Alcohol use and misuse: What are the contributions of occupation and work organization conditions?
Bibliographic record
Abstract
BACKGROUND: This research examines the specific contribution of occupation and work organization conditions to alcohol use and misuse. It is based on a social-action model that takes into account agent personality, structures of daily life, and macro social structures. METHODS: Data come from a representative sample of 10,155 workers in Quebec, Canada. Multinomial regression models corrected for sample design effect have been used to predict low-risk and high-risk drinking compared to non-drinkers. The contribution of occupation and work organization conditions (skill used, decision authority, physical and psychological demands, hours worked, irregular work schedule, harassment, unionization, job insecurity, performance pay, prestige) have been adjusted for family situation, social network outside the workplace, and individual characteristics. RESULTS: Compared to non-qualified blue-collars, both low-risk and high-risk drinking are associated with qualified blue-collars, semi-qualified white-collars, and middle managers; high-risk drinking is associated with upper managers. For constraints-resources related to work organization conditions, only workplace harassment is an important determinant of both low-risk and high-risk drinking, but it is modestly moderated by occupation. Family situation, social support outside work, and personal characteristics of individuals are also associated with alcohol use and misuse. Non-work factors mediated/suppressed the role of occupation and work organization conditions. CONCLUSION: Occupation and workplace harassment are important factors associated with alcohol use and misuse. The results support the theoretical model conceptualizing alcohol use and misuse as being the product of stress caused by constraints and resources brought to bear simultaneously by agent personality, structures of daily life, and macro social structures. Occupational alcohol researchers must expand their theoretical perspectives to avoid erroneous conclusions about the specific role of the workplace.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".