Bibliographic record
Abstract
“Debate” is a series offering opposing sides of a continuing, controversial issue in tobacco control. In this and the three following articles, the likely future of the tobacco industry is discussed and debated by Clive Bates of ASH in London, Rob Cunningham from the Canadian Cancer Society, Stan Glantz from the Institute of Health Policy Studies at the University of California, San Francisco, and Michelle Scollo, from the VicHealth Tobacco Control Centre in Victoria, Australia Here is a best case health scenario for the future of the tobacco industry. Despite the hopes of some of the health lobby, the industry will survive even the most severe litigation assaults. Even the worst judgements would leave the tobacco industry intact. Diversification into completely new businesses will not prove to be a commercial reality for the main companies involved because there is no advantage to non-tobacco business to be merged with tobacco. Regulators will assert proper jurisdiction over tobacco and force the companies to make products that are less harmful by setting emissions limits and product standards—for example, to reduce or remove carbon monoxide, carcinogenic nitrosamines, or many other toxins in tobacco smoke. Over time the delivery of nicotine through tobacco will evolve from combustion, through heating and oral use, and eventually to extracts and purified distillates. Nicotine—the psychoactive chemical that differentiates smoking tobacco from smoking cabbage—will become recognised as the real “product”. The tobacco companies will face competition from new forms of nicotine delivery unconnected with tobacco and will have to respond by using the power of their brands to move into this market. Nicotine will continue to be widely used in society and many will be addicted, but the risk to users will be reduced—at least the option to reduce risk will be available. Concern about “addiction” rather than “disease” will …
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.021 | 0.021 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.018 | 0.016 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".