Content analysis of Netflix and Amazon Prime Instant Video original films in the UK for alcohol, tobacco and junk food imagery
Bibliographic record
Abstract
BACKGROUND: Exposure to alcohol, tobacco and high fat, sugar and salt (HFSS) food imagery is a significant risk factor for the uptake and regular use of these products in young people, and imagery are more frequently portrayed in video-on-demand (VOD) than in terrestrial television programmes. This study compared alcohol, tobacco and HFSS imagery in original films on Amazon Prime Instant Video and Netflix. METHODS: Content analysis of 11 original films released by Amazon Prime and Netflix in 2017 using 5-minute interval coding of alcohol, tobacco and HFSS content. Proportions of intervals containing alcohol, tobacco and HFSS imagery were compared between services using the chi-square test. RESULTS: Alcohol content appeared in 200 (41.7%) out of the total of 479 intervals coded, whereas tobacco and HFSS appeared in 129 (26.9%) and 169 (35.24%), respectively. Proportions were similar between Amazon Prime Instant Video and Netflix original films and were unrelated to film age classification. CONCLUSIONS: Alcohol, tobacco and HFSS content likely to promote consumption among young people occurs frequently in original films shown by VOD services in the UK. Further studies are needed to investigate effective regulatory frameworks for VOD services to protect viewers from harmful or unwanted contents.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".