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Record W3125039791

Grey Zones: Emerging Issues at the Boundaries of the Canada Health Act

2012· article· en· W3125039791 on OpenAlexaboutno aff
Gerard W. Boychuk

Bibliographic record

VenueC.D. Howe Institute Commentary · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsDiscretionSubject (documents)Public administrationHealth careHealth servicesBusinessPolitical scienceEconomic growthLawMedicineEnvironmental healthEconomicsLibrary science
DOInot available

Abstract

fetched live from OpenAlex

The Canada Health Act (CHA) creates a series of “grey zones” in which considerable discretion is granted to the federal health minister to determine what is subject to penalty under the Act. This report outlines the provisions of the CHA, and examines four current issues relating to the Act: annual fees charged by integrative health clinics; provincial healthcare deductibles; provincial funding of health services purchased or insured out-of-country; and provincial funding of out-of-province health services facilitated by private medical concierge services. In each case, the Commentary examines how the practice might be subject to penalties under the CHA, and highlights the federal role to date in debates on these issues.

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)0.020
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.788
Threshold uncertainty score0.914

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0430.062
Scholarly communication0.0240.010
Open science0.0060.006
Research integrity0.0270.030
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 head0.027
GPT teacher head0.312
Teacher spread0.285 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2012
Admission routes1
Has abstractyes

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