Bibliographic record
Abstract
OBJECTIVES: This article estimates the prevalence of insomnia among Canadians aged 15 or older, and factors related to it. Associations between insomnia and coping ability, work status, two-week disability days and life dissatisfaction are analyzed. DATA SOURCES: The data are from the 2002 Canadian Community Health Survey: Mental Health and Well-being. ANALYTICAL TECHNIQUES: Cross-tabulations were used to estimate the prevalence of insomnia by selected characteristics. Associations between these characteristics and insomnia, and between insomnia and selected negative situations, were examined in multivariate logistic regression models. MAIN RESULTS: In 2002, an estimated 3.3 million Canadians (13.4% of the household population aged 15 or older) had insomnia. Factors independently associated with insomnia included painful chronic conditions, activity limitations, mood and anxiety disorders, life stress, frequent use of alcohol or cannabis, obesity, and low education. Compared with those who did not have insomnia, people with insomnia were more likely to report negataive situations such as difficulty coping and not having a job.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.111 | 0.033 |
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".