Bibliographic record
Abstract
Welfare state supporters typically contend that social-welfare programs boost the incomes of low-earning households. Critics argue that, over time, such programs reduce the growth of economic output and/or employment. As a result, redistribution may produce stagnant or even declining real incomes for those at the bottom. A number of recent cross-country empirical studies have found that welfare state generosity is strongly associated with low relative poverty, but there has been virtually no cross-national analysis of welfare state effects on absolute poverty, which is at the heart of the critics' argument. I use Luxembourg Income Study (LIS) data to examine the relationship between welfare state generosity and absolute poverty for working-age households in Sweden, Germany, the United Kingdom, Canada, and the United States from the mid-1970s to 2000. Consistent with the critics' charge, the countries with the most generous welfare states experienced rising pretax-pretransfer absolute poverty. Yet the actual causal significance of welfare state generosity in this development is questionable. On the whole, the comparative evidence seems more consistent with the view of welfare state supporters. Germany, with its relatively generous social-welfare programs, had the lowest levels of both pretax-pretransfer and posttax-posttransfer absolute poverty throughout the period. And the sharpest decline in posttax-posttransfer absolute poverty, as well as the second lowest level as of 2000, were found in Sweden, the country with by far the most generous welfare state.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".