Duty Hours Reforms in the United States, France, and Canada: Is It Time to Refocus Our Attention on Education?
Bibliographic record
Abstract
Resident duty hours restrictions have now been instituted in many countries worldwide. Such policies have resulted in a broad-based discussion in the medical literature concerning their effects on patient care, resident education, and resident well-being. To better understand the impetuses behind these changes, the authors examine not only the duty hours mandates currently in effect in the United States, Canada, and France, but also the events influencing their independent development in these three countries. In the United States, an 80-hour resident workweek was mandated by the Accreditation Council for Graduate Medical Education out of concern for patient safety. In France, a 52.5-hour workweek was decreed by the government, reflecting the broader European Working Time Directive initiated out of concern for the negative impact of extended work hours on its population. In Canada, resident unions, whose primary interest has been one of resident well-being, have negotiated a series of reduced resident duty hours that approach those mandated in the United States. At the core of these changes are unique differences in these countries' health care and medical education systems. The resulting diversity in the origin and nature of such regulations serves to highlight the lack of evidence that has guided their development and the need to refocus on the educational elements of postgraduate training.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 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".