Does Major Illness Cause Financial Catastrophe?
Bibliographic record
Abstract
OBJECTIVE: We examine the financial impact of major illnesses on the near-elderly and how this impact is affected by health insurance. DATA SOURCES: We use RAND Corporation extracts from the Health and Retirement Study from 1992 to 2006.(1) STUDY DESIGN: Our dependent variable is the change in household assets, excluding the value of the primary home. We use triple difference median regressions on a sample of newly ill/uninsured near elderly (under age 65) matched to newly ill/insured near elderly. We also include a matched control group of households whose members are not ill. RESULTS: Controlling for the effects of insurance status and illness, we find that the median household with a newly ill, uninsured individual suffers a statistically significant decline in household assets of between 30 and 50 percent relative to households with matched insured individuals. Newly ill, insured individuals do not experience a decline in wealth. CONCLUSIONS: Newly ill/uninsured households appear to be one illness away from financial catastrophe. Newly ill insured households who are matched to uninsured households appear to be protected against financial loss, at least in the near term.
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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 | 0.000 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".