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Record W4410827829 · doi:10.3390/nu17111828

Evaluating the Proportion of Foods and Beverages in the Canadian Grocery and Chain Restaurant Food Supply That Would Be Restricted from Marketing to Children on Television and Digital Media

2025· article· en· W4410827829 on OpenAlexafffundabout
Hayun Jeong, Christine Mulligan, Ayesha Khan, Laura Vergeer, Mary R. L’Abbé

Bibliographic record

VenueNutrients · 2025
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchUniversity of TorontoPresident's Choice Children's Charity
KeywordsBusinessAdvertisingFood marketingMarketingGrocery storeFood scienceChemistry

Abstract

fetched live from OpenAlex

Background/Objectives: Despite evidence on the association between marketing unhealthy foods to children (M2K) and negative health outcomes, M2K remains widespread in Canada. To support mandatory restrictions, Health Canada has prioritized a monitoring strategy to assess the current state of M2K, identify gaps, and establish a baseline for future policy evaluation. This study aimed to support this initiative by updating the University of Toronto (UofT) Food Classification List and evaluating the proportion of foods and beverages in the Canadian grocery and restaurant food supply that would be permitted or restricted from M2K under Health Canada’s proposed nutrient profile model. Methods: Grocery items from the UofT Food Label Information Price 2020 (n = 24,949) and restaurant menu items from Menu-Food Label Information Price 2020 (n = 14,286) databases were evaluated using Health Canada’s M2K nutrient profile model, which assesses foods solely based on thresholds for added sodium, sugars, and saturated fat. The proportion of items permitted for or restricted from M2K was determined overall and by food and menu categories for grocery and restaurant items, respectively. Results: The updated UofT List contained n = 24,494 grocery items and n = 14,286 menu items. Overall, 83% (n = 32,664/39,235) of foods and beverages in the 2020 Canadian food supply would be restricted from M2K. Among grocery items, 23% (n = 5630) would be permitted and 77% (n = 19,202) would be restricted from M2K. Among restaurant items, only 6% (n = 837) would be permitted and 94% (n = 13,442) restricted. Conclusions: The updated UofT List supports Health Canada’s monitoring strategy and highlights the large proportion of unhealthy products in the Canadian food supply that are currently still permitted for M2K. While Health Canada’s M2K nutrient profile model is stringent, gaps remain that could allow continued M2K exposure under the current proposed policy. Ongoing monitoring and policy refinement are essential to effectively protect children from M2K and its harmful effects.

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)0.003
metaresearch head score (Gemma)0.008
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.037
GPT teacher head0.311
Teacher spread0.273 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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