Origin and use of the 100 cigarette criterion in tobacco surveys
Bibliographic record
Abstract
Truly global standards and definitions will likely never exist for tobacco control surveillance. One difference across definitions of smoking status is whether or not a lifetime consumption of 100 cigarettes is a necessary criterion for ever and current smoking. Frequently asked questions about this measure demonstrate a need for information on its development and appropriateness in different settings. This commentary attempts to assemble information on the origin and adoption of this measure and provide some critical commentary on its usefulness. The question has been traced to Canadian and American mortality cohort studies from the mid-1950s. From there it has spread to inconsistent use in many settings. To our knowledge, it was not originally (or since) empirically defined as a threshold of exposure related to health consequences or future smoking risk when used in youth. Anecdotal evidence over several decades, however, shows the question has pragmatic utility in self-report data collection. It is a useful, if somewhat arbitrary, screener for "never regular" tobacco use among adults, where never smoking needs to be defined in data collection. Use of the criterion may lower prevalence estimates somewhat. Definitions must always be considered when creating time-trends or international comparisons. There are also circumstances where it is inappropriate to exclude individuals who do not meet this criterion from further data collection, or reports. For research in youth, the criterion typically should be used only with more detailed information about experimentation, but it may be a useful additional indicator of established smoking.
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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 | 0.102 | 0.244 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".