Feeding children while Asian
Bibliographic record
Abstract
In feeding children in a new country, immigrant parents engage in continuous and ongoing adaptation. Children’s exposure to new food practices outside the home can sometimes conflict with parents’ efforts to maintain traditional foodways. This qualitative study explores the factors that influence Asian immigrant parents’ everyday decisions about packing cultural food in their children’s school lunches in Toronto, Canada. Through arts-informed interviews, 19 elementary school children (ages 7-13) and 17 parents from Indian and Chinese backgrounds shared their experiences. Findings reveal that family’s food identity and the convenience of cooking familiar recipes encourage the inclusion of cultural foods, while direct and indirect experiences of lunchbox shaming and school food environments discourage it. Factors such as children’s preferences, parental perceptions of healthy food, and classroom demographics influence parental decisions in both directions. These findings indicate that homemade school lunches communicate both immigrant families’ cultural heritage and their changing food habits in Canada. We argue that the upcoming national school food program carries high stakes: if not thoughtfully implemented with cultural inclusivity at its core, it risks further marginalizing non-dominant foodways and undermining the cultural agency of immigrant families.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".