Sex and Gender Medical Education Summit: a roadmap for curricular innovation
Bibliographic record
Abstract
The Sex and Gender Medical Education Summit: a roadmap for curricular innovation was a collaborative initiative of the American Medical Women's Association, Laura W. Bush Institute for Women's Health, Mayo Clinic, and Society for Women's Health Research (www.sgbmeducationsummit.com). It was held on October 18-19, 2015 to provide a unique venue for collaboration among nationally and internationally renowned experts in developing a roadmap for the incorporation of sex and gender based concepts into medical education curricula. The Summit engaged 148 in-person attendees for the 1 1/2-day program. Pre- and post-Summit surveys assessed the impact of the Summit, and workshop discussions provided a framework for informal consensus building. Sixty-one percent of attendees indicated that the Summit had increased their awareness of the importance of sex and gender specific medicine. Other comments indicate that the Summit had a significant impact for motivating a call to action among attendees and provided resources to initiate change in curricula within their home institutions. These educational efforts will help to ensure a sex and gender basis for delivery of health care in the future.
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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 | 0.017 | 0.036 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.024 | 0.032 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
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".