THE INDIVIDUAL AND STRUCTURAL DETERMINANTS OF AGING WELL IN CANADA AND MEXICO
Bibliographic record
Abstract
The literature suggests that successful aging is largely determined by health behaviors and the social and physical environment of older adults. For this presentation, we examined the determinants of a person-centered index of aging well (0–100), as inspired by the determinants of the WHO concept of active aging, namely socioeconomic, behavioral, and environmental determinants. In both contexts, older participants were less likely to age well. Those with less than very sufficient income also had lower scores on the index. In Canada, smoking (past and present) was associated with lower scores, while physical exercise had a small but significant positive association. In Mexico, men aged well significantly more than women, as did those with more education and those who exercised at least 60 minutes a week. This presentation sheds light on modifiable determinants of aging well that can be addressed through health and social policies, particularly health behaviors and income sufficiency.
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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 | 0.000 | 0.000 |
| 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 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".