Bibliographic record
Abstract
OBJECTIVES: This article describes the characteristics of shift workers and compares stress factors and health behaviours of shift and regular daytime workers. Based on an analysis of people followed over four years, associations between the incidence of chronic conditions and changes in psychological distress levels are explored in relation to working shift. DATA SOURCES: Data are from the 2000/01 Canadian Community Health Survey, the longitudinal (1994/95, 1996/97 and 1998/99) and cross-sectional (1994/95) components of the National Population Health Survey, and the Survey of Work Arrangements (1991 and 1995). ANALYTICAL TECHNIQUES: Cross-tabulations were used to profile shift workers and to compare some of their health behaviours and sources of stress with those of regular daytime workers. Multivariate analyses were used to examine associations between shift work and the incidence of chronic conditions and changes in psychological distress levels over four years, controlling for other potential confounders. MAIN RESULTS: Men who worked an evening, rotating or irregular shift had increased odds of reporting having been diagnosed with a chronic condition over a four-year period. For both sexes, an evening shift was associated with increases in psychological distress levels over two years.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.031 | 0.003 |
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".