LGBTQ-Related Material in Undergraduate Medical Education in the Mid-Atlantic Region of the United States
Bibliographic record
Abstract
Purpose This study describes the current state of formal lesbian, gay, bisexual, transgender and queer (LGBTQ)-related education at undergraduate medical schools in the Mid-Atlantic region of the United States. A review of literature shows the last time a similar study was conducted was in 2011 by Obedin-Maliver et al and was a survey that included all medical schools of the United States and Canada. Given the changes over time for both the LGBTQ and medical community , it is likely that the state of LGBTQ-related education in undergraduate medical education has changed greatly. Methods This was a cross-sectional Internet-based survey, utilizing Qualtrics to deliver the questionnaire. An email with a unique link to the survey was sent to the designated Dean of Diversity and Inclusion or Dean of Medical Education of all Doctor of Medicine (MD)-granting medical schools and Doctor of Osteopathic Medicine (DO)-granting medical schools in the Mid-Atlantic (Delaware, Maryland, New Jersey, New York, Pennsylvania) region. This questionnaire is derived from the 2011 Obedin-Malliver study and includes 13 questions that evaluate LGBTQ-related undergraduate medical school materials. Results and Conclusions Of the 35 schools, 15 (42.9%) responded and 13 (37.1%) completed the survey. The median time dedicated to teaching LGBTQ-related content in the entire curriculum was 8 hours (interquartile range [IQR], 6-13 hours). None of the schools reported zero hours during pre-clinical years, but 6 (46.1%) schools reported 0 hours during the clinical years. Work should be done to improve both pre-clinical and clinical LGBTQ-related content.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".