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Record W2787623336 · doi:10.11575/prism/30087

Addressing Misleading Nutrition Marketing on Children's Foods

2013· dissertation· en· W2787623336 on OpenAlexaboutno aff
Christine Veit

Bibliographic record

VenueOpen MIND · 2013
Typedissertation
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsnot available
Fundersnot available
KeywordsMarketingNutrition LabelingAdvertisingFood sciencePsychologyMedicineBusinessBiology

Abstract

fetched live from OpenAlex

Childhood obesity is a complex issue with many contributing factors. Today, children live in an obesogenic environment that promotes the consumption calorie dense foods high in sugar, fat, and sodium. While much of the previous research has focused on linking the consumption of junk foods to obesity, an important area that has been overlooked until recently is how regular children’s foods are contributing to the childhood obesity epidemic. Today, a large proportion of children’s foods are being marketed with nutrition claims, health claims, and industry generated front-of-package nutrition logos despite the fact that they contain high levels, of sugar, fat, and sodium. A study by Elliott (2008) found that 89% of the children’s foods in Canadian grocery stores were marketed with nutrition and health claims, yet 63% of them could be classified “as of poor nutritional quality” due to their high levels of sugar, fat, and sodium. Similarly, a study by Colby (2010) examining a large sample of foods in the US found that 42% of children’s foods contained both nutrition marketing and high levels of saturated fat, sugar, and sodium. These regular foods which include granola bars, breakfast cereals, fruit leathers, and yogourts are often marketed with claims such as ‘excellent source of calcium’, ‘reduced fat’, and ‘made with real fruit juice’ in large font on the front of the packaging of children’s foods in order to appeal to parents. Claims that prominently single out one nutrient in large bold font of the front of a food package in a nutritionally inferior product high in sugar, fat, and sodium could be construed as misleading advertisement. The misleading information conveyed by claims on children’s food packaging can be framed as a problem of information asymmetry. Foods boldly displaying large nutrition claims that draw attention one nutrient in an otherwise unhealthy product interfere with parents’ ability to accurately judge the nutritional quality of the foods they are purchasing for their children. As a result, many uninformed parents swayed by health and nutrition claims may end up purchasing foods for their children that are high in sugar, fat, and salt. Regulated nutrition and health claims as well as unregulated industry generated nutrition logos constitute the two main sources of information asymmetry. Although the Food and Drugs Regulations lay out specific criteria for the use of nutrition and health claims, it falls short in two major areas: it does not prohibit foods high in sugar, fat, and sodium from carrying health or nutrition claims, nor does it prohibit food manufacturers from displaying their own unregulated nutrition logos on the front of children’s food packages. As a result, food manufacturers are free to continue aggressively marketing their unhealthy foods to parents with important consequences for children’s weight and their future health.

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)0.014
metaresearch head score (Gemma)0.064
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.064
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0050.004
Scholarly communication0.0080.008
Open science0.0020.006
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0250.005

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 head0.331
GPT teacher head0.527
Teacher spread0.196 · 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 designQualitative
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

Citations0
Published2013
Admission routes1
Has abstractyes

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