The healthfulness of major food brands according to Health Canada’s nutrient profile model for proposed restrictions on food marketing to children
Bibliographic record
Abstract
OBJECTIVE: To examine the proportion of products offered by leading food brands in Canada that are 'unhealthy' according to Health Canada's (HC) nutrient profile model for proposed restrictions on food marketing to children (M2K-NPM). DESIGN: Nutritional information for products offered by top brands was sourced from the University of Toronto FLIP and Menu-FLIP 2020 databases, respectively. HC's M2K-NPM, which includes thresholds for Na, total sugars and saturated fat, was applied to products. SETTING: Canada. PARTICIPANTS: 60 unique brands overall). RESULTS: 21), 100 % of their products exceeded ≥1 nutrient threshold(s), with ≥50 % of the products offered by twenty-three brands (46 %) exceeding two thresholds. Specifically, one or more nutrient thresholds were exceeded by ≥50 % of the products offered by 14/15 breakfast cereal brands, 18/21 beverage brands, all ten yogurt brands and all seventeen restaurant brands. Notably, 100·0 % of the products offered by ten breakfast cereal, six beverage, two yogurt and three restaurant brands exceeded ≥1 threshold(s). CONCLUSIONS: Most products offered by top food brands in Canada exceeded HC's M2K-NPM thresholds. Nonetheless, these brands could still be marketed under the proposed regulations, which exclude brand marketing (i.e. promotions without an identifiable product) despite its contribution to marketing power. These findings reinforce the need for Canada and other countries to include brand marketing in M2K policies.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".