A Comparison of the Healthfulness of Prepackaged Children's Foods from Participants and Non‐Participants of the Canadian Voluntary Code on Marketing to Children
Bibliographic record
Abstract
This study's purpose was to determine whether children's food and beverage products from companies participating in the Canadian voluntary code on marketing to children (CAI), which does not cover product packaging, were healthier than children's products from non‐participating companies. All products marketed to children (n=415) were identified in a database of Canadian food products (n=10,488). The Ofcom nutrient profiling method was used to calculate a summary score of the healthfulness of each children's product based on its content of specific nutrients. These scores, ranging from 1 to 100 (where 1 is least healthy), were compared between children's products from CAI participants (n=164) and non‐participants (n=251). The Ofcom model provides a cutoff score for products to be classified as “healthier”; the proportion of products meeting this “healthier” cutoff was compared between products from CAI participants and non‐participants. The median healthfulness score of children's products from CAI participants was 43 (interquartile range 37‐66); this score was not significantly different compared to children's products from non‐participants, which scored 54 (interquartile range 38‐64). However, a significantly lower proportion of children's products from CAI participants were considered “healthier”, 14% of products, compared to 23% from non‐participants; p = .02. These results indicate that voluntary codes, such as the CAI, in which companies commit to reduce the marketing of unhealthy foods and beverages to children, should also apply to all components of their marketing, including product packaging. Supported by McHenry Chair grant (ML); and OGS, CIHR Master's, and CIHR PICDP graduate scholarships (CM)
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".