How Can Both the Intervention and Its Evaluation Fulfill Health Promotion Principles? An Example From a Professional Development Program
Bibliographic record
Abstract
The emergence over the past 20 years of health promotion discourse poses a specific challenge to public health professionals, who must come to terms with new roles and new intervention strategies. Professional development is, among other things, a lever for action to be emphasized in order to meet these challenges. To respond to the specific training needs of public health professionals, a team from the Direction de santé publique de Montréal (Montreal Public Health Department) in Quebec, Canada, established in 2009 the Health Promotion Laboratory, an innovative professional development project. An evaluative component, which supports the project's implementation by providing feedback, is also integrated into the project. This article seeks to demonstrate that it is possible to integrate the basic principles of health promotion into a professional development program and its evaluation. To this end, it presents an analytical reading of both the intervention and its evaluation component in light of the cardinal principles in this field. Initiatives such as the Health Promotion Laboratory and its evaluation are essential to consolidate the foundations of professional development and its assessment by concretely integrating health promotion discourse into these practices.
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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 | 0.198 | 0.179 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.031 |
| Scholarly communication | 0.017 | 0.011 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".