The School Food Solution: Creating a healthy school food environment with Canada's Food Guide
Bibliographic record
Abstract
In 2021, Canada’s federal government made a historic commitment to develop a national school food policy. Among overlapping challenges of increasing food insecurity, rising food costs, and the impact on food systems from climate change, there is now an opportunity to create a school food environment that ensures universal access to nutritious foods and supports sustainability in food systems. A universal school food program can ensure that all children, regardless of income, access the recommended nutritious foods and can promote climate-friendly diets. Such school food programs can also support local farmers and regional economies. In this paper, we outline the policy context for the new Canada’s Food Guide and the researched benefits of school food. We argue that Canada’s Food Guide can support a healthy school environment that is equitable and that promotes sustainability in the food system by embracing founding principles of diet equity and sustainability. Our concluding discussion outlines issues to be addressed in implementation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.020 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".