“Efforts to Reprioritise the Agenda” in China: British American Tobacco's Efforts to Influence Public Policy on Secondhand Smoke in China
Bibliographic record
Abstract
BACKGROUND: Each year, 540 million Chinese are exposed to secondhand smoke (SHS), resulting in more than 100,000 deaths. Smoke-free policies have been demonstrated to decrease overall cigarette consumption, encourage smokers to quit, and protect the health of nonsmokers. However, restrictions on smoking in China remain limited and ineffective. Internal tobacco industry documents show that transnational tobacco companies (TTCs) have pursued a multifaceted strategy for undermining the adoption of restrictions on smoking in many countries. METHODS AND FINDINGS: To understand company activities in China related to SHS, we analyzed British American Tobacco's (BAT's) internal corporate documents produced in response to litigation against the major cigarette manufacturers to understand company activities in China related to SHS. BAT has carried out an extensive strategy to undermine the health policy agenda on SHS in China by attempting to divert public attention from SHS issues towards liver disease prevention, pushing the so-called "resocialisation of smoking" accommodation principles, and providing "training" for industry, public officials, and the media based on BAT's corporate agenda that SHS is an insignificant contributor to the larger issue of air pollution. CONCLUSIONS: The public health community in China should be aware of the tactics previously used by TTCs, including efforts by the tobacco industry to co-opt prominent Chinese benevolent organizations, when seeking to enact stronger restrictions on smoking in public places.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| 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".