Child-appealing packaged food and beverage products in Canada–Prevalence, power, and nutritional quality
Bibliographic record
Abstract
BACKGROUND: Children are frequently exposed to marketing on food packaging. This study evaluated the presence, type and power of child-appealing marketing and compared the nutritional quality of child-appealing vs. non-child-appealing Canadian packaged foods and examined the relationship between nutrient composition and marketing power. METHODS: Child-relevant packaged foods (n = 5,850) were sampled from the Food Label Information Program 2017 database. The presence and power (# of techniques displayed) of child-appealing marketing were identified. Fisher's Exact test compared the proportion of products exceeding Health Canada's nutrient thresholds for advertising restrictions and Mann Whitney U tests compared nutrient composition between products with child- /non-child-appealing packaging. Pearson's correlation analyzed the relationship between nutrient composition and marketing power. RESULTS: 13% (746/5850) of products displayed child-appealing marketing; the techniques used, and the power of the marketing varied ([Formula: see text] 2.2 techniques; range: 0-11). More products with child-appealing packaging than with non-child appealing packaging exceeded Health Canada's thresholds (98% vs. 94%; p < .001). Products with child-appealing packaging (vs. non-child-appealing) were higher in total sugars (median: 14.7 vs. 9 g/RA; p < .001) and free sugars (11.5 vs. 6.2 g/RA; p < .001), but lower in all other nutrients. There was weak overall correlation between marketing power and nutrient levels. Results varied by nutrient and food category. CONCLUSIONS: Unhealthy products with powerful child-appealing marketing displayed on package are prevalent in the food supply. Implementing marketing restrictions that protect children should be a priority.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".