MétaCan
Menu
← Back to cohort
Record W4409990983 · doi:10.32920/28912442.v1

Exploring the Impacts of Arts Participation on Healthy Ageing

2025· preprint· en· W4409990983 on OpenAlexfundaboutno aff
Temba Middelmann

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
FundersCanada Excellence Research Chairs, Government of CanadaGovernment of Canada
KeywordsThe artsAgeingHealthy ageingPsychologyVisual artsArtMedicine

Abstract

fetched live from OpenAlex

This short report provides a synopsis of the research conducted on a series of art classes for older adults in Rexdale, Toronto. The classes were funded by a New Horizons grant, arranged by Rexdale Community Health Centre (RCHC) in partnership with Franklin Carmichael Art Group (FCAG), who hosted the classes. The research was funded under the Canada Excellence Research Chair in Health Equity & Community Wellbeing. The researcher, Dr. Temba Middelmann, used a series of focus groups, one-to-one interviews, and observations at classes and the exhibition, speaking to 41 participants, 4 staff members and 6 teachers. The focus was on participant experiences in relation to personal, collective and contextual factors affecting health and wellbeing. The research found multiple benefits that connected social, artistic, and psychological factors. These preliminary findings suggest the multi-levelled power of art to assist directly with difficult mental health concerns, simultaneously helping to address social isolation and loneliness, with various positive impacts on health and wellbeing.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0000.004
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.357
GPT teacher head0.380
Teacher spread0.024 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same topicArt Therapy and Mental Health→French-language works237,207→