The Effect of Limiting Residents’ Work Hours on Their Surgical Training: A Canadian Perspective
Bibliographic record
Abstract
Restrictions in residents' work hours have been in place in Canada for roughly a decade, having been negotiated rather than imposed. The changes in residents' schedules that resulted are roughly equivalent to the limitation of 80 duty hours per week in the United States. When work-hours restrictions began, surgery faculty were worried that residents' experience would be compromised. But these fears have not materialized. Why? The author maintains there are many reasons. (1) Most surgical procedures are now faster, and lengthy inpatient care has diminished, all of which saves time. (2) Formerly difficult or risky procedures are now performed more frequently and safely, which increases residents' education about difficult conditions. (3) A variety of resources (e.g., skills-transfer courses, surgical simulators, etc.) are now available for residents to learn and evolve surgical techniques, and residents take advantage of these resources, being highly motivated to learn the best in the time available to them. (4) There have been positive changes in residents' education that have helped them become more efficient learners than before, with improved resources and skills for faster access to information. The author maintains that in his present surgery residency program, the residents still work extremely hard but are more protected from the unending demands for patient care. They have more time for orderly study and greater opportunities to develop skills other than technical ones. They are in a happier work setting, which the author strongly believes facilitates improved patient care.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.028 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| 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".