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Record W1981765914 · doi:10.1108/09654280310472397

Bridging the gap between knowledge and action on the societal determinants of cardiovascular disease: how one Canadian community effort hit – and hurdled – the lifestyle wall

2003· article· en· W1981765914 on OpenAlexaffabout
Dennis Raphael

Bibliographic record

VenueHealth Education · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsYork University
Fundersnot available
KeywordsRedressPublic healthSocial determinants of healthDiseasePublic relationsPolitical scienceAction (physics)Call to actionHealth policyHealth promotionHealth careEconomic growthGerontologyMedicineBusinessEconomicsNursing

Abstract

fetched live from OpenAlex

An expanding conceptual and research literature identifies cardiovascular disease (CVD) as the disease whose incidence varies most, according to income level. To date however, there has been virtually no public consideration in Canada of the role that societal factors play in its incidence. In an attempt to redress this gap, a community coalition brought together the latest research on the societal determinants of CVD. Barriers to public awareness and public policy action to address these societal determinants of health included the unwillingness of health care associations to consider societal determinants of health as relevant to their activities; general resistance by the media; and active attempts by governments of the day to shift focus away from societal determinants of health. Considering these barriers, university personnel involvement appears essential to any attempt to identify and address the societal determinants of CVD and other diseases.

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)0.028
metaresearch head score (Gemma)0.032
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 score0.106
Threshold uncertainty score0.771

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0240.022
Scholarly communication0.0130.007
Open science0.0030.011
Research integrity0.0070.013
Insufficient payload (model declined to judge)0.0050.000

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 head0.126
GPT teacher head0.386
Teacher spread0.260 · 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

Citations15
Published2003
Admission routes2
Has abstractyes

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