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Record W7037746418

Federalism and Health Care in Canada: A Troubled Romance?

2017· article· en· W7037746418 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2017
Typearticle
Languageen
FieldNursing
TopicNuts composition and effects
Canadian institutionsnot available
Fundersnot available
KeywordsFederalismHealth careJurisdictionFederal jurisdictionPublic healthGovernment (linguistics)Health policyConstitutionHealth law
DOInot available

Abstract

fetched live from OpenAlex

Canadian federalism fragments health system governance Although the Constitution has been interpreted as providing shared jurisdiction over health generally with respect to health care specifically the courts have interpreted the Constitution as giving direct jurisdiction to the provinces The Federal role in health care is therefore indirect but nevertheless potentially powerful For example the Federal government has used its spending powers to establish the Canada Health Act CHA which commits funding to provinces on condition they provide firstdollar public coverage of hospital and physician services However in recent times as federal contributions have declined the CHA has been weakly enforced Further the failure to broaden the CHA to include prescription drugs dentistry and other important aspects of health care have contributed to Canada's abysmal record on aboriginal health and its increasingly poor rankings in international comparisons Progress requires enforcement of an adequately funded CHA national pharmacare and concerted action on aboriginal health It requires bolder federal action and a panCanadian approach to governance in which federalism again becomes a laboratory of experimentation including on health human resource planning drug utilization and safety health emergency readiness health technology assessment electronic health information systems and systemlevel quality assurance

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)0.012
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.295
Threshold uncertainty score0.817

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.010
Science and technology studies0.0380.057
Scholarly communication0.0230.010
Open science0.0040.009
Research integrity0.0120.018
Insufficient payload (model declined to judge)0.0160.001

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 head0.274
Teacher spread0.258 · 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 designTheoretical or conceptual
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

Citations0
Published2017
Admission routes1
Has abstractyes

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