The Income and Wealth Packages of Older Women in Cross-National Perspective
Bibliographic record
Abstract
OBJECTIVES: We assess the income and wealth packages of older women's (age 65+ years) households and the extent to which low income is paired with low wealth, across a group of six high-income countries. METHODS: We use data on income and net worth from the Luxembourg Wealth Study, a new cross-national microdatabase. We define income poverty as having household income less than 50% of the national median and asset poverty as holding financial assets equivalent to less than 6 months of income at the poverty threshold. RESULTS: Older women typically have less income than do members of younger households at the national median, but their wealth holdings are generally much higher than their country's median wealth holdings. Older women's households in the United States report the highest net worth across these countries, in part because older American women have comparatively high rates of homeownership. However, American older women are also substantially more likely to be income poor. They also report high levels of asset poverty, as do women across all our comparison countries, with Sweden as a partial exception. DISCUSSION: Further research is needed to identify the most vulnerable subgroups, to integrate analyses of necessary expenditures, and to assess policy implications.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".