Bibliographic record
Abstract
The purpose of this study is to examine the institutional development of means-tested benefits over the last four decades in a comparative perspective. The countries included in the study are Canada, Germany, Sweden, the United Kingdom and the Untied States. Since a main objective of means-tested benefits is to mitigate and alleviate poverty, the comparisons and evaluations presented in the study are based on the adequacy of benefits, that is, the extent to which provisions are provided at levels sufficient to allow recipients to escape poverty. The long time frame of the study also gives an opportunity to relate to the ongoing theoretical discussion about potential differences in the development of means-tested benefits and social insurance entitlements. Here, two questions are addressed: the extent to which the development of means-tested benefits describes a different pattern than social insurance provisions, and the extent to which means-tested benefits are more prone to cutbacks than social insurance entitlements. The empirical analyses combine institutional information on the level of means-tested benefits with micro-level income data from the Luxembourg Income Study. Over the whole period covered, the development of means-tested benefits resembles more than diverges form that observed in the area of social insurance. Furthermore, despite cutbacks in means-tested benefits in recent years, there is no clear evidence that means-tested benefits are more resistant to retrenchment than social insurance provisions. On the contrary, means-tested benefits seem to be more vulnerable to cutbacks, particularly in Germany and Sweden. Although the curtailments in means-tested provisions in recent years have had negative consequences for their capacity to alleviate poverty, the adequacy of benefits has generally been greatest in Sweden and the United Kingdom, followed by Germany, Canada and the United States.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".