Industry influence over global alcohol policies via the World Trade Organization: a qualitative analysis of discussions on alcohol health warning labelling, 2010–19
Bibliographic record
Abstract
BACKGROUND: Accelerating progress to implement effective alcohol policies is necessary to achieve multiple targets within the WHO global strategy to reduce the harmful use of alcohol and the Sustainable Development Goals. However, the alcohol industry's role in shaping alcohol policy through international avenues, such as trade fora, is poorly understood. We investigate whether the World Trade Organization (WTO) is a forum for alcohol industry influence over alcohol policy. METHODS: In this qualitative analysis, we studied discussions on alcohol health warning labelling policies that occurred at the WTO's Technical Barriers to Trade (TBT) Committee meetings. Using the WTO Documents Online archive, we searched the written minutes of all TBT Committee meetings available from Jan 1, 1995, to Dec 31, 2019, to identify minutes and referenced documents pertaining to discussions on health warning labelling policies. We specifically sought WTO member statements on health warning labelling policies. We identified instances in which WTO member representatives indicated that their statements represented industry. We further developed and applied a taxonomy of industry rhetoric to identify whether WTO member statements advanced arguments made by industry in domestic forums. FINDINGS: Among 83 documents, comprising TBT Committee minutes, notifications to the WTO of the policy proposal, and written comments by WTO members, WTO members made 212 statements (between March 24, 2010, and Nov 15, 2019) on ten alcohol labelling policies proposed by Thailand, Kenya, the Dominican Republic, Israel, Turkey, Mexico, India, South Africa, Ireland, and South Korea. WTO members stated that their claims represented industry in seven (3·3%) of 212 statements, and 117 (55·2%) statements featured industry arguments. Member statements featured many arguments used by industry in domestic policy forums to stall alcohol policy. Arguments focused on descaling and reframing the nature and causes of alcohol-related problems, promoting alternative policies such as information campaigns, promoting industry partnerships, questioning the evidence, and emphasising manufacturing and wider economic costs and harms. INTERPRETATION: WTO discussions at TBT Committee meetings on alcohol health warnings advanced arguments used by the alcohol industry in domestic settings to prevent potentially effective alcohol policies. WTO members appeared to be influenced by alcohol industry interests, although only a minority of challenges explicitly referenced industry demands. Increased transparency about vested interests might be needed to overcome industry influence. FUNDING: 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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".