Male-Dominated Occupations and Substance Use Disorders in Young Adulthood
Bibliographic record
Abstract
This article examined associations between male-dominated occupations and substance use disorders in young adulthood, accounting for adolescent experiences of work intensity (more than 15 hr a week at 16 to 17 years of age) and substance use (i.e., smoking, heavy drinking, cannabis, and illicit drug use). The moderating effects of biological sex and coming from a family with a low socioeconomic status (SES) were also assessed. Data were from a 10-year prospective study of community-based youth aged 12–18 in 2003 (T1; N = 662; 48% male; M age = 15.5, SD = 1.9). Their occupations at ages 22–29 were categorized so that higher scores indicated more male-dominated occupations. Young adults in male-dominated occupations (more than 75% males) had lower education, worked in less prestigious occupations, and earned higher hourly wages than those in the other gendered-occupation groups. Work intensity in high school was associated with substance use at ages 18–25 and substance use was also associated with alcohol- and cannabis-use disorder symptoms and illicit drug use in young adulthood (ages 22–29). Adding to these effects, employment in a male-dominated occupation was associated with more cannabis-use disorder symptoms for the low, but not the high SES group. Public health messages need greater focus on preventing substance use disorders among individuals employed in male-dominated jobs in young adulthood. Efforts to promote self-assessment of problematic substance use and motivation to change may be particularly important for young workers.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".