Bibliographic record
Abstract
OBJECTIVES: This article estimates the prevalence of depression among employed Canadians aged 25 to 64, and examines its association with work impairment, as measured by reduced work activity, mental health/general disability days, and work absence. DATA SOURCES: Data are from the 2002 Canadian Community Health Survey: Mental Health and Well-being and the longitudinal household component of the National Population Health Survey (1994/1995 to 2002/2003). ANALYTICAL TECHNIQUES: Cross-tabulations were used to estimate and determine factors associated with the prevalence of depression among the employed population. Multiple logistic regression was used to examine associations between depression and work impairment while controlling for other variables. Longitudinal data for 1994/1995 to 2002/2003 were used to examine the temporal sequence of depression and work impairment. MAIN RESULTS: In 2002, almost 4% of employed people aged 25 to 64 had had an episode of depression in the previous year. Crosssectional analysis indicates that these workers had high odds of reducing work activity because of a long-term health condition, having at least one mental health disability day in the past two weeks, and being absent from work in the past week. Longitudinally, depression was associated with reduced work activity and disability days two years later.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".