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Record W2164523738 · doi:10.1177/1524839906289342

Promoting Health and Innovative Health Promotion Practice Through a Community Arts Centre

2007· article· en· W2164523738 on OpenAlexaff
Arlene J. Carson, Neena L. Chappell, Carolyn J. Knight

Bibliographic record

VenueHealth Promotion Practice · 2007
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsQUAD Engineering (Canada)University of Victoria
Fundersnot available
KeywordsHealth promotionThe artsCommunity healthCommunity-based participatory researchMedicineNursingPublic relationsSociologyPublic healthMedical educationPolitical scienceParticipatory action research

Abstract

fetched live from OpenAlex

The salubrious effects of participation in and exposure to the arts are well documented. This paper describes the development of a unique arts centre established in a disadvantaged urban school setting as part of a larger community-based health promotion research project. The discussion highlights how community-based arts programming may impact health not only through positive effects on "upstream" non-medical health determinants, particularly aspects of social support, but also through its ability to facilitate the more traditional health-promotion initiatives of the larger parent project. Also discussed is this centre's potential to act as a catalyst to achieve the overarching project goal of enhanced community health by building constitutive capacity around positive aspects of the community, rather than focusing on capacity only as an instrumental resource to solve social or health problems. Greater incorporation of the arts within health-promotion projects offers potential to enhance both health promotion practice and outcomes.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.003
Scholarly communication0.0040.001
Open science0.0020.009
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.243
GPT teacher head0.539
Teacher spread0.296 · 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

Citations22
Published2007
Admission routes1
Has abstractyes

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