Surgeons disciplined by regulatory bodies in Canada between 2000 and 2017
Bibliographic record
Abstract
Summary Identifying characteristics of disciplined surgeons is important for public safety. A database of all physicians disciplined by a Canadian provincial medical regulatory authority (College of Physicians and Surgeons) between 2000 and 2017 was constructed, and comparisons between surgeons and other physicians were undertaken. Of 1100 disciplined physicians, 174 (15.8 %) were surgeons. Obstetrics and gynecology was the specialty with the most disciplined surgeons (57 of 174 [32.8%]), followed by general surgery (48 of 174 [27.6%]). The overall disciplinary rate for surgeons was higher than for other physicians (12.59, 95 % confidence interval [CI] 10.69–14.83 v. 9.85, 95 % CI 8.88–10.94 cases per 10 000 physician-years, p = 0.013). Even after adjusting for surgeon age, sex, international medical graduation and years in practice, surgeons remained more likely than other physicians to be disciplined for standard of care issues (55.6%, 95% CI 46.6–64.2 v. 38.7%, 95% CI 32.6–45.2, p < 0.001).
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| 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) | 0.004 | 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".