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Record W2799704751 · doi:10.3138/utlj.2017-0055

Canadian legislatures and the regulation of the private health-care industry

2018· article· en· W2799704751 on OpenAlexaffvenueabout
Marie‐Claude Prémont, Cory Verbauwhede

Bibliographic record

VenueUniversity of Toronto Law Journal · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsUniversité du Québec à MontréalÉcole Nationale d'Administration Publique
Fundersnot available
KeywordsCharterLegislaturePublic administrationHealth careBusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

This article discusses the three regulatory measures that Canadian provinces have used to implement the Canada Health Act criteria of universality, accessibility, and comprehensiveness. These three measures – the prohibition of duplicative private insurance, the prohibition of mixed private–public practice, and the capping of private physician fees to the levels of public fee schedules – are designed, above all, to regulate the health-care insurance and delivery industries. The article highlights the dangers of superficial analysis by the courts that is limited to canvassing potential violations of some patients’ individual rights, without taking into account the intricacies of health-care industry regulations and their effects on the public system as a whole. Without the vigilance of the courts, the Canadian Charter of Rights and Freedoms can certainly become the industry’s best ally in forcing a radical realignment of public policy in health-care systems across the country, without democratic debate.

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)0.010
metaresearch head score (Gemma)0.022
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: Empirical · Consensus signal: none
Teacher disagreement score0.138
Threshold uncertainty score0.998

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.022
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0190.018
Scholarly communication0.0110.002
Open science0.0020.004
Research integrity0.0070.008
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 head0.016
GPT teacher head0.212
Teacher spread0.196 · 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
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
Published2018
Admission routes3
Has abstractyes

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