The Under-representation of Canadian Women in Gastroenterology from Residency to Leadership
Bibliographic record
Abstract
BACKGROUND: To determine representation of women in gastroenterology (GI) at residency and leadership levels in Canada. METHODS: -tests were used to compare proportion of women entering each residency program. An internet search was conducted to calculate percentages of women as GI association presidents, residency program directors, division heads and oral speakers at conferences. RESULTS: IM residency had on average of 1789 applicants with 487 matched (49.4% versus 49.5% women). GS residency had on average 357 applicants with 90 matched (41% versus 54.4% women). GI residency had on average 46 applicants with 34 matched (37% versus 35.3% women). Cardiology residency had on average 76 applicants with 54 matched (29% versus 27.8% women).The Canadian Association of Gastroenterology (CAG) has had two out of 47 (4.2%) women presidents. The Ontario Association of Gastroenterology (OAG) has had no women presidents (0/9). The Association des gastro-entérologues du Québec (AGEQ) has had two out of 15 (13%) women presidents. The Alberta Society of Gastroenterology (ASG) has had one out of five (20%) women presidents. From 2018 to 2020, university division heads ranged from 0% to 13.3% women (0 to 2/15). University GI training program directors ranged from 28.6% to 35.7% (4 to 5/14). Women speakers at CAG's annual conference varied 27% to 42% from 2016 to 2020, averaging 32.7%. Women speakers at OAG's, AGEQ's and ASG's annual conferences averaged 23.3%, 24.1% and 35%, respectively. CONCLUSION: Women gastroenterologists display low representation at multiple levels along the GI career pathway.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 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".