're waiting, giving diversity, um a large amount of weight.” “Medical school admissions are done through… a holistic means… and they weight things that have not been statistically validated.” “The awkward but correct approach is to say, yes, you should.” (re: whether people should use demographics as predictors) 🎙 The Pod is hosted by Jesse Wright💬 For guest suggestions, questions, or media inquiries, reach out at https://elpodcast.media/📬 Never miss an episode – subscribe and follow wherever you get your podcasts.⭐️ If you enjoyed this episode, please rate and review the show. It helps others find us. Thanks for listening!