Welfare state, labour market inequalities and health. In a global context: An integrated framework. SESPAS report 2010
Bibliographic record
Abstract
Since the nineteen seventies, high- and low-income countries have undergone a pattern of transnational economic and cultural integration known as globalization. The weight of the available evidence suggests that the effects of globalization on labor markets have increased economic inequality and various forms of economic insecurity that negatively affect workers’ health. Research on the relation between labor markets and health is hampered by the social invisibility of many of these health inequalities. Empirical evidence of the impact of employment relations on health inequalities is scarce for low-income countries, small firms, rural settings, and sectors of the economy in which "informality" is widespread. Information is also scarce on the effectiveness of labor market interventions in reducing health inequalities. This pattern is likely to continue in the future unless governments adopt active labor market policies. Such policies include creating jobs through state intervention, regulating the labor market to protect employment, supporting unions, and ensuring occupational safety and health standards. A partir de los años 1970, los países de altos y bajos ingresos entraron en una fase de integración económica y cultural conocida como «globalización». La evidencia disponible muestra que los efectos de la globalización en los mercados de trabajo acarrea incrementos en desigualdades y varias formas de inseguridad económica que afectan negativamente a la salud de los trabajadores. La investigación sobre la relación entre los mercados laborales y salud se ve perjudicada por la invisibilidad social de estas desigualdades en salud. La evidencia empírica sobre las relaciones de empleo y su impacto en las desigualdades de salud es escasa en los países con ingresos bajos, las pequeñas empresas, los entornos rurales y los sectores de la economía donde la «informalidad» es generalizada. La información disponible es también escasa sobre la efectividad de las intervenciones en el mercado laboral para reducir las desigualdades en salud. Esta situación no parece que vaya a mejorar en un futuro cercano, a menos que los gobiernos adopten políticas de mercado laboral activas, incluyendo la creación de empleo, la regulación de los mercados laborales para proteger el empleo, la ayuda a los sindicatos, y aseguren el cumplimiento de las leyes de seguridad y salud laborales.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".