Unboxing the bento box: An arts-informed inquiry into Japanese families’ experience at Canadian school lunch time
Bibliographic record
Abstract
Bento, a Japanese style boxed lunch, has a distinct cultural meaning for Japanese people as a medium of affective communication between children and parents. However, in Canadian schools governed by the Anglo-Western food norms, their culinary practices may stand out. This study employed an arts-informed participatory design to explore how school-aged children (6-12 years old) of Japanese origin and their parents describe their experience bringing Japanese food to school in Canada. We conducted arts-informed workshops with 16 children who created artworks about their lunchboxes, and focus groups with 19 parents (all mothers). Children’s artworks illuminated a common aesthetics about “good” lunch that closely reflected mothers’ commitment to preparing nutritionally balanced and aesthetically appealing bento boxes. Both children and mothers reported that Canadian school food environment (e.g., short eating periods, snack times, built environment) sometimes misaligns with their food practices. Some families were compelled to modify their bento to accommodate children’s needs to fit in at school. Meantime, participants’ narratives indicate the prevalence of stigma toward “junk” food that may perpetuate food shaming at school. A more inclusive, diverse and culturally appropriate discussion on “healthy eating” at school can embrace children’s and their families’ intercultural food identities.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.031 | 0.016 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".