Transitioning to a Plant-Based Menu in Childcare: Identifying the Nutritional, Financial, and Logistical Considerations
Bibliographic record
Abstract
International health organizations have called for a shift towards more plant-based foods as a way of promoting both individual health and environmental sustainability. Given the high percentage of children in Canada who attend childcare and the high volume of food provided in childcare, transitioning menus to incorporate plant-based foods could have important implications for both planetary and child health. The purpose of this case study is to describe a childcare centre's transition to a plant-based menu. A detailed nutritional analysis of the menu was conducted. The financial and logistical implications of the transitions to a plant-based menu were also assessed. Nutritional analysis revealed that the plant-based menu met or exceeded the daily nutrient requirement for all the key nutrients explored. Financially, the transition led to a 9% reduction in food costs. Logistically, the transition led to improved efficiency and safety with regard to food preparation, with substantially fewer tailored meals due to allergies and dietary restrictions required after the transition. These novel findings are relevant for food service administrators interested in transitioning to a plant-based menu as well as public health dietitians who could support the transition.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".