District-level implementation of British Columbia’s school food and beverage sales policy: a realist evaluation exploring intervention mechanisms in urban and rural contexts
Bibliographic record
Abstract
INTERVENTION: British Columbia's (BC) provincial school food and beverage sales policy. RESEARCH QUESTION: What are the processes associated with district-level implementation of BC's school food and beverage sales policy? METHODS: We adopted a realist approach and a qualitative, multiple case study design that included three urban and two rural BC school districts. Data collection involved semi-structured interviews and questionnaires with health, education, and industry stakeholders, observations, document analysis and website scans. Analysis identified: (i) mechanisms influencing if and how stakeholders engage in implementation activities at the district level and (ii) specific dimensions of context influencing these mechanisms. RESULTS: We identified three mechanisms driving implementation processes at the school district level associated with BC's school food and beverage sales policy. These mechanisms are influenced by various dimensions of context that lead to a range of implementation outcomes. The 'mandatory mechanism' refers to the mandatory nature of the policy effectively triggering implementation efforts, influenced by a normative acceptance of the education system hierarchy. The 'money mechanism' refers to how this district demand leads vendors to create a compliant supply; it is influenced by beliefs about children's food preferences, health and food, and the existence of competition. Finally, the 'monitoring mechanism' refers to how systems of informal monitoring are used to promote compliance in the context of a competitive sales environment. CONCLUSION: The outcomes of these three policy mechanisms are influenced by complex dimensions of context. Identifying context-mechanism interactions can help inform public health policymakers interested in interventions for improving school food environments.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".