Theorizing the relationship between welfare state regimes and health using comparative national-level health measure
Bibliographic record
Abstract
Welfare state regime typologies have proven useful in analyzing the impacts of various social policy structures on health. Recently, several welfare state regime typologies have been identified as having relevance for the study of health. However, comparative research examining the relationships between population health and welfare states has relied disproportionately upon child-based health measures – in particular, infant mortality rate, under-5 mortality and low birthweight. Using hierarchical cluster analysis, eta, and ANOVA, this paper demonstrates that these commonly-used child-based health measures are more strongly correlated with welfare state regime typologies than other measures of population health. Adult mortality, life expectancy and disease measures are not strongly correlated with welfare state regime typologies, and greater use of such measures in comparative research may problematize the often-observed correlations between welfare states and health. The paper argues that the disproportionate use of child-based health measures may therefore present an incomplete picture of the connections between welfare state regimes and population health. Implications for theorizing the relationship between welfare states and health are discussed.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".