The Impact of Canadian School Food Programs on Children’s Nutrition and Health: A Systematic Review
Bibliographic record
Abstract
The quality of children's diets has declined over the past few decades, giving rise to a variety of health-related consequences. In response to this trend, school food programs have become an increasingly effective method to support nutrition and lifelong healthy eating habits. This systematic review synthesizes current academic literature pertaining to school nutrition programs in Canada to identify existing interventions and their impacts on children's nutritional knowledge, dietary behaviour, and food intake. The review was conducted through a search of the following databases: ERIC, Education Source, CINAHL, PubMed, SagePub, SCOPUS, EMBASE, and CBCA. Information extracted from the articles included the program objectives, intervention design and components, research evaluation, and primary outcomes. A total of 11 articles evaluating Canadian school nutrition programs were identified. The programs incorporated a variety of intervention components including policy, education, family and community involvement, and/or food provision. These multi-component interventions were positively associated with children's development of nutrition knowledge, dietary behaviour changes, and intake of healthy foods; however, barriers associated with intervention duration, intensity, and availability of resources may have influenced the extent to which these programs impacted children's diets and overall health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.011 | 0.021 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".