“It's junk food and chicken nuggets”: Children's perspectives on ‘kids' food’ and the question of food classification
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Given the expansive nature of children's food, banning the advertising of poorly nutritious products to children only deals with part of the problem. What is missing is an understanding of how child‐oriented food marketing has reconfigured children's broader perceptions of what food means and the kinds of foods that are ‘for them’. Drawing from focus groups conducted across Canada, this article examines the perspectives of 225 children who discussed both ‘kids' food’ and ‘adult food’. The research reveals the broader implications of particular food marketing strategies. When children think of ‘kids' food’, they generally think of junk food, sugar, sugary cereals and the fun shapes and unusual colours characterizing much of contemporary child‐oriented packaged food. When children think of ‘adult food’, they think of fruits, vegetables and meat. In short, ‘adult foods’ are generally the unprocessed fruits, vegetables and meats that all North Americans should be consuming more of, whereas ‘kids' foods’ are associated with processed, high‐sugar, low‐nutrient edibles. The paper further reveals how ‘kids' food’ functions as an object or technology of identification for children enacted through a set of characteristics that the edibles share. Children's classification of food also reveals their savvy awareness that both ‘kids' food’ and ‘adult food’ can contain transgressive elements. Copyright © 2011 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it