Specialization between Family and State Intergenerational Time Transfers in Western Europe
Bibliographic record
Abstract
Intergenerational time transfers can be differentiated and divided into two support forms: help and care activities. Adult children support their elderly parents with more or less intensive and widely differing transfers ranging from help with household chores and paperwork to personal care. However, elderly people are also an important source of intergenerational support, as they help their children by looking after the grandchildren for example. In general intergenerational solidarity patterns are influenced by opportunity, need, family and culturalcontextual structures, which have differing impacts on help and care: Care is mainly depending on the need structures of the receiver while help activities to parents and children are primarily influenced by the opportunity structures of the giver. Additionally, using the SHARE data, logistic multilevel modeling allows national help and care levels to be traced back to the provision of public services. The empirical findings support the “specialization hypothesis”: A higher national level of social services coincides with less intensive help and more demanding care. Well-developed welfare states thus lower the risk of an overburdening of the family and secure the overall support of older people and young families through efficient collaboration between family and state.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".