Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This landmark study of the material well-being of older people in nine OECD countries -- Canada, Finland, Germany, Italy, Japan, the Netherlands, Sweden, the United Kingdom and the United States -- uses a wealth of new data to shed light on the challenges that face policy-makers as they anticipate the coming retirement of the baby-boom generation. The findings are often surprising. In all the countries surveyed, policies have been fundamentally successful: older people at all income levels tend to maintain or even increase their material standards of living once they stop working. This happens despite large differences in approaches to public policy, including the size of public pensions. The systems that provide resources to older people are considerably more complex than is usually taken into account in policy-making, and the effects of policy, while large, are less direct than often thought. Demography and changing labour market patterns make reforms to these systems imperative. The challenge is to make needed changes without undermining past success. This is difficult, but entirely possible; the payoffs from relatively small changes in the balance between work and retirement could be particularly large. The study examines the many diverse ways in which the nine countries are tackling this challenge and the lessons that have been learned from their experiences. It provides invaluable evidence for policy-makers, researchers and citizens concerned about the challenges posed for societies by ageing populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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