Alcohol marketing in the Americas and Spain during the 2014 FIFA World Cup Tournament
Bibliographic record
Abstract
BACKGROUND AND AIMS: To identify the nature of visual alcohol references in alcohol advertisements during televised broadcasts of the 2014 FIFA World Cup Tournament matches and to evaluate cross-national differences according to alcohol marketing policy restrictiveness. DESIGN: Content analysis using the Delphi method and identification of in-game sponsorships. SETTING: Television broadcasts of the 2014 FIFA World Cup in Argentina, Brazil, Canada, Finland, France, Mexico, Spain and the United States. CASES: Eighty-seven alcohol advertisements; 20 matches. MEASUREMENTS: Quantitative rating scales, combined with the Delphi rating technique, were used to determine compliance of the alcohol advertisements with the International Alliance for Responsible Drinking's (IARD) Guiding Principles. Recordings of five matches from four countries were also used to identify the number of in- and out-of-game alcohol brand appearances. FINDINGS: A total of 86.2% of all unique alcohol advertisements contained at least one violation of IARD's Guiding Principles, with violation rates ranging from 72.7% (Mexico) to 100% (Brazil). Countries with the least restrictive marketing policies had a higher prevalence of violations in guidelines designed to protect minors. There were 2.76 in-game alcohol brand appearances and 0.83 out-of-game alcohol brand appearances per minute. Brand appearances did not differ across countries or according to a country's marketing policy restrictiveness. CONCLUSIONS: Self-regulation and statutory policies were ineffective at limiting alcohol advertising during the 2014 FIFA World Cup Tournament television broadcasts. Most advertisements contained content that violated the self-regulation codes, and there were high levels of within-broadcast brand appearances.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".