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Primary care in Ontario, Canada: New proposals after 15 years of reform

2016· article· en· W2339632938 on OpenAlexaffabout
Gregory P. Marchildon, Brian Hutchison

Bibliographic record

VenueHealth Policy · 2016
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsRestructuringGovernment (linguistics)Primary carePosition (finance)Health care reformPaymentPublic administrationService (business)BusinessInvestment (military)MedicineEconomic growthPolitical scienceFamily medicineHealth careFinanceEconomicsHealth policyPoliticsLaw

Abstract

fetched live from OpenAlex

Primary care has proven to be extremely difficult to reform in Canada because of the original social compact between the state and physicians that led to the introduction of universal medical care insurance in the 1960s. However, in the past decade, the provincial government of Ontario has led the way in Canada in funding a suite of primary care practice models, some of which differ substantially from traditional solo and group physician practices based on fee-for-service payment. Independent evaluations show some positive improvements in patient care. Nonetheless, the Ontario government's large investment in the reform combined with high expectations concerning improved performance and the deteriorating fiscal position of the province's finances have led to major conflict with organized medicine over physician budgets and the government's consideration of an even more radical restructuring of the system of primary care in the province.

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)0.033
metaresearch head score (Gemma)0.033
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.739
Threshold uncertainty score0.858

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0110.015
Scholarly communication0.0140.004
Open science0.0050.005
Research integrity0.0130.007
Insufficient payload (model declined to judge)0.0050.000

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 head0.037
GPT teacher head0.394
Teacher spread0.358 · 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

Citations126
Published2016
Admission routes2
Has abstractyes

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