Elderly Demand for Family-based Care and Support: Evidence from a Social Intervention Strategy
Bibliographic record
Abstract
This paper examines the influence of the national health insurance scheme on elderly demand for family-based care and support. It contributes to the growing concern on the rapid increase in the elderly population globally using micro-level social theory to examine the influence the health insurance has on elderly demand for family support. A qualitative case study approach is applied to construct a comprehensive and thick description of how the national health insurance scheme influences the elderly in their demand for family support.Through focused interviews and direct observation of six selected cases, in-depth information on primary carers, living arrangement and the interaction between the health insurance as structure and elders as agents are analyzed. The study highlights that the interaction between the elderly and the national health insurance scheme has produced a new stratum of relationship between the elderly and their primary carers. Consequently, this has created equilibrium between the elderly demand for support and support made available by their primary carers. As the demand of the elderly for support is declining, supply of support by family members for the elderly is also on the decline.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".