Sneak peek: food, waste and packaging characteristics of South Australian school children’s lunchboxes
Bibliographic record
Abstract
Abstract Objective: To characterise children’s lunchbox contents for food, waste and packaging. Design: A cross-sectional study was conducted. Lunchboxes were photographed at two time points on the same day: before first morning break to capture food and packaging and post-lunch break to capture food waste. Contents were coded using an audit tool developed using REDCap. Setting: Twenty-three sites across metropolitan Adelaide, South Australia including fourteen preschools and nine primary schools in low ( n 8), medium ( n 7) and high ( n 8) socioeconomic areas. Participants: Preschool (ages 3–5 years) to Grade 7 primary school (ages 6–13 years) students. Results: 673 lunchboxes were analysed. Grain foods dominated (with at least half of them being discretionary varieties), with 92 % of lunchboxes having at least one item from that category, followed by fruits (78 %), snacks (62 %), dairy (32 %) and vegetables (26 %). Lunchboxes of preschool children contained more fruits (92 % v . 65 %; χ2(1) = 73·3, P < 0·01), vegetables (36 % v . 16 %; χ2(1) = 34·0, P < 0·01) and dairy items (45 % v . 19 %; χ2(1) = 53·6, P < 0·01), compared to lunchboxes of primary school children. Snack foods were more prevalent in primary school (68 %) than preschool (55 %; χ2(1) = 11·2, P < 0·01). Discretionary foods appeared more frequently, and single-use packaging accounted for half (53 %) of all packaging in lunchboxes, primarily from snacks and grain foods. Preschool children had less single-use packaging but more food waste. Vegetables were the most wasted food group. Conclusions: Sandwiches, fruits and various snacks are typical lunchbox foods, often accompanied by single-use packaging. Considering both health and environmental factors in lunchbox choices could benefit children and sustainability efforts in schools.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".