Prevalence and correlates of roll-your-own smoking in Thailand and Malaysia: Findings of the ITC-South East Asia Survey
Bibliographic record
Abstract
Roll-your-own (RYO) cigarette use has been subject to relatively limited research, particularly in developing countries. This paper seeks to describe RYO use in Thailand and Malaysia and relate RYO use to smokers' knowledge of the harmfulness of tobacco. Data come from face-to-face surveys with 4,004 adult smokers from Malaysia (N = 2,004) and Thailand (N = 2000), collected between January and March 2005. The prevalence of any use of RYO cigarettes varied greatly between Malaysia (17%) and Thailand (58%). In both countries, any RYO use was associated with living in rural areas, older average age, lower level of education, male gender, not being in paid work, slightly lower consumption of cigarettes, higher social acceptability of smoking, and positive attitudes toward tobacco regulation. Among RYO users, exclusive use of RYO cigarettes (compared with mixed use) was associated with older age, female gender (relatively), thinking about the enjoyment of smoking, and not making a special effort to buy cheaper cigarettes if the price goes up. Finally, exclusive RYO smokers were less aware of health warnings (RYO tobacco carries no health warnings), but even so, knowledge of the health effects of tobacco was equivalent.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".