Why trade and investment liberalisation may threaten effective tobacco control efforts
Bibliographic record
Abstract
Trade and investment liberalisation in tobacco products offers no benefits for tobacco control. Thus, if trade and investment liberalisation—as embodied in international agreements or viewed as an economic process—may harm tobacco control, as we believe it might, then trade and investment liberalisation in tobacco is an unhealthy and inappropriate public policy. We support the resolution of the 11th World Conference on Tobacco or Health that called on “the international tobacco control community [to] work vigorously to exclude and remove tobacco and tobacco products from bilateral and multilateral trade agreements that would have negative public health consequences.”1 We think this position is well supported by the record of the last two decades on trade and tobacco, the text of existing trade agreements, and the threats posed by proposals for expanded trade and investment agreements. In the 1980s, the Office of the US Trade Representative, working hand-in-glove with US cigarette companies, used the threat of trade sanctions to pry open key markets in Japan, Taiwan, South Korea, and Thailand. In the face of US threats, these countries removed restrictions on tobacco imports. In Japan, Taiwan, and South Korea, the result was a rapid rise in smoking rates. After South Korea opened its market to US companies in 1988, for example, smoking rates among male Korean teens rose from 18.4% to 29.8% in a single year, according to the US General Accounting Office.2 The smoking rate among female teens more than quintupled from 1.6% to 8.7%.2 Overall, according to World Bank estimates, the opening of Asian markets to US cigarettes escalated Asian smoking rates 10% above what they would have been.3 Price competition and advertising—the introduction of slick promotional strategies that link cigarettes with notions of sophistication, freedom, and “hipness”, and a heavy linkage between smoking and sports and …
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".