MétaCan
Menu
Back to cohort
Record W2059877245 · doi:10.1177/1471301215580895

Presence redefined: The reciprocal nature of engagement between elder-clowns and persons with dementia

2015· article· en· W2059877245 on OpenAlexafffundabout
Pia Kontos, Karen‐Lee Miller, Gail J. Mitchell, Jan Stirling-Twist

Bibliographic record

VenueDementia · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsYork UniversityPublic Health OntarioToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsDementiaPsychologyReciprocalEmpathyDanceEmbodied cognitionPerspective (graphical)The artsEthnographyImprovisationSocial psychologySociologyDiseaseMedicineVisual artsArt

Abstract

fetched live from OpenAlex

Elder-clowns are a recent innovation in arts-based approaches to person-centred dementia care. They use improvisation, humour, and empathy, as well as song, dance, and music. We examined elder-clown practice and techniques through a 12-week programme with 23 long-term care residents with moderate to severe dementia in Ontario, Canada. Analysis was based on qualitative interviews and ethnographic observations of video-recorded clown-resident interactions and practice reflections. Findings highlight the reciprocal nature of clown-resident engagement and the capacity of residents to initiate as well as respond to verbal and embodied engagement. Termed relational presence, this was achieved and experienced through affective relationality, reciprocal playfulness, and coconstructed imagination. These results highlight the often overlooked capacity of individuals living with dementia to be deliberately funny, playful, and imaginative. Relational presence offers an important perspective with which to rethink care relationships between individuals living with dementia and long-term care staff.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.014
Scholarly communication0.0050.003
Open science0.0010.010
Research integrity0.0010.001
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 head0.062
GPT teacher head0.278
Teacher spread0.216 · 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 source (direct Gemma or distilled Codex), 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

Citations97
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueDementiaSame topicArt Therapy and Mental HealthFrench-language works237,207