Internet marketing directed at children on food and restaurant websites in two policy environments
Bibliographic record
Abstract
OBJECTIVE: Food and beverage marketing has been associated with childhood obesity yet little research has examined the influence of advertising policy on children's exposure to food/beverage marketing on the Internet. The purpose of this study was to assess the influence of Quebec's Consumer Protection Act and the self-regulatory Canadian Children's Food and Beverage Advertising Initiative (CAI) on food manufacturer and restaurant websites in Canada. DESIGN AND METHODS: A content analysis of 147 French and English language food and restaurant websites was undertaken. The presence of child-directed content was assessed and an analysis of marketing features, games and activities, child protection features, and the promotion of healthy lifestyle messages was then examined on those sites with child-directed content. RESULTS: There were statistically no fewer French language websites (n = 22) with child-directed content compared to English language websites (n = 27). There were no statistically significant differences in the number of the various marketing features, or in the average number of marketing features between the English and French websites. There were no fewer CAI websites (n = 14) with child-directed content compared to non-CAI websites (n = 13). The CAI sites had more healthy lifestyle messages and child protection features compared to the non-CAI sites. CONCLUSION: Systematic surveillance of the Consumer Protection Act in Quebec is recommended. In the rest of Canada, the CAI needs to be significantly expanded or replaced by regulatory measures to adequately protect children from the marketing of foods/beverages high in fat, sugar, and sodium on the Internet.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".