Examining school-level implementation of British Columbia, Canada’s school food and beverage sales policy: a realist evaluation
Bibliographic record
Abstract
OBJECTIVE: To identify key school-level contexts and mechanisms associated with implementing a provincial school food and beverage policy. DESIGN: Realist evaluation. Data collection included semi-structured interviews (n 23), structured questionnaires (n 62), participant observation at public events (n 3) and scans of school, school district and health authority websites (n 67). The realist heuristic, context + mechanism → outcome configuration was used to conduct the analysis. SETTING: Public schools in five British Columbia (BC), Canada school districts. PARTICIPANTS: Provincial and regional health and education staff, private food vendors and school-level stakeholders. RESULTS: We identified four mechanisms influencing the implementation of BC's school food and beverage sales policy. First, the mandatory nature of the policy triggered some actors' implementation efforts, influenced by their normative acceptance of the educational governance system. Second, some expected implementers had an opposite response to the mandate where they ignored or 'skirted' the policy, influenced by values and beliefs about the role of government and school food. A third mechanism related to economics demonstrated ways vendors' responses to school demand for compliance with nutritional Guidelines were mediated by beliefs about food preferences of children, health and food. The last mechanism demonstrated how resource constraints and lack of capacity led otherwise motivated stakeholders to not implement the mandatory policy. CONCLUSION: Implementation of the food and beverage sales policy at the school level is shaped by interactions between administrators, staff, parent volunteers and vendors with contextual factors such as varied motivations, responsibilities and capacities.
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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 | 0.051 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".