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Record W2166192258 · doi:10.1093/heapro/dar063

Health promotion, the Ottawa Charter and 'developing personal skills': a compact history of 25 years

2011· article· en· W2166192258 on OpenAlexaboutno aff
David V. McQueen, Ligia de Salazar

Bibliographic record

VenueHealth Promotion International · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsnot available
Fundersnot available
KeywordsCharterHealth promotionPromotion (chess)Political scienceMedicinePsychologyPublic healthNursing

Abstract

fetched live from OpenAlex

The challenge of understanding what has happened in the 25 years since the Ottawa Charter would be difficult enough if there had been no Charter. However, our task is to interpret to what extent the Charter has influenced the world of health promotion as it is today. The task here is to consider what has happened regarding one action component of the Charter, notably developing personal skills. In taking only one of the five components, we are deconstructing the holistic approach that was implied in the Ottawa Charter and it is somewhat strange to isolate this action area from the others, and perhaps outside the 'spirit' of the Charter. Nonetheless, the approach will be to interpret this area broadly while still being restrictive and not venturing into discussions of the other action areas except where the connection is so strong that to isolate personal skills from the other area would be unproductive. The Ottawa Charter brought to the table, for health promotion and education, a growing recognition that health was a broad concept in its own right. It made explicit that ties to disease approaches were highly related to health education and promotion, but that health promotion had to go well beyond a narrow interpretation of the field. It recognized that active participation by people, to directly affect their health and the broader determinants of it, was paramount.

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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.593
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.120
GPT teacher head0.431
Teacher spread0.312 · 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 teacher head, not a consensus.

Study designObservational
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

Citations36
Published2011
Admission routes1
Has abstractyes

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