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Record W3000189960 · doi:10.1111/cag.12592

Long‐term trends in health status and determinants of health among the off‐reserve Indigenous population in Canada, 1991–2012

2020· article· en· W3000189960 on OpenAlexaffvenueabout
Darius Wrathall, Kathi Wilson, Mark W. Rosenberg, Marcie Snyder, Shyra Barberstock

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsIndigenousHealth equityPopulationHealth careSocial determinants of healthPopulation healthEquity (law)SocioeconomicsGeographyUrbanizationEconomic growthEnvironmental healthMedicinePolitical scienceSociologyEcologyEconomics

Abstract

fetched live from OpenAlex

The Indigenous population in Canada totals approximately 1.6 million individuals, representing about 5% of the total population. The off‐reserve Indigenous population represents the fastest growing segment of the Indigenous population, with over 50% living in urban settings. Despite the size of the off‐reserve population, research on the health of Indigenous peoples tends to remain focused on reserve‐based populations. The purpose of this paper is to contribute to a better understanding of health and social determinants of health among off‐reserve Indigenous peoples in Canada. Using data from the 1991 and 2012 Aboriginal Peoples Surveys this paper examines changes in health status and the social determinants of health over a 20‐year time span. Results show a decline in health care use and self‐reported health status in the period between 1991 and 2012. The results may be related to urbanization, aging, and increased prevalence of some chronic conditions. The findings may also be tied to barriers to achieving adequate off‐reserve health care—jurisdictional disputes, disjointed program coverage, systemic racism, and a lack of equity‐oriented health services. There remains a pressing need for Indigenous and non‐Indigenous governments, researchers, and policymakers to build new relationships that bridge these gaps in health and access to timely care.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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 designObservational
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

Citations4
Published2020
Admission routes3
Has abstractyes

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Same venueCanadian Geographies / Géographies canadiennesSame topicIndigenous Health, Education, and RightsFrench-language works237,207