The effectiveness of voluntary policies and commitments in restricting unhealthy food marketing to Canadian children on food company websites
Bibliographic record
Abstract
Marketing unhealthy foods and beverages to children (M2K) fosters poor dietary patterns, increasing obesity and noncommunicable disease risk. Federal restrictions on M2K have been under development in Canada since 2016; however, at present, M2K is mostly self-regulated by food companies. This study aimed to compare M2K on Canadian websites of food companies with and without voluntary policies or commitments in this area. A systematic content analysis of company websites was conducted in spring/summer 2017 for major packaged food (n = 16), beverage (n = 12), and restaurant chain (n = 13) companies in Canada. M2K policies were sourced from company websites and published corporate documents. Sixteen companies (43%) reported national and/or global M2K policies, while 21 companies (57%) had no published policies. The websites of Canadian companies (n = 154) were scanned for child-directed products and marketing; type and frequency of marketing techniques were recorded. Child-directed marketing appeared on 19 websites of 12 companies (32%), including 9 companies with M2K policies. Websites featured products with unconventional flavours, colours, shapes, or child-oriented packaging, and used promotional characters, contests, games, activities, or lettering and graphics appealing to children. The nutritional quality of products marketed to children was evaluated using a nutrient profile model developed by Health Canada for proposed M2K regulations. Of the 217 products marketed to children, 97% exceeded Health Canada's proposed ∼5% Daily Value threshold for saturated fat, sodium, and/or sugars, 73% of which were products from 9 companies with policies. These findings highlight the limitations of self-regulation in restricting M2K on food company websites, reinforcing the need for government regulations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".