Bibliographic record
Abstract
OBJECTIVES: This article describes stress levels among the employed population aged 18 to 75 and examines associations between stress and depression. DATA SOURCES: Data are from the 2002 Canadian Community Health Survey: Mental Health and Well-being and the longitudinal component of the 1994/95 through 2002/03 National Population Health Survey. ANALYTICAL TECHNIQUES: Stress levels were calculated by sex, age and employment characteristics. Multivariate analyses were used to examine associations between stress and depression in 2002, and between stress and incident depression over a two-year period, while controlling for age, employment characteristics, and factors originating outside the workplace. MAIN RESULTS: In 2002, women reported higher levels of job strain and general day-to-day stress. When the various sources of stress were considered simultaneously, along with other possible confounders, for both sexes, high levels of general day-to-day stress and low levels of co-worker support were associated with higher odds of depression, as was high job strain for men. Over a two-year period, men with high strain jobs and women with high personal stress and low co-worker support had elevated odds of incident depression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".