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Record W4407908702 · doi:10.7202/1115960ar

La collaboration interprofessionnelle comme enjeu de la qualité des services en santé mentale : le cas des travailleuses sociales et des médecins psychiatres

2024· article· fr· W4407908702 on OpenAlexaffabout
Émmanuelle Khoury, Henri Dorvil

Bibliographic record

VenueIntervention · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsUniversité du Québec à MontréalUniversité de MontréalMinistère de l’Emploi et de la Solidarité Sociale (Québec)
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Depuis le premier Plan d’action en santé mentale au Québec (MSSS, 2005), le ministère de la Santé et des Services sociaux privilégie des soins collaboratifs, un modèle de plus en plus souvent adopté dans les provinces canadiennes depuis 2011 (Kates et al., 2023). Bien que la collaboration interprofessionnelle soit reconnue comme un moyen de fournir des soins de qualité (McNeil et al., 2013) et de protéger le bien-être des patients, peu de recherches explorent la dynamique entre le travail social et le traitement médical en santé mentale. Quelles possibilités de collaboration existent entre ces professions? Comment leurs expertises en évaluation, planification et prise de décision partagée peuvent-elles améliorer les résultats et la qualité des soins? Cet article discute des stratégies susceptibles de contribuer à co-construire des territoires partagés entre ces professions. Nous soutenons que pour y parvenir, il est essentiel de remettre en question les rapports de pouvoir entre les groupes professionnels, d’encourager la créativité et de reconnaître les différents savoirs professionnels.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.070
GPT teacher head0.457
Teacher spread0.387 · 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 teacher head, 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

Citations0
Published2024
Admission routes2
Has abstractyes

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