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Record W1585146851 · doi:10.7202/014837ar

Créer des contextes de coopération pour sortir des culs-de-sac thérapeutiques

2007· article· fr· W1585146851 on OpenAlexaffvenue
Suzanne Lamarre

Bibliographic record

VenueSanté mentale au Québec · 2007
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsSt Mary's Hospital Centre
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Cet article vise à : 1) décrire la gestion des problèmes de santé mentale selon les deux modèles opposés ici et qui se différencient lors des tensions, le modèle de la coopération et le modèle traditionnel médical ; 2) illustrer à l’aide d’exemples cliniques ces différences essentielles ; et 3) proposer quelques réflexions sur les obstacles à la coopération en raison des attitudes protectionnistes du modèle traditionnel médical qui s’accentuent lors des crises. S’en tenir aux traitements des pathologies en ignorant la nature des contextes relationnels, comme le veut le modèle traditionnel médical, risque de conduire les acteurs dans des culs-de-sac thérapeutiques dont le plus fréquent est celui la psychiatrisation. L’auteure propose un modèle d’intervention qu’elle intitule les 4Rs pour installer un contexte de coopération afin de sortir des culs-de-sac thérapeutiques.

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)0.015
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.141
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0190.026
Scholarly communication0.0100.006
Open science0.0020.011
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0090.001

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 head0.049
GPT teacher head0.412
Teacher spread0.362 · 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 designNot applicable
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
Published2007
Admission routes2
Has abstractyes

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