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Record W2128279850 · doi:10.1071/hp090601

Regulatory axes on food advertising to children on television

2009· article· en· W2128279850 on OpenAlexaboutno aff
Elizabeth Handsley, Kaye Mehta, John Coveney, Chris Nehmy

Bibliographic record

VenueAustralia and New Zealand Health Policy · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsAdvertisingLimitingVariety (cybernetics)CentringProduct (mathematics)Population healthUnhealthy foodMarketingBusinessPopulationMedicineEnvironmental healthEngineeringComputer science

Abstract

fetched live from OpenAlex

This article describes and evaluates some of the criteria on the basis of which food advertising to children on television could be regulated, including controls that revolve around the type of television programme, the type of product, the target audience and the time of day. Each of these criteria potentially functions as a conceptual device or "axis" around which regulation rotates. The article considers examples from a variety of jurisdictions around the world, including Sweden and Quebec. The article argues that restrictions centring on the time of day when a substantial proportion of children are expected to be watching television are likely to be the easiest for consumers to understand, and the most effective in limiting children's exposure to advertising.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.141
Threshold uncertainty score0.280

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0050.016
Scholarly communication0.0100.002
Open science0.0010.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.387
Teacher spread0.331 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations59
Published2009
Admission routes1
Has abstractyes

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