Integrating Public Health Policy, Practice, Evaluation, Surveillance, and Research: The School Health Action Planning and Evaluation System
Bibliographic record
Abstract
The Canadian Cancer Society and the National Cancer Institute of Canada have charged their Centre for Behavioral Research and Program Evaluation with contributing to the development of the country's systemic capacity to link research, policy, and practice related to population-level interventions. Local data collection and feedback systems are integral to this capacity. Canada's School Health Action Planning and Evaluation System (SHAPES) allows data to be collected from all of a school's students, and these data are used to produce computer-generated school "health profiles." SHAPES is being used for intervention planning, evaluation, surveillance, and research across Canada. Strong demand and multipartner investment suggest that SHAPES is adding value in all of these domains. Such systems can contribute substantially to evidence-informed public health practice, public engagement, participatory action research, and relevant, timely population intervention research.
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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 | 0.446 | 0.290 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.017 | 0.022 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.028 | 0.014 |
| Open science | 0.006 | 0.027 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".