Young consumers in fast food restaurants: technology, toys and family time
Bibliographic record
Abstract
Purpose The purpose of the study was to further our understanding of in-restaurant family behaviors using an ethnographic study of families with children (at least one child from 2 to 12 years old) dining in fast food restaurants. Design/methodology/approach This study includes an unobtrusive, direct observational study of family fast food restaurant behaviour, including use of mobile technology, toys and indoor play area. Ordering and dining behaviours include field notes and enumeration of activity times for 300 families (450 children). Findings The food ordering process was rapid (<6 min), during which personal technology use was minimal, and adult/child interactions were perfunctory. Visits averaged 53 min, and only 18 min on average was spent eating. Families were observed using the fast food restaurant as a “third place” (home away from home) for many activities other than eating food. In-restaurant family behaviours included frequent use of technology (40 per cent of children/ 70 per cent of adults), use of the indoor play area (65 per cent of children/ 33 min of play) and child engagement with a toy (53 per cent of children/10 min of play). Originality/value Studying how time is spent in fast food restaurants expands the knowledge of current family eating behaviours and how young consumers behave in restaurants (i.e. with restaurant-provided activities, toys and indoor play spaces). Shifts in dining practices, from the intrusion of technology during the meal (technoference) to a decline in the use of restaurant-provided toys were noted. Dining visits now include many non-food activities, and the dining time in the restaurant was not a time for extensive family conversations or interactions, but rather a public home away from home.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".