Welfare state regimes, health and health inequalities in adolescence: a multilevel study in 32 countries
Bibliographic record
Abstract
Comparative research on health and health inequalities has recently started to establish a welfare regime perspective. The objective of this study was to determine whether different welfare regimes are associated with health and health inequalities among adolescents. Data were collected from the 'Health Behaviour in School-aged Children' study in 2006, including 11- to 15-year-old students from 32 countries (N = 141,091). Prevalence rates and multilevel logistic regression models were calculated for self-rated health (SRH) and health complaints. The results show that between 4 per cent and 7 per cent of the variation in both health outcomes is attributable to differences between countries. Compared to the Scandinavian regime, the Southern regime had lower odds ratios for SRH, while for health complaints the Southern and Eastern regime showed high odds ratios. The association between subjective health and welfare regime was largely unaffected by adjusting for individual socioeconomic position. After adjustment for the welfare regime typology, the country-level variations were reduced to 4.6 per cent for SRH and to 2.9 per cent for health complaints. Regarding cross-level interaction effects between welfare regimes and socioeconomic position, no clear regime-specific pattern was found. Consistent with research on adults this study shows that welfare regimes are important in explaining variations in adolescent health across countries.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".