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Record W49728341

Law as a Tool for Addressing Social Determinants of Health

2013· article· en· W49728341 on OpenAlexaffabout
Martha Jackman

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSocial determinants of healthHealth equityRight to healthGovernment (linguistics)Action (physics)Political scienceHealth careHealth policyHuman rightsLaw and economicsLawSociology
DOInot available

Abstract

fetched live from OpenAlex

Despite the fact that equality and equal access to health care are core Canadian values, the reality is that Canadians' health is overwhelmingly dictated by the unequal living conditions they experience – the social determinants of health. This chapter examines law as a tool for translating our understanding of health inequities into government action to address social determinants of health. The chapter provides a brief review of the findings and recommendations of some of the major Canadian reports in this area, followed by a review of international and domestic human rights guarantees that can be invoked to challenge health inequity in Canada. The final section examines the obstacles facing determinant of health-related claims, in particular, the continued reliance by Canadian courts on the outmoded distinction between positive and negative rights. The author concludes by suggesting that, rather than focusing on biomedical and lifestyle initiatives, social injustices must be addressed, and that moving forward on determinants of health requires action by all branches of government, including the courts.

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)0.032
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 score0.528
Threshold uncertainty score0.950

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0190.102
Scholarly communication0.0230.011
Open science0.0040.010
Research integrity0.0150.017
Insufficient payload (model declined to judge)0.0060.001

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 head0.046
GPT teacher head0.351
Teacher spread0.305 · 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

Citations3
Published2013
Admission routes2
Has abstractyes

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