MétaCan
Menu
Back to cohort

Residentsʼ Duty Hours in the Province of Ontario, Canada

2003· article· en· W2072084177 on OpenAlexaffabout
Murray B. Urowitz, Anne-Marie Crescenzi, L. Muharuma

Bibliographic record

VenueAcademic Medicine · 2003
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNegotiationArbitrationDutyCollective agreementMedicinePolitical scienceFamily medicineMedical educationCollective bargainingLaw

Abstract

fetched live from OpenAlex

The author explains the history of the Professional Association of Internes and Residents of Ontario (PAIRO), Canada, founded in 1968-69 to represent postgraduate medical trainees in negotiations with the Ontario Hospital Association over issues of trainees' stipends. Over the years, the negotiations evolved to cover a number of other issues, including duty hours, and established the principle that binding arbitration would be used to resolve any disputes between the two parties that could not be resolved through negotiation. At present, PAIRO negotiates a biannual collective agreement with the Ontario Council of Teaching Hospitals (OCOTH), whose features the author describes. The most important provisions of the 2000-2002 PAIRO-OCOTH agreement on the limits of duty hours are described. The author then comments that while such limits have benefited programs and residents, there is concern that the limits decrease the opportunities for trainees to be involved in the care of patients with a wide variety of medical conditions. Also, the duty-hours limits have required some services to use attending physicians or outside health professionals to perform duties previously carried out by trainees, creating problems that the author describes.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.060
Threshold uncertainty score0.435

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.017
GPT teacher head0.285
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueAcademic MedicineSame topicHospital Admissions and OutcomesFrench-language works237,207