Two worlds of retirement income: A comparative analysis of retirement-income outcomes using the Luxembourg Income Study
Bibliographic record
Abstract
This paper examines whether retirement-income systems allow older individuals to enjoy socially acceptable income levels independent of paid work (decommodification) and the family (defamilialization). Little research has investigated the degree to which decommodification and defamilialization levels, whether from public or private sources, vary by age. We employ the Luxembourg Income Study to compare Canada, Finland, France, Germany, Sweden, and the United States. This study applies the Pythagorean Theorem to measure autonomy, then explores whether members experience decommodification and defamilialization levels predicted for their system. Our results show Sweden and Canada provide highest autonomy levels, Finland, France and the United States provide moderate levels, and Germany low levels. We find age polarity: Swedes and Finns who are decommodified and defamilialized tend to be younger than age 70. Individuals who are decommodified and defamilialized through the retirement-income systems of Canada, France, Germany, and the United States, however, tend to be older than age 75. Some experts contend systems have converged, yet retirement-income systems do not produce similar autonomy levels. Outcomes for system members vary by age, suggesting reformers cannot take 'one size fits all' approaches.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".