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Record W7047975817

Indigenous Peoples and Health Law and Policy: Responsibilities and Obligations

2017· article· en· W7047975817 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousCorporate governanceHealth lawHealth policyWork (physics)Health careRight to healthHuman rights
DOInot available

Abstract

fetched live from OpenAlex

Much more than the study of laws relevant to the area of medicine, Canadian Health Law and Policy draws together the legal and policy issues that are relevant to human health, and sheds new light on emerging and continuing trends. Written by Canada's leading health law scholars, the fifth edition of this unique work provides expert commentary and analysis on a wide range of emerging health law related issues. It is a vital resource for anyone seeking to understand the developing and critical issues in health law and policy.\nState governance of Indigenous health in Canada is burdened by inequitable administrative structures and policy-based arrangements which were born of eras that denied the right of Indigenous peoples to self-govern. Although no longer resting on explicitly racist premises, this governance regime remains only partially aligned with Indigenous understandings of health and well-being. Moreover, no federal entity has assumed responsibility for a national governance structure, nor have the provinces and territories committed to a comprehensive governance structure to foster Indigenous health. The result is a cumbersome series of programs and policies with varying criteria for access, even among Indigenous populations within the same region. Governance of Indigenous health lacks the foundational principles that otherwise underpin health care governance in Canada.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.832
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.312
Teacher spread0.290 · 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 teacher head, not a consensus.

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

Citations2
Published2017
Admission routes1
Has abstractyes

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