Home Care Services for Seniors: A Typology of Instruments and Administrative Burdens in Industrialized Countries
Bibliographic record
Abstract
Abstract This contribution has two key objectives. First, inspired by earlier studies in comparative welfare state and in (social) gerontology, we develop a conceptualization of autonomy that is rooted in its social dimensions. This concept is then deployed to assess its policy considerations within the field of home care, both with regards to access and generosity in 21 industrialized countries. Second, this contribution performs a comparative assessment of the key factors resulting in a prioritization of the social dimensions of home care and social services in long term care. This study involves an-depth analysis of policy instruments deployed by public authorities to enhance the (social) autonomy of older adults, complemented with interviews with policy makers in diverse home care policy settings (Canada, France, South Korea, Sweden, and the United States). As such, this study features an evaluation of the presence of social elements in the definition and supply of care needs across 21 countries. It leads to the construct of a social dimensions of autonomy index based upon these instruments and the budgetary prioritization of home care within long term care policies. Among core findings, one discovers broader access and more generous funding when home care responsibilities are firmly embedded at the local level.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| 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".