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Record W2724139951 · doi:10.1093/geroni/igx004.300

LIBERATING THE ARTS FROM THE THERAPY CULTURE IN DEMENTIA CARE

2017· article· en· W2724139951 on OpenAlexaff
Sherry L. Dupuis, Pia Kontos, Gail J. Mitchell, Christine Jonas‐Simpson, Julia Gray

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsUniversity of TorontoYork UniversityToronto Rehabilitation InstituteUniversity of Waterloo
Fundersnot available
KeywordsThe artsTransformative learningDementiaFlourishingPsychologySociologyPsychotherapistMedicinePedagogyVisual artsDiseaseArt

Abstract

fetched live from OpenAlex

Influenced by biomedical/behavioural models, the arts within dementia care are valued primarily as therapy; arts-based interventions are provided as non-pharmacological means to improve functioning of “patients” and treat misunderstood “behaviours”. Informed by theorizing within liberation arts and critical theory, this presentation aims to liberate the arts in dementia care from the therapy culture and demonstrate the power of the arts to address broader relational and social justice issues connected to aging and elder care. We draw on interview, focus group, and video data from four qualitative research projects using theatre, visual arts, an arts-based learning academy, and elder clowning. Findings demonstrate how the arts: challenge dominant discourses and problematize oppressive policies and practices; ignite personal discovery, growth, and transformation; and nurture relational citizenship. The arts create transformative spaces for relational flourishing and prompt the social change needed to reduce the harm and suffering experienced by older adults living with dementia.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.962

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 studies0.0010.000
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 head0.072
GPT teacher head0.324
Teacher spread0.252 · 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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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