Food providers’ experiences with a central procurement school snack program
Bibliographic record
Abstract
Universal, government-funded school food programs (SFPs) offer many benefits not only to the children they serve, but also to the communities that support them. To date, Canada does not have a national SFP. Thus, if one is to be considered, evaluations of current SFPs in a Canadian context are necessary. This study explored food providers’ experiences with the Centrally Procured School Food Program (CPSFP) in Southwestern Ontario, Canada. Twenty interviews were conducted with individuals involved in the production, procurement, and delivery of food to schools. Successes included improved economies of scale, increased profile and awareness of local food systems, and enhanced reach into schools. Challenges included inconsistent delivery times and unexpected food volumes that placed additional burdens on program implementation. Recommendations for program sustainability included enhanced engagement of partners, sustained funding to build capacity (including paid personnel), and more learning opportunities for students. Food providers gave insights on how the CPSFP can be improved and sustained into the future, as well as its potential to provide new opportunities for all stakeholders and have a positive impact on the local food system.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.020 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".