Stratégies d’intégration des services en réseau, régulation et moteurs d’implantation de changement
Bibliographic record
Abstract
Les réseaux intégrés de services sont présentés comme l'une des principales voies de solutions pour accroître l'efficience, la pertinence et la cohérence du système de santé dans le contexte actuel d'augmentation de la demande et de contraintes budgétaires. Dans le domaine de la santé mentale, l'intégration s'inscrit aussi dans une tentative de répondre aux besoins multiples de la population cible, plus spécifiquement les personnes souffrant de troubles mentaux graves. Cet article décrit les balises du concept de réseau intégré de services en santé mentale, les principales stratégies qui en favorisent le développement et les modèles de régulation qui permettent leur élaboration. L'article aborde aussi les difficultés et les enjeux de ce mode d'organisation et plus particulièrement les défis liés à l'implantation de changement et de transformation des systèmes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".