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Record W2944135991 · doi:10.1093/heapro/daz039

Language and framing as determinants of the predominance of behavioural health promotion: an Australian view

2019· article· en· W2944135991 on OpenAlexaboutno aff
Denise Fry

Bibliographic record

VenueHealth Promotion International · 2019
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsHealth promotionCharterFraming (construction)Public relationsCognitive reframingDeclarationHealth policySociologyPolitical scienceMedicinePsychologyPublic healthSocial psychologyNursingEngineering

Abstract

fetched live from OpenAlex

The language used in health promotion warrants attention as it shapes how health promotion is understood, constraining or opening up possibilities for action. The 2016 Shanghai Declaration and the 1986 Ottawa Charter for Health Promotion call for comprehensive approaches which include policy and environmental changes. Yet many health promotion programmes in Australia continue to focus on informational and/or behavioural strategies, and there is a contemporary tendency for such programmes to be described as 'sending messages'. This paper uses frame analysis to discuss the role of language, and specifically language that frames health promotion as sending messages, in contributing to and reinforcing the predominance of informational and/or behavioural strategies. It argues such 'message' language helps to set a pattern in which informational and/or behavioural strategies are assumed to be the primary goal and extent of health promotion; rather than one component of a comprehensive, multi-strategic approach. It discusses how frames can be 'taken for granted' and ways in which such frames can be challenged and broadened. It argues that the message frame and associated behavioural framings set narrow boundaries for health promotion, contributing to the continuation of health inequities. These frames can also displace the language of the Ottawa Charter, which has capacity to reframe health issues socio-ecologically and include collective strategies. The paper concludes that a first step (of the many needed) towards applying the Charter's approach and multi-level, multi-strategic framework is to use the innovative vocabulary it offers. The words matter.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.805

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.139
GPT teacher head0.482
Teacher spread0.342 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations17
Published2019
Admission routes1
Has abstractyes

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