Proportion of women presenters at medical grand rounds at major academic centres in Canada: a retrospective observational study
Bibliographic record
Abstract
OBJECTIVE: To assess the proportion of women who presented research or medical grand rounds at five major academic hospitals in Canada. DESIGN: A cross-sectional study. SETTING: Five major university-affiliated hospitals in Toronto and Calgary. RESULTS: Overall, at all sites and types of academic rounds, there were an average of 17% fewer women presenting than men (P<0.001). There were an average of 32% and 21% more men presenting at the city-wide grand rounds in cities A and B, respectively (P<0.001, P=0.002). There were more male speakers at four out of five types of rounds. The proportion of women presenting on average was proportional to the Canadian workforce, but on average, below the proportion of female residents and medical students (median ratio 1.1, 0.7 and 0.8, respectively). CONCLUSION: Our study demonstrated a lower proportion of females in an important outlet for academic recognition and role modelling. This provides a possible contributing factor to the under-representation of women in academic medicine and an area that can be systematically targeted to promote equity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".