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Addressing social and gender inequalities in health among seniors in Canada

2003· review· en· W2127624755 on OpenAlexaffabout
Louise Plouffe

Bibliographic record

VenueCadernos de Saúde Pública · 2003
Typereview
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsHealth Canada
Fundersnot available
KeywordsPovertySocioeconomic statusGovernment (linguistics)GerontologyHealth equitySocial securitySocial determinants of healthPublic healthPopulationHealth careInequalityEconomic growthDemographic economicsPolitical sciencePsychologyEnvironmental healthMedicineEconomicsNursing

Abstract

fetched live from OpenAlex

Although canadian seniors enjoy economic security and good health and have made substantial gains in recent decades, this well-being is not equally shared among socioeconomic groups and between men and women. As for younger age groups, income predicts health status in later life, but less powerfully. Potential alternative explanations include an overriding influence of the aging process, the subjective effects of income loss at retirement and the attenuation of the poverty gap owing to public retirement income. Older women are more likely to age in poverty than men, to live alone and to depend on inadequately resourced chronic health care and social services. These differences will hold as well for the next cohort of seniors in Canada. Addressing these disparities in health requires a comprehensive, multisectoral approach to health that is embodied in Canada's population health model. Application of this model to reduce these disparities is described, drawing upon the key strategies of the population health approach, recent federal government initiatives and actions recommended to the government by federal commissions.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.148
Threshold uncertainty score0.298

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.285
GPT teacher head0.450
Teacher spread0.165 · 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

Citations32
Published2003
Admission routes2
Has abstractyes

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