What's for Lunch? Investigating the Experiences, Perceptions, and Habits of Parents and School Lunches: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Research indicates home-packed school lunches are lower in nutritional value compared with school-provided meals. Due to the lack of a school lunch program, most of what Canadian children consume during the school day is determined by parents and caregivers through packed lunches. Despite this, little research has focused on the school lunch packing habits and attitudes of parents. The purpose of this scoping review was to improve understanding of parental perceptions, experiences, and habits with respect to home-packed school lunches. METHODS: We conducted a scoping review of peer-reviewed and gray literature. We reviewed only studies published from January 2000 to January 2019 with a focus on parents' lunch packing habits for their school-aged children. RESULTS: The review included 7 studies, with articles from the United Kingdom, Australia, and Canada. The studies identified 6 themes influencing parental decisions regarding what to pack in their child's lunch-school environment, food as fuel, convenience, child's influence, cost, and the lunch experience. CONCLUSIONS: The decisions that influence what is packed in a school lunch are complex and indicate the need for support. Parents, schools, districts, and government policymakers need to work collaboratively to improve the healthiness of home-packed school lunches.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 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".