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Record W4360991821 · doi:10.1370/afm.2945

Declining Comprehensiveness of Services Delivered by Canadian Family Physicians Is Not Driven by Early-Career Physicians

2023· article· en· W4360991821 on OpenAlexafffundabout
M. Ruth Lavergne, David Rudoler, Sandra Peterson, David Stock, Carole Taylor, Andrew S. Wilton, Sabrina T. Wong, Ian Scott, Kimberlyn McGrail, Rita McCracken, Emily Gard Marshall, Adrian MacKenzie, Alan Katz, Margaret Jamieson, Lindsay Hedden, Agnes Grudniewicz, Laurie J. Goldsmith, Richard H. Glazier, Fred Burge, Doug Blackie

Bibliographic record

VenueThe Annals of Family Medicine · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsSt. Michael's HospitalNova Scotia Health AuthorityUniversity of OttawaInstitute for Clinical Evaluative SciencesSimon Fraser UniversityUniversity of ManitobaManitoba HealthRoyal Roads UniversityOntario Tech UniversityGolder Associates (Canada)Dalhousie UniversityOntario Shores Centre for Mental Health SciencesUniversity of British ColumbiaUniversity of TorontoCARE Canada
FundersCanadian Institutes of Health ResearchOntario Ministry of Health and Long-Term CareInstitute for Clinical Evaluative Sciences
KeywordsMedicineFamily medicineNova scotiaNursingMinor (academic)Service (business)

Abstract

fetched live from OpenAlex

We describe changes in the comprehensiveness of services delivered by family physicians in 4 Canadian provinces (British Columbia, Manitoba, Ontario, Nova Scotia) during the periods 1999-2000 and 2017-2018 and explore if changes differ by years in practice. We measured comprehensiveness using province-wide billing data across 7 settings (home, long-term care, emergency department, hospital, obstetrics, surgical assistance, anesthesiology) and 7 service areas (pre/postnatal care, Papanicolaou [Pap] testing, mental health, substance use, cancer care, minor surgery, palliative home visits). Comprehensiveness declined in all provinces, with greater changes in number of service settings than service areas. Decreases were no greater among new-to-practice physicians.

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)0.001
metaresearch head score (Gemma)0.011
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 score0.063
Threshold uncertainty score0.455

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.007
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.269
GPT teacher head0.462
Teacher spread0.194 · 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

Citations19
Published2023
Admission routes3
Has abstractyes

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