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Record W3042964924 · doi:10.7870/cjcmh-2020-005

Transition Space at the Museum: A Community Arts-Based Group Program to Foster the Psychosocial Rehabilitation of Youths with Mental Health Problems

2020· article· en· W3042964924 on OpenAlexaffvenue
Kim Archambault, Élyse Porter-Vignola, Marilyn Lajeunesse, Victor Debroux-Leduc, Rocio Macabena Perez, Patricia Garel

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité du Québec à MontréalUniversité de Montréal
Fundersnot available
KeywordsPsychosocialRehabilitationMental healthPsychologySpace (punctuation)The artsApplied psychologyQualitative researchCommunity integrationClinical psychologyMedical educationPsychiatryMedicinePhysical therapySociologyComputer science

Abstract

fetched live from OpenAlex

Transition Space at the Museum is a community arts-based group program aiming to foster the psychosocial rehabilitation of adolescents and young adults with mental health problems. In this pilot evaluation, we assessed the preliminary effectiveness of the program at improving participants’ well-being and social functioning. Following a mixed-methods, single-group, repeated-measures design, we collected data before, during, and after program from participants, clinicians, and close relatives using standardized questionnaires and semi-structured interviews. We found converging quantitative and qualitative results supporting the safety and potential of the program to improve the way participants feel and function socially in the short term.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.003
Research integrity0.0010.001
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 head0.085
GPT teacher head0.329
Teacher spread0.243 · 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

Citations6
Published2020
Admission routes2
Has abstractyes

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