Changes in the volume, power and nutritional quality of foods marketed to children on television in Canada
Bibliographic record
Abstract
OBJECTIVE: To evaluate the self-regulatory Children's Food and Beverage Advertising Initiative pre- and post-implementation in terms of volume of marketing, marketing techniques, and nutritional quality of foods marketed to children on television. METHODS: Data for 11 food categories for May 2006 and 2011 were purchased from Nielsen Media Research for two children's specialty channels in Toronto. A content analysis of food advertisements examining the volume and marketing techniques was undertaken. Nutritional information on each advertisement was collected and comparisons were made between 2006 and 2011. RESULTS: The volume of ads aired by Canadian Children's Food and Beverage Advertising Initiative (CAI) companies on children's specialty channels decreased by 24% between 2006 and 2011; however, children and teens were targeted significantly more, and spokes-characters and licensed characters were used more frequently in 2011 compared to 2006. The overall nutritional quality of CAI advertisements remains unchanged between 2006 and 2011. CONCLUSION: There are clear weaknesses in the self-regulatory system in Canada. Food advertising needs to be regulated to protect the health of Canadian children.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".