School Food Programs in Canada: Characteristics and Nutritional Quality as Measured by Adherence to National Dietary Guidelines
Bibliographic record
Abstract
School food programs (SFPs) are associated globally with extensive benefits; however, Canada remains one of very few high-income countries without a well-established nationally harmonized and funded school feeding strategy. Although the federal government has committed $1 billion over the next five years toward improving and expanding SFPs in Canada, the existing patchwork landscape of SFPs in Canada is poorly understood. To address this gap, we surveyed SFP providers across Canada about their program characteristics and menu data. SFPs were heavily reliant on donations and prepackaged foods, with a primary goal of reducing food insecurity. The nutritional quality of SFPs, as measured by adherence to Canada’s Food Guide was revealed to be approximately 51% and 63% when utilizing dietary quality indices and nutrient profiling models, respectively. Combined, these findings support existing research in emphasizing the opportunity for Canada’s upcoming investment to strengthen the school food landscape and build on best practices.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 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) | 0.004 | 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".