Gender Differences in Disability-Free Life Expectancy for Selected Risk Factors and Chronic Conditions in Canada
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
This article shows how mortality and morbidity patterns differ for women and men 45 years of age and older. The impact on disability-free life expectancy was calculated for selected risk factors and chronic conditions: low income, low education, abnormal body mass index, lack of physical activity, smoking, cancer, diabetes, and arthritis. For each factor, the expected number of years free of disability was calculated for men and women using multi-state life tables. In terms of disability-free life expectancy, the greatest impacts on affected women were for diabetes (14.1 years), arthritis (8.8 years), and physical inactivity (6.0 years), while for affected men, the greatest impacts were for diabetes (10.5 years), smoking (6.9 years), arthritis (6.5 years), and cancer (6.4 years). The implications of these results are discussed from the perspective of developing programs designed to improve population health status.
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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 | 0.000 | 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) | 0.000 | 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