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Record W4414873467 · doi:10.1080/2997965x.2025.2562820

“Art is a means to freedom, without it I have nothing”: impacts of gifting art supplies to support holistic wellbeing for incarcerated people

2025· article· en· W4414873467 on OpenAlexfundaboutno aff
Kelsey Timler, Helen Brown

Bibliographic record

VenueJustice Opportunities and Rehabilitation · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsQualitative researchPrisonWork (physics)Government (linguistics)Action (physics)

Abstract

fetched live from OpenAlex

COVID-19 disproportionately impacted people in prison in Canada and around the world. In response, our team pivoted research funding to support a rapid response arts-based mental health intervention in British Columbia (BC) federal prisons. We gifted high quality art supplies and invited incarcerated artists to share their creativity and identity through art creation and sharing as mechanisms of community building. This paper presents findings from a survey conducted with incarcerated artists, enquiring about their experiences of incarceration during COVID-19, and the impacts of the arts-based mental health intervention. Impacts included feeling not forgotten, therapeutic opportunities through art creation, strengthened social connection, and feeling the simple yet radical idea of hope. Implications for research with incarcerated and criminalized peoples, arts-based practice across contexts, and art as a mechanism to support mental health and collective resilience are discussed.

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)0.004
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.007
Scholarly communication0.0030.001
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.059
GPT teacher head0.332
Teacher spread0.273 · 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

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