Bibliographic record
Abstract
OBJECTIVES: This article examines changes in the health status of Canadian adults between 1978/79 and 1996/97. DATA SOURCES: Data are from the the Canadian Vital Statistics Data Base, the 1991 General Social Survey, the 1978/79 Canada Health Survey (CHS), and the 1996/97 National Population Health Survey (NPHS). ANALYTICAL TECHNIQUES: Age-specific mortality rates are presented for 1978 and 1996. The cumulative incidence of heart disease is shown for 1991. Cross-sectional comparisons of prevalence rates for selected chronic conditions, activity limitation, disability days, smoking and overweight are shown for 1978/79 and 1996/97. Multiple logistic regression models were used to test differences in odds ratios for the chronic conditions and for activity limitation between the CHS and the NPHS. SUDAAN, which accounts for the complex survey design, was used to estimate standard errors of the prevalence and of the coefficients in the logistic model. MAIN RESULTS: Lower mortality rates and lower prevalence of heart disease, high blood pressure, arthritis and activity limitation suggest that recent cohorts are healthier than previous cohorts. When the age effect was controlled along with education and income, the odds of having these conditions were generally lower for each successive cohort, and lower in the mid-1990s than in the late 1970s. However, the odds of having diabetes were higher in 1996/97 than in 1978/79, and higher among more recent cohorts than among earlier cohorts.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".