Disclosing disabilities: Barriers for medical school applicants
Bibliographic record
Abstract
This study investigated the availability of accommodation request procedures for medical school admissions interviews and the accessibility of Technical Standards (TS) for candidates with disabilities (CWD) across Liaison Committee on Medical Education (LCME)-accredited institutions in the United States and Canada. Utilizing a cross-sectional study methodology, surveys were distributed to Deans of Admissions and Disabilities Resource Professionals (DRP) at all LCME-accredited US and Canadian MD programs. Surveys gathered data about interview formats, interview accommodation procedures, and TS accessibility during the 2018-2019 academic year. We received responses from 71 institutions (41.3%), with 56.3% survey completion rate (n = 40). Among respondents, interview formats varied: 26.8% (n = 19) Multiple Mini Interview, 32.4% (n = 23) Traditional Interviews, and 16.9% (n = 12) hybrid. 38% (n = 27) of respondents informed CWD of accommodation procedures before interviews. Ten institutions (14.1%) indicated they had updated their procedure since the 2018-2019 academic year, which demonstrated better overall outcomes. Statistical analyses showed significant differences between institutions with/without updated procedures in the total number of applicants who requested accommodations, were granted interviews, provided interview day accommodation, offered admission, and matriculated (p = 0.005). In 66.7% (n = 18) of respondent institutions, admissions staff were aware of initial interview accommodation requests and 44.4% (n = 12) involved admissions staff when communicating accommodation plans. Among 27 schools, 55.6% (n = 15) required no documentation to support the CWD's need for accommodation; the rest required a form, clinician's letter, past proof, or other methods. 56.3% (n = 40) responded questions about TS and confirmed posting them on their website, with 77.5% (n = 31) on their admissions webpage. 77.5% (n = 31) also reported including language in the TS that direct CWD to the institution's disability office. This study reveals communication deficiencies about accommodations and TS requirements during the admissions process. Recommendations to enhance accessibility include informing candidates early about accommodation procedures and TS, and utilizing DRPs as CWD's primary accommodation contact.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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 source (direct Gemma or distilled Codex), 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".