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The Effect of Limiting Residents’ Work Hours on Their Surgical Training: A Canadian Perspective

2004· article· en· W2045283581 on OpenAlexaffabout
Ken Romanchuk

Bibliographic record

VenueAcademic Medicine · 2004
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsSaskatoon City HospitalUniversity of Saskatchewan
Fundersnot available
KeywordsLimitingWork (physics)Work hoursPerspective (graphical)Medical educationMedicineDutyVariety (cybernetics)PsychologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.322
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations22
Published2004
Admission routes2
Has abstractyes

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