Dorling D. Geographical inequalities of mortality by income in two developed island countries: a cross-national comparison of Britain and Japan. Soc Sci Med 2005;60:2865–75
Bibliographic record
Abstract
In this paper we examine the ecological relations between household income distribution and age-grouped mortality in Britain and Japan. Comparable datasets were prepared in terms of age intervals of mortality, household income intervals and geographical units for years around 1990. Then we conducted series of regression analyses to associate absolute and relative income indices with age and sex-specific standardized mortality ratios (SMRs). The results are as follows: (1) In Britain mortality is lower where inequalities in income are lower, while in Japan there is no obvious relationship. It is, however, apparent that- just as in the case of the USA and Canada- Britain and Japan appear to merge and appear part of greater pattern when considered as series of city regions. Thus an overall global relationship between income inequality and mortality may exist. To assess such global relationship, further studies using cross-national regional datasets covering wide rage of rich nations are desirable. (2) Income–mortality relations are consistent among different age–sex groups in Britain, but there are substantial differences in the relationships as revealed between different demographic groups in Japan. In particular, while absolute income levels are correlated negatively with mortality of working-age men in both countries, mortality of elderly people in Japan is higher where absolute income is higher. This indicates the different historical contexts to the health divides these two different geographical contexts, but further consideration of more historically nuanced understanding of income–mortality relations is required.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".