Educational inequalities in longevity in 18 OECD countries
Bibliographic record
Abstract
Abstract This paper assesses inequality in longevity across education and gender groups in 23 OECD countries around 2011. Data on mortality rates by age, gender, educational attainment, and, for 17 countries, cause of death were collected from national sources, with similar treatment applied to all countries in order to derive comparable measures of longevity at age 25 and 65 by gender and education. These estimates show that, on average, the gap in life expectancy between high and low-educated people is 7.6 years for men and 4.8 years for women at age 25 years, and 3.6 years for men and 2.6 years for women at age 65. At the age of 25, the gap in life expectancy between high and low-educated people varies between 4.1 years (in Canada) and 13.9 years (in Hungary) for men, and between 2.5 years (in Italy) and 8.3 years (in Latvia) for women; in the United States, the gap is 10.0 years for men and 7.0 years for women. Cardiovascular diseases are the first cause of death for all gender and education groups after age 65 years, and the first cause of mortality inequality between the high and low-education elderly.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".