Understanding the Environment for Health-Promoting Schools Policies in Nova Scotia: A Comprehensive Scan at the Provincial and Regional School Level
Bibliographic record
Abstract
The World Health Organization has identified the school community as a key setting for health promotion efforts, laying out its priorities in the Health-Promoting Schools (HPS) framework. This framework offers a comprehensive approach that has been adopted in countries around the globe, with defining characteristics focused around the school curriculum and environment. Nova Scotia (NS) adopted the HPS framework at a provincial level in 2005, but it has been variably implemented. We aimed to identify, categorize, and broadly describe the environment for HPS policies in NS. Four iterative steps were employed: (1) a scan of government and regional school websites to identify publicly available policies; (2) consultations with provincial departments with respect to policy relevance and scope; (3) cross-comparison of policies by two reviewers; (4) compilation of policies into an online database. Seventy policies at the provincial level and 509 policies across eight public school regions were identified. Policies focusing on a 'safe school environment' were most common; those addressing mental health and well-being, physical activity, nutrition and healthy eating, and substance use were among those least commonly identified. This scan provides a comprehensive overview of HPS-relevant policies in NS, along with relative proportions and growth over time. Our findings suggest areas of policy action and inaction that may help or hinder the implementation of HPS principles and values.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.011 | 0.020 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".