Socioeconomic and drug use determinants of smoking status in an urban adult population of Black African descent
Bibliographic record
Abstract
We examined the influence of socioeconomics and drug use on current smokers (N = 137) and nonsmokers (N = 143) from an urban adult population of Black African descent. Median participant age was 33 years (range = 20-59). Smokers consumed a median of eight cigarettes/day (range = 0-35). Interestingly, 86% smoked fewer than 15 cigarettes/day and only 8% smoked menthol cigarettes. Socioeconomic and drug use variables significantly associated with smoking status in univariate analyses were included in a multiple logistic regression model that controlled for gender and age. Compared with nonsmokers, smokers were less likely to be university educated, more likely to be divorced, separated, or widowed, more likely to be current alcohol users, and more likely to be current marijuana users. Unexpectedly, household income and employment status were not associated with smoking status. Among current alcohol users, smokers consumed three times the number of drinks per month that nonsmokers consumed (p<.001). Among current marijuana users, smokers consumed more than five times the number of joints per month that nonsmokers consumed (p<.001). Overall, lower education levels, divorce, and alcohol and marijuana use were significantly associated with increased likelihood of smoking among this population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".