Children’s Perceptions of the Ontario Student Nutrition Program (OSNP) in Southwestern Ontario, Canada
Bibliographic record
Abstract
Purpose: This study aimed to explore children’s lived experiences with the Ontario Student Nutrition Program (OSNP), a free, school-based snack program implemented in elementary schools in Southwestern, Ontario, Canada, to gain insights into future school food programs (SFP). Methods: Focus group discussions (n=17) were conducted with 105 children in Grades 5 to 8 in seven elementary schools. Focus groups were audio-recorded, transcribed, and coded for themes using inductive content analysis. Results: Overall, children appreciated the OSNP and felt that it filled a need in students. Children also reported a willingness to try novel food items. For future SFPs, participants recommended that input be sought from children to ensure food preferences were considered. Children also discussed wanting more appealing food offerings that may include some choice. Finally, children also mentioned wanting a fair and equitable distribution of food in classrooms. Conclusions: Children appreciated the OSNP and reported benefits to themselves and their peers. They also provided some valuable recommendations for future SFPs. If a nationally funded SFP is to be considered in Canada, children expressed the need to make the program equitable, while still allowing schools the flexibility to meet their unique needs and preferences.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".