Proteção social na América Latina e Caribe: mudanças, contradições e limites
Bibliographic record
Abstract
Recent studies suggest that governments in the majority of Latin American and Caribbean countries were able to expand social investments and introduce innovations in social protection policies in the last two decades with positive results in the actions' coverage and impact. However, the restrictions imposed by the current fiscal crisis and the rise of governments more ideologically aligned with the neoliberal discourse in various countries in the region point to a new retreat of the state from the social area, thereby compromising recent advances. The article aims to discuss the changes, contradictions, and limits of recent social protection standards in Latin America and the Caribbean. The discussion includes three items: a description of the history of social protection in the region, seeking to identify its principal historical periods and characteristics (benefits, target public, and financing); the social protection models that have been implemented in the region; and the specific case of health. We argue that although countries have adopted different solutions in the field of social protection, the policies' hybrid nature (with extensive private sector participation in the financing, supply, and management of services) and the prevalence of segmented models (with differential access according to individuals' social status) have been predominant traits in social protection in Latin America and the Caribbean, thus limiting the possibilities for greater equity and social justice.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".