Rating Health and Rating Change: How Canadians Rate Their Health and Its Changes
Bibliographic record
Abstract
<b>Objectives:</b> We investigated the contribution of five health domains to self-rated health (SRH) cross-sectionally and longitudinally and whether these contributions differ by gender or age. <b>Methods:</b> Employing dominance analyses, we quantified the contributions of functioning, diseases, pain, mental health, and behavior to both SRH at a point in time and for changes in SRH using data from the Canadian National Population Health Survey (NPHS, 1994–2011). <b>Results:</b> Cross-sectionally and longitudinally, functioning was the most important health domain, followed by diseases and pain. There were no meaningful differences in the ranking by gender while functioning, diseases, and pain were more relevant in older cohorts. <b>Discussion:</b> Functioning, diseases, and pain systematically were the most important health domains in both cross-sectional and longitudinal analyses. While these results held for women and men, they were more salient for older adults. This points to a gender-invariant but age-graded process, confirming previous research with European data.
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How this classification was reachedexpand
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".