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Record W1884379431 · doi:10.3402/gha.v8.27968

Understanding the social determinants of health among Indigenous Canadians: priorities for health promotion policies and actions

2015· review· en· W1884379431 on OpenAlexaffabout
Fariba Kolahdooz, Forouz Nader, Kyoung June Yi, Sangita Sharma

Bibliographic record

VenueGlobal Health Action · 2015
Typereview
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsMemorial University of NewfoundlandUniversity of Alberta
Fundersnot available
KeywordsIndigenousHealth equitySocial determinants of healthHealth promotionHealth policyLife expectancyEconomic growthEthnic groupPublic healthGovernment (linguistics)MedicineEnvironmental healthPolitical scienceSocioeconomicsGerontologyPopulationSociologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Indigenous Canadians have a life expectancy 12 years lower than the national average and experience higher rates of preventable chronic diseases compared with non-Indigenous Canadians. Transgenerational trauma from past assimilation policies have affected the health of Indigenous populations. OBJECTIVE: The purpose of this paper is to comprehensively examine the social determinants of health (SDH), in order to identify priorities for health promotion policies and actions. DESIGN: We undertook a series of systematic reviews focusing on four major SDH (i.e. income, education, employment, and housing) among Indigenous peoples in Alberta, following the protocol Preferred Reporting Items for Systematic Reviews and Meta-Analysis-Equity. RESULTS: We found that the four SDH disproportionately affect the health of Indigenous peoples. Our systematic review highlighted 1) limited information regarding relationships and interactions among income, personal and social circumstances, and health outcomes; 2) limited knowledge of factors contributing to current housing status and its impacts on health outcomes; and 3) the limited number of studies involving the barriers to, and opportunities for, education. CONCLUSIONS: These findings may help to inform efforts to promote health equity and improve health outcomes of Indigenous Canadians. However, there is still a great need for in-depth subgroup studies to understand SDH (e.g. age, Indigenous ethnicity, dwelling area, etc.) and intersectoral collaborations (e.g. community and various government departments) to reduce health disparities faced by Indigenous Canadians.

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)0.029
metaresearch head score (Gemma)0.052
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: Review · Consensus signal: none
Teacher disagreement score0.147
Threshold uncertainty score0.314

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0060.006
Science and technology studies0.0080.005
Scholarly communication0.0060.006
Open science0.0030.006
Research integrity0.0040.007
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 head0.307
GPT teacher head0.510
Teacher spread0.203 · 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
GenreReview

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

Citations116
Published2015
Admission routes2
Has abstractyes

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