A comparative study of sociocultural factors and young adults' smoking in two midwestern communities
Bibliographic record
Abstract
Young adults were the only age group to defy the downward trend in cigarette use seen in the 1980s and 1990s. To help explain this phenomenon, we conducted an exploratory study to examine the association between the sociocultural contexts of young adults' everyday lives and their smoking attitudes and behaviors. "Context" was operationalized by (a) including students and nonstudents in the study population, and (b) selecting two distinctly different areas of Minnesota for examination. The study sites were Hibbing and environs (Range), the sparsely populated hub of the state's once-thriving iron ore industry, and the Twin Cities metropolitan area (Metro), center of state government, finance, transportation, education, and industry. This report focuses on the first phase of the study, which consisted of a computer-assisted telephone interview of 995 randomly selected young adults, aged 18-24. Approximately equal numbers of students and nonstudents were selected from each site. Exploratory factor analysis yielded four distinct scales related to alcohol consumption and partying (Drinking Behavior), the social attractiveness and utility of smoking (Social Utility), outdoor recreation (Outdoor Rec), and media use and hours of free time. We decided not to use the media and free time scale, however, because of its low Cronbach alpha (.42). We used polynomial logistic regression to evaluate the association between smoking status, gender, student status, location (Range vs. Metro), and the three retained scales. Results indicated that living on the Iron Range (OR = 2.6), being female (OR = 1.3), and scoring higher on the Social Utility scale (OR = 3.06) increased the risk of smoking, whereas being a student (OR = 0.53) decreased the risk substantially.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".