A205 A SNAPSHOT OF WOMEN IN GASTROENTEROLOGY IN CANADA: PICTURE PERFECT?
Bibliographic record
Abstract
Graduating medical school classes in Canada are now 50% or more female. The number of staff gastroenterologists in Canada has been on the rise in the last 20 years but female representation has stayed disproportionately low (30%). To determine proportionate female representation in gastroenterology (GI) at residency, attending and leadership levels. The Canadian Resident Matching Service (CaRMS) was used to obtain data for residency program applicants and matched trainees by gender from 2014–2018. General internal medicine (GIM), general surgery (GS) were analyzed for the PGY1 match. GI and cardiology were analyzed for the PGY4 match. An internet search was conducted for national and provincial gastroenterology associations to determine presidential history by gender (run date July 31, 2018). Similar searches for university affiliated GI training programs directors and academic university GI division heads by gender were conducted. PGY1 match 2014–2018: In GIM, the average number of annual applicants was 1789 (49.4% female). The average number of matched applicants was 487 (49.5% female). In GS, the average number of annual applicants was 357 (41% female). The average number of matched applicants was 90 (54.4% female). PGY4 match 2014–2018): In GI, the average number of applicants annually was 46 (37% female). The average number of matched applicants was 34, (35.3% female). In cardiology, the average number of annual applicants was 76 (29% female). The average number of matched applicants was 54 (27.8% female). Only one major national GI organization was identified, the Canadian Association of Gastroenterology (CAG). Three provincial organizations were identified (Ontario Association of Gastroenterology (OAG), Alberta Society of Gastroenterology (ASG) and Association of Gastroenterologists of Quebec (AGQ)). A review of complete historical data on past presidents by gender revealed the following: In CAG’s 60-year history, only 2/47 (4%) female presidents have ever been elected. In OAG’s 22-year history, no (0/9) female presidents have ever been elected. In AGQ’s 52-year history, 1/14 (7%) of presidents have been female. In ASG’s 8-year history, 1/4 (25%) of presidents have been female. Only 2018 data was available for academic leadership positions. At the time of the search, university division heads across Canada were 0% female (0/15). University GI training program directors across Canada in 2018 were 27% female (4/15). Despite gender equivalency in medical school and GIM, women are under-represented in GI (similar to other procedure sub-specialties such as cardiology). They are also under-represented in major GI leadership roles, demonstrating a need for targeted intervention. None
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.017 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".