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Record W4389620874 · doi:10.12927/hcpol.2023.27233

Training in Team-Based Practices: A Descriptive Analysis of Family Medicine Postgraduate Site Distribution across Canada

2023· article· en· W4389620874 on OpenAlexafffundvenueabout
Asiana Elma, Laurie Yang, Irene Chang, Lawrence Grierson

Bibliographic record

VenueHealthcare policy · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcMaster University Medical CentreHamilton Health SciencesUniversity of TorontoMcMaster UniversityPopulation Health Research Institute
FundersMcMaster University
KeywordsAccreditationGraduation (instrument)Training (meteorology)Medical educationGraduate medical educationDescriptive statisticsDistribution (mathematics)Family medicineMedicinePsychologyGeography

Abstract

fetched live from OpenAlex

Background: College of Family Physicians of Canada accreditation policies contemplate exemplary ratings for postgraduate family medicine programs that train residents in sites aligned with the Patient's Medical Home (PMH) vision. This may overrepresent the PMH in training relative to what is available in independent practice. Methods: We appraised training sites to describe the degree to which PMH features are present in family medicine education across the country. Results: More than half (70.7%) of Canadian training sites reflect PMH features. Conclusion: Education policy that incentivizes PMH in training may create downstream tension for physicians who find these practices unavailable upon graduation.

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)0.002
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 score0.145
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.007
Science and technology studies0.0010.000
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 head0.271
GPT teacher head0.535
Teacher spread0.264 · 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

Citations2
Published2023
Admission routes4
Has abstractyes

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