“We Need a Seismic Shift”: Disabled Student Perspectives on Disability Inclusion in U.S. Medical Education
Bibliographic record
Abstract
PURPOSE: Students with disabilities have inequitable access to medical education, despite widespread attention to their inclusion. Although systemic barriers and their adverse effects on medical student performance are well documented, few studies include disabled students' first-person accounts. Existing first-person accounts are limited by their focus predominantly on students who used accommodations. This study bridged these gaps by analyzing a national dataset of medical students with disabilities to understand their perceptions of disability inclusion in U.S. medical education. METHOD: The authors analyzed 674 open-text responses by students with disabilities from the 2019 and 2020 Association of American Medical Colleges Year Two Questionnaire responding to the prompt, "Use the space below if you would like to share anything about your experiences regarding disability and medical school." Following reflexive thematic analysis principles, the authors coded the data using an inductive semantic approach to develop and refine themes. The authors used the political-relational model of disability to interpret themes. RESULTS: Student responses were wide-ranging in experience. The authors identified key dimensions of the medical education system that influenced student experiences: program structure, processes, people, and culture. These dimensions informed the changes students perceived as possible to support their access to education and whether pursuing such change would be acceptable. In turn, students took action to navigate the system, using administrative, social, and internal mechanisms to manage disability. CONCLUSIONS: Key dimensions of medical school affect student experiences of and interactions with disability inclusion, demonstrating the political-relational production of disability. Findings confirm earlier studies on disability inclusion that suggest systemic change is necessary, while adding depth to understand how and why students do not pursue accommodations. On the basis of student accounts, the authors identify existing resources to help medical schools remedy deficits in their systems to improve their disability inclusion practice.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".