A Perfect Storm? Welfare, Care, Gender and Generations in Uruguay
Bibliographic record
Abstract
This article claims that welfare states modelled on a contributory basis and with a system of entitlements that assumes stable two-parent families, a traditional breadwinner model, full formal employment and a relatively young age structure are profoundly flawed in the context of present-day challenges. While this is true for affluent countries modelled on the Bismarckian type of welfare system, the costs of the status quo are even more devastating in middle-income economies with high levels of inequality. A gendered approach to welfare reform that introduces the political economy and the economy of care and unpaid work is becoming critical to confront what may very well become a perfect storm for the welfare of these nations and their peoples. Through an in-depth study of the Uruguayan case, the authors show how the decoupling of risk and protection has torn asunder the efficacy of welfare devices in the country. An ageing society that has seen a radical transformation of its family and labour market landscapes, Uruguay maintained during the 1980s and 1990s a welfare state that was essentially contributory, elderly and male-oriented, and centred on cash entitlements. This contributed to the infantilization of poverty, increased the vulnerability of women and exacerbated fiscal stress for the system as a whole. Furthermore, because of high levels of income and asset inequality, the redistribution of risk between upper- and lower-income groups presented a deeply regressive pattern. The political economy of care and welfare has begun to change in the last decade or so, bringing about mild reforms in the right direction; but these might prove to be too little and too late.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".