Retirement Responses to Early Social Security Benefit Reductions
Why this work is in the frame
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Bibliographic record
Abstract
This paper evaluates potential responses to reductions in early Social Security retirement benefits. Using the Health and Retirement Study (HRS) linked to administrative records, we find that Social Security coverage is quite uneven in the older population: one-quarter of respondents in their late 50's lacks coverage under the Disability Insurance program, and one-fifth lacks coverage for old-age benefits. Among those eligible for benefits, respondents who subsequently retired early appear quite similar initially to those who later filed for normal retirement benefits, but both groups were healthier and better educated than those who later filed for disability benefits. Next we investigate the potential impact of curtailing, and then eliminating, early Social Security benefits. A life-cycle model of retirement behavior provides estimated parameters used to simulate the effects of cutting early Social Security benefits on retirement pathways. We find that cutting early Social Security benefits would boost the probability of normal retirement by twice as much as it would the probability of disability retirement.
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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 | 0.013 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it