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Record W4416929279 · doi:10.7870/cjcmh-2025-013

Les ateliers collectifs inspirés des TCC dans les dispositifs d’emploi accompagné français : résultats d’une étude quasi expérimentale

2025· article· en· W4416929279 on OpenAlexaffvenueabout
Simon Roussey, Manon Coulange, Bernard Pachoud, Charles‐Édouard Giguère, Tania Lecomte, Marc Corbière

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2025
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsUniversité du Québec à MontréalUniversité de MontréalInstitut universitaire en santé mentale de MontréalInstitut Universitaire en Santé Mentale de Québec
Fundersnot available
KeywordsPsychological interventionPoison controlWindshieldWork (physics)

Abstract

fetched live from OpenAlex

La performance de l’emploi accompagné peut être améliorée en combinant l’accompagnement personnalisé à des interventions collectives (de groupe) inspirées des TCC. L’objectif de cette expérimentation était de démontrer la valeur ajoutée, en France, de ce type d’intervention. L’expérimentation a été menée selon une approche mixte, associant une évaluation quasi-expérimentale longitudinale et qualitative. Une amélioration des taux d’accès et de maintien en emploi a été constatée. On observe également une réduction importante des symptômes anxieux et dépressifs, plus rapide pour les personnes du groupe expérimental. Ce type d’intervention de groupe, validé au Canada, mérite d’être déployé à plus grande échelle en France.

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)0.010
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.260

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.115
GPT teacher head0.464
Teacher spread0.349 · 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 designNon-randomized trial
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 routes3
Has abstractyes

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