Alcohol Portrayal on Television Affects Actual Drinking Behaviour
Bibliographic record
Abstract
AIMS: Alcohol portrayal in movies and commercials is generally positive and might stimulate young people to drink. We tested experimentally whether portrayal of alcohol images in movies and commercials on television promotes actual drinking. METHODS: In a naturalistic setting (a bar lab), young adult male pairs watched a movie clip for 1 h with two commercial breaks and were allowed to drink non-alcohol and alcoholic beverages. These participants were randomly assigned to one of four conditions varying on the type of movie (many versus few alcohol portrayals) and commercials (alcohol commercials present or not). RESULTS: Participants assigned to the conditions with substantial alcohol exposure in either movies or commercials consume more alcohol than other participants. Those in the condition with alcohol portrayal in movie and commercials drank on average 1.5 glasses more than those in the condition with no alcohol portrayal, within a period of 1 h. CONCLUSIONS: This study-for the first time-shows a causal link between exposure to drinking models and alcohol commercials on acute alcohol consumption.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".