Smokers' reactions to FDA regulation of tobacco products: Findings from the 2009 ITC United States survey
Bibliographic record
Abstract
BACKGROUND: On June 22, 2009, the US FDA was granted the authority to regulate tobacco products through the Family Smoking Prevention and Tobacco Control Act (FSPTCA). The intent is to improve public health through regulations on tobacco product marketing and tobacco products themselves. This manuscript reports baseline data on smokers' attitudes and beliefs on specific issues relevant to the FSPTCA. METHOD: Between November 2009 and January 2010, a telephone survey among a nationally representative sample of n = 678 smokers in the US was performed as part of the International Tobacco Control (ITC) United States Survey. Participants answered a battery of questions on their attitudes and beliefs about aspects of the FSPTCA. RESULTS: Most smokers were unaware of the new FDA tobacco regulations. Smokers indicated support for banning cigarette promotion and nearly a quarter supported requiring tobacco companies to sell cigarettes in plain packaging. Seventy two percent of smokers supported reducing nicotine levels to make cigarettes less addictive if nicotine was made easily available in non-cigarette form. CONCLUSION: Most smokers were limited in their understanding of efforts to regulate tobacco products in general. Smokers were supportive of efforts to better inform the public about health risks, restrict advertising, and make tobacco products less addictive.
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.
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 | 0.002 | 0.006 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".