Who Foregoes Survivor Protection in Employer-Sponsored Pension Annuities?” The Gerontologist 45(1
Bibliographic record
Abstract
Purpose: Retirees in traditional pension plans must generally choose between single life annuities, which provide regular payments until death, and joint and survivor annuities, which pay less each month but continue to make payments to the spouse after the death of the retired worker. This article examines the payout decision and measures the share of married retirees with pension annuities who forego survivor protec-tion. Design and Methods: The analysis consists of aprobitmodel of thepensionpayout decision, basedon data from the 1992–2000 waves of the Health and Retirement Study. Results: More than one quarter (28%) of married men and two thirds of married women receiving employer-sponsored retirement annuities de-clined survivor protection. Men with small pensions and limited household wealth, men in better health than their spouses, and men whose spouses have pension coverage from their own employers are more likely than other men to reject survivor protection. Implica-tions: Most workers appear to make payout decisions by rationally balancing the costs and benefits of each type of annuity, suggesting that existing measures to encourage joint and survivor annuities are adequate. However, the growth in 401(k) plans, which are generally not covered by existing laws protecting spousal pension rights, may leave widows vulnerable.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".