Measuring Unemployment Insurance Generosity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Unemployment insurance policies are multidimensional objects, with variable waiting periods, eligibility duration, benefit levels, and asset tests, making intertemporal or international comparisons very difficult. Furthermore, labor market conditions, such as the likelihood and duration of unemployment, matter when assessing the generosity of different policies. In this article, we develop a new methodology to measure the generosity of unemployment insurance programs with a single metric. We build a first model with all characteristics of the complex unemployment insurance policy. Our model features heterogeneous agents that are liquidity constrained but can self-insure. We then build a second model, similar in all aspects but one: the unemployment insurance policy is one-dimensional (no waiting periods, eligibility limits, or asset tests, but constant benefits). We then determine which level of benefits in this second model makes society indifferent between both policies. We apply this measurement strategy to the unemployment insurance program of the United Kingdom.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 it