Peanut-free guidelines reduce school lunch peanut contents
Bibliographic record
Abstract
BACKGROUND: Some schools implement peanut-free guidelines (PFG) requesting omission of peanut from lunches. Our study assessed parental awareness of, and adherence to, PFG by comparing the percentage of lunches containing peanut between primary school classes with and without PFG in Montreal, Québec. METHODS: Parents, school principals and teachers were queried concerning the school's PFG and children's lunches were inspected by a dietician for peanut-containing foods. RESULTS: When lunch peanut contents were compared in randomly selected classrooms, peanut was found in 5/861 lunches in classes with PFG (0.6%, 95% CI 0.2% to 1.4%) and in 84/845 lunches in classes without PFG (9.9%, 95% CI 8.0% to 12.2%), a 9.4% (95% CI 7.3% to 11.4%) difference. CONCLUSIONS: Our findings demonstrate that PFG are effective in reducing peanut in classrooms providing a basis for future research that should address whether or not the reduction in peanut achieved by restrictive lunch policies decreases the morbidity associated with peanut allergy in the school setting.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".