L'accompagnement pour améliorer les pratiques professionnelles en santé publique
Bibliographic record
Abstract
Accompaniment (professional support) is increasingly used to support improvement of public health practices. In the field of education, the term accompaniment is at the heart of a structured teaching approach. In public health, the term is commonly used, but has not been clearly defined, which means that proposals are often not sufficient to support real changes in practice. The present article proposes a reflection on accompaniment in the field of public health inspired by progress in the education sector. The actions of managing, guiding and supporting are derived from the action of accompaniment and are illustrated by the example of the Health Promotion Laboratory of the Montréal Public Health Department. Accompaniment requires knowledge that is acquired with practice, hence the importance of strategically targeting a project which could benefit from such an approach and supporting the development of professional skills. The improvement of public health professional practices and public health management, necessary for adaptation of the health system, is dependent on development of an expertise in accompaniment of the processes of change.
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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 | 0.029 | 0.033 |
| 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 | 0.010 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".