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Record W2774401058 · doi:10.1177/1471301217739737

Global perspectives on dementia and art: An international discussion about changing public health policy

2017· article· en· W2774401058 on OpenAlexaff
Peter J. Whitehouse, Trish Vella-Burrows, Duncan Stephenson

Bibliographic record

VenueDementia · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsUniversity of Toronto
FundersRoyal Society
KeywordsPublic healthFraming (construction)DementiaPoliticsPublic relationsPolitical sciencePublic policyHealth policyCommunity engagementSociologyMedicineNursing

Abstract

fetched live from OpenAlex

In an era of global environmental deterioration and income inequity, public health faces many challenges, including the growing number of individuals, especially older people, with chronic diseases. Dementia is increasingly being seen not just as a biomedical problem to solve but as a public and community challenge to address more broadly. Concepts like prevention, brain health, and quality of life/well-being are receiving more attention. The engagement of community in addressing these challenges is being seen as critical to successful social adaptation. Arts programs are reinvigorating cultural responses to the growing number of older people with cognitive challenges. The humanities offer ways of understanding the power of words and stories in public discourse and a critical lens though which to view political and economic influences. In this paper, we report on a panel held in London on the occasion of the conference at the Royal Society for Public Health in March, 2017, in which the authors presented. Key issues discussed included problem framing, the nature of evidence, the politics of power and influence, and the development of effective interventions. In this paper, we review the rejection of two policies, one on dementia and one on the arts and humanities in public health, by the American Public Health Association; the emergence of policies in the UK; and some of the state of the art practices, particularly in training, again focusing on the UK.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.900
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.054
GPT teacher head0.354
Teacher spread0.300 · 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 designNot applicable
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

Citations5
Published2017
Admission routes1
Has abstractyes

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