Regulatory Body Perspectives on Complaints and Disciplinary Action Processes for Health Professionals
Bibliographic record
Abstract
Background:. Previous Canadian reviews of physician, pharmacist, and dentist disciplinary action have noted differences in discipline outcomes across professions and provinces. The objective of this study was to compare the disciplinary action process across provinces and professions, and to describe the perspectives of health professional regulatory bodies on the disciplinary action process.Methods:. Participation from medicine, pharmacy, nursing, and dentistry registrars or complaints directors from 10 Canadian provinces was sought. One-on-one, semi-structured interviews were conducted by telephone or video call.Results:. Nineteen interviews with regulators were conducted—8 pharmacy, 5 nursing, 5 medicine, and 1 dentistry. Complaints and discipline processes followed a similar overall pathway with some differences. Differences in process were largely due to differences in health regulation legislation and were noted across professions, across provinces, and within a province. Participants tended to be more aligned with regulators within their province rather than regulators of the same profession across the country.Conclusion:. To our knowledge, this paper is the first to describe Canadian health professional regulatory body perspectives on the complaints and discipline process. More research is needed to better understand the factors that affect discipline outcomes and to ultimately improve complaints and discipline processes.
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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 | 0.057 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.019 | 0.024 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| 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".