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Record W2144975299 · doi:10.1177/1757975913499034

Sur la contribution des personnes utilisatrices de services de santé mentale en tant que partenaires d’enseignement en psychiatrie

2013· article· fr· W2144975299 on OpenAlexaffabout
Jean‐François Pelletier, Anthony Gifuny, Luc Nicole, Gabrielle Labrie Racine, Julie Bordeleau, Michael Rowe

Bibliographic record

VenueGlobal Health Promotion · 2013
Typearticle
Languagefr
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversité de MontréalInstitut universitaire en santé mentale de MontréalInstitut Universitaire en Santé Mentale de Québec
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Le Collège royal des médecins et chirurgiens du Canada prévoit qu’au terme de leur formation, les résidents en psychiatrie pourront agir efficacement en tant que promoteurs de la santé. Ce commentaire présente une analyse d’entrevues réalisées dans le cadre d’un perfectionnement professionnel auprès d’experts mondialement reconnus du rétablissement en santé mentale. À la lumière de la Charte d’Ottawa pour la promotion de la santé, il en ressort que des personnes utilisatrices de services de santé mentale peuvent être de précieux partenaires d’enseignement à la fois en matière de promotion de la santé et de rétablissement. Le recours à des patients partenaires d’enseignement en psychiatrie peut également représenter une stratégie de lutte à la stigmatisation et aux préjugés en favorisant davantage de réciprocité entre les professionnels et les personnes traitées.

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)0.007
metaresearch head score (Gemma)0.025
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 score0.347
Threshold uncertainty score0.690

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0050.004
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.040
GPT teacher head0.384
Teacher spread0.344 · 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

Citations5
Published2013
Admission routes2
Has abstractyes

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