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Record W2963928289 · doi:10.1093/nutrit/nuz021

Governmental policies to reduce unhealthy food marketing to children

2019· review· en· W2963928289 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNutrition Reviews · 2019
Typereview
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsnot available
FundersCarolina Population Center, University of North Carolina at Chapel HillEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthInternational Development Research CentreBloomberg Philanthropies
KeywordsFood marketingMarketingBusinessEnvironmental healthMedicineFood scienceChemistry

Abstract

fetched live from OpenAlex

Reducing children's exposure to food marketing is an important obesity prevention strategy. This narrative review describes current statutory regulations that restrict food marketing; reviews available evidence on the effects of these regulations; and compares policy design elements in Chile and the United Kingdom. Currently, 16 countries have statutory regulations on unhealthy food marketing to children. Restrictions on television advertising, primarily during children's programming, are most common. Schools are also a common setting for restrictions. Regulations on media such as cinema, mobile phone applications, print, packaging, and the internet are uncommon. Eleven evaluations of policies in 4 jurisdictions found small or no policy-related reductions in unhealthy food advertising, in part because marketing shifted to other programs or venues; however, not all policies have been evaluated. Compared with the United Kingdom, Chile restricts marketing on more products, across a wider range of media, using more marketing techniques. Future research should examine which elements of food marketing policy design are most effective at reducing children's exposure to unhealthy food marketing.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.894
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.108
GPT teacher head0.402
Teacher spread0.294 · 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