MétaCan
Menu
Back to cohort
Record W2101360493 · doi:10.3138/cpp.34.2.259

Marketing Fun Foods: A Profile and Analysis of Supermarket Food Messages Targeted at Children

2008· article· en· W2101360493 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Public Policy · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsCarleton University
Fundersnot available
KeywordsScrutinyChildhood obesityFood marketingJunk foodMeaning (existential)AdvertisingMarketingBusinessFocus (optics)PsychologyObesityPublic relationsPolitical scienceMedicineOverweight

Abstract

fetched live from OpenAlex

Childhood obesity is a significant problem that requires innovative solutions. This article suggests that researchers and policy-makers move beyond a scrutiny of junk food and televised advertisements to children to focus on the messages targeted to children in the supermarket. Following a content analysis of fun foods marketed to children, the article (a) outlines why the recoding of “regular” food into “fun food” contributes to the childhood obesity crisis, and (b) suggests how the meaning-making practices of food can be acknowledged in the policy-making process.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.016
GPT teacher head0.197
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it