“Key to the Future”: British American Tobacco and Cigarette Smuggling in China
Bibliographic record
Abstract
BACKGROUND: Cigarette smuggling is a major public health issue, stimulating increased tobacco consumption and undermining tobacco control measures. China is the ultimate prize among tobacco's emerging markets, and is also believed to have the world's largest cigarette smuggling problem. Previous work has demonstrated the complicity of British American Tobacco (BAT) in this illicit trade within Asia and the former Soviet Union. METHODS AND FINDINGS: This paper analyses internal documents of BAT available on site from the Guildford Depository and online from the BAT Document Archive. Documents dating from the early 1900s to 2003 were searched and indexed on a specially designed project database to enable the construction of an historical narrative. Document analysis incorporated several validation techniques within a hermeneutic process. This paper describes the huge scale of this illicit trade in China, amounting to billions of (United States) dollars in sales, and the key supply routes by which it has been conducted. It examines BAT's efforts to optimise earnings by restructuring operations, and controlling the supply chain and pricing of smuggled cigarettes. CONCLUSIONS: Our research shows that smuggling has been strategically critical to BAT's ongoing efforts to penetrate the Chinese market, and to its overall goal to become the leading company within an increasingly global industry. These findings support the need for concerted efforts to strengthen global collaboration to combat cigarette smuggling.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".