Examining Guidelines for School-Based Breakfast Programs in Canada: A Systematic Review of the Grey Literature
Bibliographic record
Abstract
School breakfast programs are widespread and serve varying objectives regarding youth health promotion. Evidence-based guidelines for breakfast programs may be important in maximizing their effectiveness related to student outcomes, yet it is unclear what is available in Canada. A systematic review was conducted to identify and compare Canadian guidelines related to breakfast programs. Data sources included grey literature databases, customized search engines, targeted websites, and content expert consultations. Eligible guidelines met the following criteria: government and nongovernment sources at the federal and provincial/territorial levels, current version, and intended for program coordinators. Recommendations for program delivery were extracted, categorized, and mapped onto the 4 environments outlined in the ANGELO framework, and they were classified as "common" or "inconsistent" across guidelines. Fifteen sets of guidelines were included. No guidelines were available from federal or territorial governments and 4 provincial governments. There were few references to peer-reviewed literature within the guidelines and despite many common recommendations for program delivery, conflicting recommendations were also identified. Potential barriers to program participation, including a lack of consideration of allergies and other dietary restrictions, were identified. Future research should identify how guidelines are implemented and evaluate what effect their implementation has on program delivery and student outcomes.
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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 | 0.036 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.024 | 0.036 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| 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".