Vers un modèle d'évaluation de l'efficacité des interventions communautaires en promotion de la santé : compte-rendu de quelques développements Nord-américains récents1
Bibliographic record
Abstract
The current systematic reviews to assess the effectiveness of community-based health promotion projects, be they quantitative (numerical meta-analyses) or qualitative (narrative reviews), both have significant drawbacks. Out of the work conducted for two initiatives, the developments for the Global programme on health promotion effectiveness carried at by the North American Region out of the International Union of Health Promotion and Education (IUHPE), as well as the work conducted for the ECIP (effectiveness of community interventions project) of Health Canada, a new way to approach the issue of effectiveness is proposed. Based on a «realist synthesis» epistemological position, this approach has led us to the first formulation of a framework aiming at identifying the mechanisms that explain why local programs are successful.
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 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 | 0.159 | 0.205 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".