Lier parcours de vie et trajectoires de services pour améliorer la qualité des systèmes de santé
Bibliographic record
Abstract
Un peu partout dans le monde, les efforts sont nombreux pour augmenter l’efficacité de l’organisation des systèmes de santé. Dans cette perspective, les appels à la collaboration interprofessionnelle et intersectorielle se multiplient et génèrent un grand nombre d’innovations visant à mieux prendre en considération les trajectoires de soins. L’article présente dans un premier temps des principes généraux qui orientent les efforts d’innovation en matière d’actualisation des systèmes de santé. Puis il expose les potentiels d’amélioration des services de santé qu’une telle perspective contient en les concevant sous l’angle des parcours de vie. Enfin, il conclut sur quelques pistes d’action afin de lier parcours de vie et trajectoires de services en fonction d’une philosophie organisationnelle ancrant les services de santé dans une approche véritablement singularisante des soins.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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 teacher head, 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".