Bibliographic record
Abstract
We analyze the evolution of inequality in mortality in Spain during 1990-2014. We focus on age-specific mortality and consider inequality across narrowly defined geographical areas, ranked by average socioeconomic status. We find substantial decreases in mortality over the past 25 years for all age groups, which were particularly pronounced for men, resulting in a sizeable reduction in the gender gap in mortality. Inequality in mortality also decreased during this period, including during the recent recession, so that by the 2010 s mortality presents a flat socioeconomic gradient for most age groups. Compared to the US and Canada, decreases in mortality have been larger in Spain, and inequality is the lowest of the three countries. We find essentially no change in inequality among the elderly, in contrast to the increase found in the US.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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; both teacher heads agree on what is shown here.
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".