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Record W2150737572 · doi:10.1136/tc.9.2.237

What is the future for the tobacco industry?

2000· letter· en· W2150737572 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTobacco Control · 2000
Typeletter
Languageen
FieldHealth Professions
TopicHealthcare Systems and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsTobacco industryBusinessEnvironmental healthMarketingAdvertisingMedicinePathology

Abstract

fetched live from OpenAlex

“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 …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0070.014
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.066
GPT teacher head0.392
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it