Weekly work hours and health-related behaviours in full-time students.
Bibliographic record
Abstract
OBJECTIVES: This article examines associations between the number of hours of paid work and smoking, alcohol use, episodic heavy drinking and leisure-time physical activity among full-time students aged 15 to 17. DATA SOURCES: Analyses are based on data from the 2003 Canadian Community Health Survey and the 1994/95 to 2002/03 National Population Health Survey. ANALYTICAL TECHNIQUES: Selected characteristics and health-related behaviours of working and non-working students were compared. Logistic regression was used to examine relationships between average weekly hours at the main job and health-related behaviours, as well as maintenance of and changes in these behaviours, while controlling for possible confounders. MAIN RESULTS: Students who worked even a modest number of hours per week had higher odds of drinking alcohol regularly, and occasionally heavily, compared with those who had not worked. Students working any number of hours had higher odds of becoming regular drinkers within two years of their baseline interview. Longer working hours were associated with higher odds of smoking. Employed students had higher odds of being physically active in their leisure time. The influences of age, household income and urban/rural residence were taken into account.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".