Institutional Accountability for Students With Disabilities: A Call for Liaison Committee on Medical Education Action
Bibliographic record
Abstract
Medical educators and leaders have called for greater diversity among the physician workforce, including those with disabilities. However, many students with disabilities are precluded from entering and completing medical training due to historically restrictive technical standards and poor internal practices to protect student privacy. This limits the possibilities for growing this part of the workforce and making progress toward the ultimate goal of having a physician workforce that better represents the patients it serves. To achieve diversity among the physician workforce, medical education must create environments that allow students with disabilities to apply to, flourish in, and feel well supported in medical school. Recent additions to Accreditation Council for Graduate Medical Education requirements have helped to catalyze work in the area of disability inclusion by incorporating disability-focused mandates into graduate medical education accreditation standards. However, similar mandates for undergraduate medical education have not yet materialized. In this article, the authors call for the Liaison Committee on Medical Education (LCME) to elevate disability as a valued part of medical school diversity in its accreditation standards and to include protections for disabled students. The authors propose that the LCME can take 5 actions to promote institutional accountability toward students with disabilities: (1) define disability as diversity, (2) mandate disability support, (3) protect from conflicts of interest, (4) protect privacy, and (5) verify schools' technical standards comply with the Americans with Disabilities Act. By adopting these recommendations, the LCME would send the powerful message that students with disabilities bring welcome expertise and value to the medical community.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".