School Food Policies and Student Eating Behaviors in Canada: Examination of the 2015 Cancer Risk Assessment in Youth Survey
Bibliographic record
Abstract
BACKGROUND: Limited evidence exists on effects of school-based nutrition policies. This study explored the influence of mandatory versus voluntary provincial school nutrition policies on student eating behaviors. METHODS: A cross-sectional, school-based survey assessed student eating behaviors using self-report survey measures in a representative sample of Canadian high school students from 7 provinces (N = 12,110). Provincial school nutrition policies were characterized as mandatory or voluntary. Healthful and nonhealthful eating behaviors were analyzed across sociodemographic characteristics. Regression models were used to assess the association between policy type and eating behaviors, and to explore potential moderating variables. RESULTS: Healthful and nonhealthful eating behaviors differed significantly across several sociodemographic characteristics. Overall, neither healthful nor nonhealthful eating behaviors differed significantly between schools with voluntary and mandatory nutrition policies (odds ratio [OR] = 0.83, 95% confidence interval [CI] 0.64-1.08; OR = 1.16, 95% CI 0.83-1.64). Frequency of buying lunch at school and buying lunch out moderated the association between policy enforcement level and healthful eating behaviors (p = .0472, p = .0119). Frequency of buying lunch out moderated the association between policy enforcement levels and nonhealthful eating behaviors (p = .0009). CONCLUSIONS: This study documents nonhealthful components of Canadian adolescents' diets, and the results highlight important areas for future research in assessing the effectiveness of school nutrition policies.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".