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Record W2117588823 · doi:10.1093/heapro/dai030

Healthy settings: challenges to generating evidence of effectiveness

2005· article· en· W2117588823 on OpenAlex
Mark Dooris

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueHealth Promotion International · 2005
Typearticle
Languageen
FieldHealth Professions
TopicSchool Health and Nursing Education
Canadian institutionsnot available
Fundersnot available
KeywordsCharterPerspective (graphical)Value (mathematics)Promotion (chess)Diversity (politics)Management scienceKnowledge managementPublic relationsSociologyProcess managementPsychologyComputer sciencePolitical scienceBusinessEconomics

Abstract

fetched live from OpenAlex

This paper starts by briefly reviewing the history, theory and practice of the settings approach to promoting public health--highlighting its ecological perspective, its understanding of settings as dynamic open systems and its primary focus on whole system organization development and change. It goes on to outline perceived benefits and consider why, almost 20 years after the Ottawa Charter advocated the approach, there remains a relatively poorly developed evidence base of effectiveness. Identifying three key challenges--relating to the construction of the evidence base for health promotion, the diversity of conceptual understandings and real-life practice and the complexity of evaluating ecological whole system approaches--it suggests that these have resulted in an ongoing tendency to evaluate only discrete projects in settings, thus failing to capture the 'added value' of whole system working. It concludes by exploring the potential value of theory-based evaluation and identifying key issues that will need to be addressed in moving forward--funding evaluation within and across settings; ensuring links between evidence, policy and practice; and clarifying and articulating the theories that underpin the settings approach generically and inform the approach as applied within particular settings.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.190
GPT teacher head0.535
Teacher spread0.345 · 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