Call to restore funding to monitor youth exposure to alcohol advertising
Bibliographic record
Abstract
Even in the face a global pandemic, alcohol persists as a leading contributor to death and disability globally [1-4]. Evidence has accumulated over four decades that alcohol advertising contributes to this public health burden [5, 6]. Despite this evidence, governments around the globe have handed responsibility for regulating alcohol advertising to the alcohol companies themselves, which they implement with their own voluntary advertising guidelines [7-9]. There has been a concerted effort in the United States since 2002 to scrutinize the alcohol industry's advertising practices, in particular documenting youth exposure to advertising in different media. Initially funded by private foundations, this work was later authorized by the US Congress as part of the STOP Underage Drinking Act of 2006 [10]. Congress encouraged the Centers for Disease Control and Prevention (CDC) to pick up this monitoring in Appropriations Report language in 2008 and 2010, and the Senate explicitly provided funding for this monitoring beginning in fiscal year 2010 [11, 12]. These surveillance efforts yielded an important body of research [13-16]. Further, this body of research produced the world's most comprehensive database of alcohol advertising practices, with more than 4 million records of advertisements placed on television in the United States from 2001 to 2019. With the publication of ‘Evaluation of monitoring youth exposure to alcohol advertising on cable television, United States, 2016–2019’ [17], public health professionals and policymakers have the best evidence to date that regular monitoring reports may reduce youth exposure to alcohol advertising. This study found that publication of monitoring reports was associated with a 27.0% decline in youth exposure to all alcohol cable television advertising and a 77.3% decline in youth exposure to advertisements that did not comply with alcohol industry voluntary guidelines. Despite these results, the CDC inexplicably terminated funding for these monitoring efforts in 2020. The CDC's decision has removed a key component for prevention of underage drinking as recommended by the National Academy of Medicine (formerly the National Research Council of the Institute of Medicine—recommendation 7–3) and incorporated into the National Prevention Strategy [18, 19]. Further, by taking this step the CDC destroyed 19 years of advertising research data by terminating the licenses needed to maintain the comprehensive advertising database that was supporting this program of research. We call upon the CDC to immediately reinstate funding to monitor the advertising practices of the alcohol industry to protect youth from earlier drinking initiation, increased drinking and drinking-related injuries, all of which have all been associated with exposure to alcohol advertising [5, 6]. None.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".