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Record W1914415712 · doi:10.7202/1032387ar

La personnalisation des services de santé mentale : une voie d’avenir

2015· article· fr· W1914415712 on OpenAlexaffvenueabout
Paul Morin, Pierre-Luc Bossé, Sébastien Carrier, Suzanne Garon, Annie Lambert

Bibliographic record

VenueSanté mentale au Québec · 2015
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsHealth and Social Services Centre University Institute of Geriatrics of SherbrookeUniversité de Sherbrooke
Fundersnot available
KeywordsPsychologySociologyHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

La personnalisation des services de santé mentale est indissociable d’un processus qui vise à penser et à circonscrire les effets recherchés par les personnes comme des aspirations légitimes, élargissant ainsi leurs possibilités de choix et de contrôle. Dans un premier temps, nous démontrerons que cette visée de personnalisation ne peut être détachée d’un contexte général et de contextes spécifiques, qu’ils soient français, anglo-saxons, québécois ou autres. L’approche narrative constitue à cet égard un apport essentiel favorisant la prise en compte des liens de codétermination entre façons de savoir et formes de pouvoir. Par la suite, les politiques, pratiques et recherches au Royaume-Uni en regard de la personnalisation seront mises en évidence avec un accent particulier sur les approches et outils d’intervention dans le champ de la santé mentale. C’est dans ce cadre que nous présenterons le « Projet Baromètre » dont l’une des retombées est la conceptualisation d’un outil d’intervention et d’évaluation, interactif et accessible via le web, qui met en évidence les forces et les progrès de la personne dans sa communauté.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.387
Teacher spread0.338 · 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; both teacher heads agree on what is shown here.

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
Published2015
Admission routes3
Has abstractyes

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