An interactive after-school nutrition and culinary education program for primary school students: The evaluation and efficacy of changing food-related knowledge, attitudes and behaviour
Bibliographic record
Abstract
Objective: To evaluate the efficacy of a 10-week afterschool nutrition and culinary education program in changing the culinary and nutritional behaviour, attitudes and knowledge of its 9-11-year-old participants, as assessed by parents and children. Methods: Retrospective matched-pairs analysis of secondary pre-post survey data collected by Boîte à Lunch (BàL). Children (n=165-197; grades 4 and 5) and parents (n=53-57) who signed-up for the BàL workshops. The program was comprised of ten-week (2 hours/week) bilingual (French and English) themed sessions led by trained educators with focus on culinary skill development, nutrition education and hands-on cooking. Secondary objectives include: team-work, kitchen hygiene, compost, understanding of food systems. Workshops were held in community centres and schools in Montreal, Canada. Changes were analyzed using the expanded exact McNemar-Bowker test with a Bonferroni-adjusted significance level of 0.001631. Results: Culinary skill and knowledge improved based on all 23 measures (all p<0.001631). Of the six measures assessed for change in attitude, three were significantly improved. Of the two items used to asses a change of behaviour, one was significantly improved. 2 stand-alone post-workshop questions suggest a positive trend for improvements in each. Conclusion: Knowledge and culinary skill of youth can be improved through nutrition education and hands-on cooking. Culinary and nutritional attitudes and behaviours may be improved; further research is needed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".