Social Security and Retirement Programs Around the World: The Capacity to Work at Older Ages – Introduction and Summary
Bibliographic record
Abstract
This is the introduction and summary to the seventh phase of an ongoing project on Social Security Programs and Retirement Around the World.The project compares the experiences of a dozen developed countries and uses differences in their retirement program provisions to explore the effect of SS on retirement and related questions.The first three phases of this project document that: 1) incentives for retirement from SS are strongly correlated with labor force participation rates across countries; 2) within countries, workers with stronger incentives to delay retirement are more likely to do so; and 3) changes to SS could have substantial effects on labor force participation and government finances.The fourth volume explores whether higher employment among older persons might increase youth unemployment and finds no link between the two.The fifth and sixth volumes focus on the disability insurance (DI) program, finding that changes in DI participation are more closely linked to DI reforms than to changes in health and that reducing access to DI would raise labor supply.This seventh phase of the project explores whether older people are healthy enough to work longer.We use two main methods to estimate the health capacity to work, asking how much older individuals today could work if they worked as much as those with the same mortality rate in the past or as younger individuals in similar health.Both methods suggest there is significant additional health capacity to work at older ages.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".