Assessing alcohol industry penetration and government safeguards: the International Alcohol Control Study
Bibliographic record
Abstract
BACKGROUND: The alcohol industry uses many of the tobacco industry's strategies to influence policy-making, yet unlike the Framework Convention on Tobacco Control, there is no intergovernmental guidance on protecting policies from alcohol industry influence. Systematic assessment of alcohol industry penetration and government safeguards is also lacking. Here, we aimed to identify the nature and extent of industry penetration in a cross-section of jurisdictions. Using these data, we suggested ways to protect alcohol policies and policy-makers from undue industry influence. METHODS: As part of the International Alcohol Control Study, researchers from 24 jurisdictions documented whether 22 indicators of alcohol industry penetration and government safeguards were present or absent in their location. Several sources of publicly available information were used, such as government or alcohol industry reports, websites, media releases, news articles and research articles. We summarised the responses quantitatively by indicator and jurisdiction. We also extracted examples provided of industry penetration and government safeguards. RESULTS: There were high levels of alcohol industry penetration overall. Notably, all jurisdictions reported the presence of transnational alcohol corporations, and most (63%) reported government officials or politicians having held industry roles. There were multiple examples of government partnerships or agreements with the alcohol industry as corporate social responsibility activities, and government incentives for the industry in the early COVID-19 pandemic. In contrast, government safeguards against alcohol industry influence were limited, with only the Philippines reporting a policy to restrict government interactions with the alcohol industry. It was challenging to obtain publicly available information on multiple indicators of alcohol industry penetration. CONCLUSION: Governments need to put in place stronger measures to protect policies from alcohol industry influence, including restricting interactions and partnerships with the alcohol industry, limiting political contributions and enhancing transparency. Data collection can be improved by measuring these government safeguards in future studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".