Track C2: Workshop: Health economic evaluation of infectious disease control
Bibliographic record
Abstract
ResultsQuebec's publicly funded public health directorates forged a coalition to pool their resources to implement a provincewide advocacy strategy.The strategy aimed to address the concerns raised by journalists, members of the National Assembly, and the business sector about the potential impacts of the bill on Quebec's economy as well as the challenges made by the tobacco manufacturers.The coalition's resources provided the promoters of the bill with a dedicated policy analysis capacity which enabled them to better grasp the opportunities at hand and allowed for swift and effective countermeasures towards the threats to the bill.The steadfastness and persistence of the coalition members wasere rooted in a set of mechanisms protecting them from possible backlash.Conclusions Building a permanent policy analysis capacity within public health systems is critical for seizing upcoming opportunities to influence the course of policy making.This study shows that policy advocacy can be performed even in the face of powerful opponents and without jeopardizing the agencies delivering public health services and programmes.Additional theoretically driven health promotion policy research is needed to improve advocacy strategies for healthy public policy.
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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 | 0.028 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.031 | 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".