Children's response to food price and warning interventions when purchasing snack foods
Bibliographic record
Abstract
Objective The process by which children make food purchasing decisions is not well understood, despite some evidence that children have considerable autonomous purchasing power, and that much of it is directed toward food. Of particular interest is the extent to which proposed “fat taxes” and inclusion of additional information may influence children's food purchases and consumption, and what developmental measures best predict responsiveness to such interventions. Methods Incentive‐compatible purchase experiments involving snack foods conducted with 10–12 year olds in after‐school problems in Edmonton, Alberta, accompanied by 6 measures of child development. Results Participating children show responsiveness to price of snack food items in the experimental setting. Conclusion and comment The ability to influence children's food purchasing choices depends on their attending to price differences and point‐of‐purchase information. The role of children's autonomous purchasing decisions has largely been ignored by practitioners and researchers to date, but is key to understanding the complete picture of modern children's diets. Research support was provided by the Agriculture and Agri‐Food Canada Research Network on Consumer and Market Demand.
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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 | 0.002 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".