How frequently is alcohol advertised on television in Canada?: A cross-sectional study
Bibliographic record
Abstract
AIMS: Alcohol marketing is a commercial driver of alcohol use, including among youth. This study sought to quantify and characterize alcohol advertising on broadcast television in Canada. METHODS: Open-source television program logs for January to December 2018 submitted to the Canadian Radio-television and Telecommunications Commission by 147 stations with alcohol advertisements were analyzed. RESULTS: Overall, 501 628 alcohol advertisements were broadcast. Four companies accounted for 83% of advertisements, namely, Anheuser-Busch in Bev (33.7%), Molson Coors (22.7%), Diageo (16.1%), and Arterra Wines Canada (10.8%). On conventional stations, advertising was highest on French-language stations [Median (Mdn) = 3224; interquartile range (IQR) = 2262] followed by those with programming in foreign/mixed languages (Mdn = 2679; IQR = 219) and English-language stations (Mdn = 1955; IQR = 1563). On speciality stations, advertising was most frequent on those primarily focused on sports programming (Mdn = 8036; IQR = 7393), movies and scripted shows (Mdn = 7463; IQR = 5937), and cooking (Mdn = 5498; IQR = 4032). On weekdays, 33% of alcohol ads aired from 6 to 9 a.m. and 3 to 9 p.m. and on weekends, 52% aired from 6 a.m. to 9 p.m. when children or adolescents are more likely to be watching television. On youth-oriented stations (n = 4), 7937 alcohol advertisements were broadcast with most airing from 9 p.m. to midnight (44-45%) or 12-6 a.m. (50%) on both weekdays and weekends. CONCLUSIONS: While few alcohol advertisements were broadcast on youth-oriented stations, young people in Canada are likely exposed to such advertising on programming intended for older or general audiences (e.g. sports). More research is needed to ascertain the extent to which broadcast television constitutes a source of alcohol advertising exposure among youth and to inform policies aimed at protecting them from the influence of such exposure.
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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".