Evaluating the nutritional quality of school food programs in Canada compared to national nutritional guidelines
Bibliographic record
Abstract
While the potential of school food programs (SFPs) to influence healthy eating behaviors and improve child health outcomes is recognized globally, Canada currently lacks a well-established nationally coordinated and funded SFP. Instead, the fragmented nature of SFPs across Canada has resulted in a limited understanding of their nutritional quality. This study builds upon prior research assessing the characteristics of Canadian SFPs and aims to provide a baseline of SFP nutritional quality before federal policy implementation to identify priority areas for improvement in the current school food landscape. SFP menu data was collected from a diverse sample of school food providers. The mean content of nutrients of public health concern was calculated and two indices of dietary quality representing adherence to national nutrition guidelines were applied to SFP menu data: Healthy Eating Food Index 2019 (HEFI-2019) and Healthy Eating Index Canada (HEI-C) 2010. Nutritional quality results from 67 SFPs serving over 20% of Canadian schools revealed approximately 51% adherence to the 2019 and 2007 Canada's Food Guides, indicating similar adherence to national dietary guidelines as in the broader population. Snacks tended to be high in total sugars but low in protein and sodium was high across all meal types. Given the limited resources available to SFPs in Canada, these findings indicate that although school food providers are serving relatively healthful choices, a federally harmonized school food policy and program (including the development of national school food guidelines) can further improve the state of school food in Canada and its nutritional quality.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".