SOCIOECONOMIC INFLUENCE ON THE HEALTH OF OLDER PEOPLE: ESTIMATES BASED ON TWO LONGITUDINAL SURVEYS
Bibliographic record
Abstract
There is a strong positive relationship between socioeconomic status (SES) and health, but identifying the direction of causation is difficult. This study exploits the longitudinal nature of two Canadian surveys, the Survey of Labour and Income Dynamics and the National Population Health Survey, to study the link from SES to health. For people aged 50 and older who are initially in good health we examine whether changes in health status over the next two to four years are related to prior SES, as represented by income and education. Although the two surveys were designed for quite different purposes the evidence they yield with respect to the probability of remaining in good health is strikingly similar. Both suggest that SES does play a role, that the differences across SES groups are quantitatively significant, that the differences increase with age, and that they are much same for men and women.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".