The effects of a psychosocial dimension of socioeconomic position on survival: occupational prestige and mortality among US working adults
Bibliographic record
Abstract
The association between education or income and mortality has been explored in great detail. These measures capture both the effects of material disadvantage on health and the psychosocial impacts of a low socioeconomic position on health. When explored independently of educational attainment and income, occupational prestige - a purely perceptual measure - serves as a measure of the impact of a psychosocial phenomenon on health. For instance, a fire-fighter, academician or schoolteacher may carry the social benefits of a higher social status without actually having the income (in all cases) or the educational credentials (in the case of the fire-fighter) to match. We explored the independent influence of occupational prestige on mortality. We applied Cox proportional hazards models to a nationally representative sample of over 380,000 US workers who had worked at any time between 1986 and 1994 with mortality follow up through 2002. We found that occupational prestige is associated with a decrease in the risk of all-cause, cancer, cardiovascular and respiratory-related mortality after controlling for household income and educational attainment. We further investigated the question of whether the effects of prestige are moderated by sex and broader occupational groupings. Prestige effects operate in white-collar occupations for men only and within service occupations for all workers.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".