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Record W52770495 · doi:10.1177/175797590601300402

Maintaining Population Health in a Period of Welfare State Decline: Political Economy as the Missing Dimension in Health Promotion Theory and Practice

2006· article· en· W52770495 on OpenAlexafffund
Dennis Raphael, Toba Bryant

Bibliographic record

VenuePromotion & Education · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversity of TorontoYork University
FundersHealth Canada
KeywordsDimension (graph theory)Period (music)WelfareWelfare stateState (computer science)PoliticsHealth promotionPromotion (chess)PopulationEconomicsPolitical scienceEconomic growthMedicineEnvironmental healthMarket economyHealth careLawMathematics

Abstract

fetched live from OpenAlex

There is increasing recognition in the health promotion and population health fields that the primary determinants of health lay outside the health care and behavioural risk arenas. Many of these factors involve public policy decisions made by governments that influence the distribution of income, degree of social security, and quality and availability of education, food, and housing, among others. These non-medical and non-lifestyle factors have come to be known as the social determinants of health. In many nations--and this is especially the case in North America--recent policy decisions are undermining these social determinants of health. A political economy analysis of the forces supporting as well as threatening the welfare state is offered as a means of both understanding these policy decisions and advancing the health promotion and population health agendas. The building blocks of social democracies--the political systems that seem most amenable to securing the social determinants of health--are identified as key to promoting health. Health promoters and population health researchers need to "get political" and recognize the importance of political and social action in support of health.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptualhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.019
metaresearch head score (Gemma)0.016
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0070.058
Scholarly communication0.0130.011
Open science0.0010.006
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0030.000

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 head0.030
GPT teacher head0.406
Teacher spread0.376 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical · Commentary

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

Citations59
Published2006
Admission routes2
Has abstractyes

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