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Record W2106889271 · doi:10.1093/heapro/dan002

Health promotion policy in Canada: lessons forgotten, lessons still to learn

2008· article· en· W2106889271 on OpenAlexaffabout
Jacqueline Low, Luc Thériault

Bibliographic record

VenueHealth Promotion International · 2008
Typearticle
Languageen
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsHealth promotionPolitical sciencePromotion (chess)Public relationsHealth policyEconomic growthNursingPublic administrationMedicinePublic healthLawPoliticsEconomics

Abstract

fetched live from OpenAlex

In this paper, we analyse Canadian health promotion discourse past and present, in the context of selected federal and provincial government policy initiatives. Principally, we examine the health promotion discourse articulated in A New Perspective on the Health of Canadians, Achieving Health for All: A Framework for Health Promotion, the Ottawa Charter for Health Promotion, Improving the Health of Canadians, and Canada Health Action: Building on the Legacy-Volume II-Synthesis reports and Issue papers. We argue that the health promotion lessons of the past 30 years contained within these reports have largely been forgotten, overlooked or disregarded in policy implementation. We conclude, as have many before us, that successful health promotion policy needs to reflect a collectivist rather than individualist ethos where responsibility for the health of Canadians is concerned. Moreover, it needs to be one that addresses the social determinants of health, including inequity, via the coordination of healthy public policy.

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)0.022
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.722
Threshold uncertainty score0.838

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.011
Science and technology studies0.0210.020
Scholarly communication0.0220.007
Open science0.0040.005
Research integrity0.0070.010
Insufficient payload (model declined to judge)0.0040.000

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 head0.183
GPT teacher head0.510
Teacher spread0.327 · 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 designQualitative
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

Citations39
Published2008
Admission routes2
Has abstractyes

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