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Record W2544054442

The Social Determinants of Health: Defining a Research Agenda for Canada’s Urban Aboriginal Population

2010· article· en· W2544054442 on OpenAlexaboutno aff
Chantelle Richmond, Katie Big-Canoe

Bibliographic record

VenueScholarship@Western (Western University) · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsCensusUrbanizationMetropolitan areaGeographySocial determinants of healthPopulationContext (archaeology)Population healthHealth equityEconomic growthInequalityPolitical scienceSocioeconomicsSociologyHealth careDemographyEconomics
DOInot available

Abstract

fetched live from OpenAlex

In the past few decades, the health of Aboriginal peoples has become a priority among Canadian health researchers (Adelson 2005; Reading and Nowgesic 2002). To date, however, the bulk of this literature has been overrepresented by research seeking to establish rates of disease and mortality, with considerably less attention paid to the social and economic processes underlying them. Indeed, while it is vital to characterize the health inequalities borne by Aboriginal Canadians—as they are vast, and, in some cases, growing—the fact remains that these observations have not transformed into a common understanding of the underlying causes of inequality, such as the important role played by the social determinants of health (SDOH) (Loppie and Wien 2009; Richmond and Ross 2009). What’s more, this body of research has tended to concentrate its efforts on segments of the Aboriginal population living on-reserve and in rural and remote areas, with appreciably less regard for patterns of urbanization that now characterize vast segments of the Aboriginal population. As of the last census count, 54% of the Aboriginal population lived in an urban centre, which includes large cities, or Census Metropolitan Areas (CMAs), and smaller urban centres. This was an increase from 50% in 1996 (Statistics Canada 2006). In spite of the recognition that increasing numbers of Aboriginal people now live in urban centres, and the challenges that this pattern of urbanization poses for Aboriginal health policy and program development, little substantive research has explored SDOH within the urban Aboriginal context. In this chapter, we examine if the current base of research on the social determinants of Aboriginal health reflects the population and geographic diversity of Canada’s increasingly urbanized population. We also describe what this base of literature looks like; specifically, we illustrate which SDOH have been examined, and through which methods this research is occurring. As an introduction, we begin with a discussion of the SDOH, and we demonstrate why the urban Aboriginal context is deserving of such research. We then describe the methodology we undertook in this review, followed by a discussion of our results. We conclude with a description of areas in which research is most urgently needed.

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)0.039
metaresearch head score (Gemma)0.028
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.762
Threshold uncertainty score0.883

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.028
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0120.015
Science and technology studies0.0320.023
Scholarly communication0.0270.015
Open science0.0080.017
Research integrity0.0140.021
Insufficient payload (model declined to judge)0.0080.001

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 head0.218
GPT teacher head0.475
Teacher spread0.257 · 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
GenreMethods

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
Published2010
Admission routes1
Has abstractyes

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