Not Just Fun and Games: Toy Advertising on Television Targeting Children Promotes Sedentary Play
Bibliographic record
Abstract
OBJECTIVE: To examine the volume of television toy advertising targeting Canadian children and to determine if it promotes active or sedentary play, targets males or females more frequently, and has changed over time. METHODS: Data for toy/game advertising from 27 television stations in Toronto for the month of May in 2006 and 2013 were licensed from Neilsen Media Research (Montreal, Quebec, Canada). A content analysis was performed on all ads to determine what age group and gender were targeted and whether physical or sedentary activity was being promoted. Comparisons were made between 2006 and 2013. RESULTS: There were 3.35 toy ads/h/children's specialty station in 2013 (a 15% increase from 2006). About 88% of toy ads promoted sedentary play in 2013, a 27% increase from 2006 levels, while toy ads promoting active play decreased by 33%. In both 2006 and 2013, a greater number of sedentary toy ads targeted males (n = 1519, May 2006; n = 2030, May 2013) compared with females (n = 914, May 2006; n = 1619, May 2013), and between 2006 and 2013, these ads increased significantly for both males and females. CONCLUSION: Future research should explore whether such advertising influences children's preferences for activities and levels of physical activity.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".