Long‐Term Care Across Europe and the United States: The Role of Informal and Formal Care
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Large cross‐country variation in long‐term‐care (LTC) policy in conjunction with household‐level data on caregiving provides a valuable laboratory for policy analysis. However, there is a lack of comprehensive cross‐country data on how care is provided. In order to close this gap, we draw on data from the Survey of Health, Ageing, and Retirement in Europe (SHARE) and the Health and Retirement Study (HRS) in the United States. Because care hours are missing for some care forms (especially for nursing‐home residents), we propose a selection model to impute these. The model allows selection into care forms to differ by country. Our estimates imply that nursing‐home residents have higher care needs, even when conditioning on observed characteristics. In contrast to the bulk of the literature, we also take into account care provision from persons in the same household, and we find that this contributes one‐third of all care hours. Informal‐care provision in Europe follows a steep North–South gradient, with the United States falling in between Central European and Southern European countries. The results are robust to alternative imputation schemes.
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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