Innovative levers for sustainable integration of gender medicine into medical school curricula
Bibliographic record
Abstract
Efforts to integrate gender medicine into medical school curricula have focused largely on the work of individual champions. Online sex and gender materials for undergraduate courses have also been developed and disseminated. Success has been sporadic, with varying uptake across schools within and between countries. International trends in medical school accreditation processes and the growing force of the millennial student voice offer untapped opportunities to promote more systematic integration of gender medicine on a national and international level. In this commentary, the president and CEO of the Association of Faculties of Medicine of Canada and the Scientific Director of the Institute of Gender and Health of the Canadian Institutes of Health Research jointly reflect on top-down and bottom-up levers for sustainable innovation in gender medicine for undergraduate medical training.
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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 | 0.021 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.050 | 0.064 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".