Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it