Rising Disability Payments: Are Cuts to Workers' Compensation Part of the Story?
Bibliographic record
Abstract
There has been a large increase in the number of workers receiving Social Security Disability Insurance (DI) over the last quarter century. While most of this increase is explained by well-known demographic factors, such as the growing number of women in the workforce and the aging of the baby boomers, there is considerable concern that workers are increasingly choosing to collect DI benefits as an alternative to working. This concern has figured prominently in the debate over plans to maintain full funding for the DI program beyond the projected DI trust fund depletion date in late 2016.This paper examines the extent to which cuts in state workers' compensation (WC) benefits may have contributed to the rise in DI awards. To some extent, these programs may be seen as alternative sources of support for workers with job-related injuries. Insofar as injured workers are less able to receive WC benefits, they may be more likely to turn to the DI program. At the national level, there is a clear correlation between the sharp decline in WC benefits over the last quarter century and the rise in DI benefits. This paper examines whether there could be a causal relationship between the reduction in WC benefits and the rise in DI benefits by examining state-level data.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".