Filial responsibility: does it matter for care-giving behaviours?
Bibliographic record
Abstract
ABSTRACT This paper examines the relationship between attitudes of filial responsibility and five different types of care-giving behaviours to parents among three cultural groups. It does so within an assessment of the relative importance of cultural versus structural factors for care-giving behaviours. Face-to-face interviews were conducted with 100 Caucasian-Canadians, 90 Chinese-Canadians and 125 Hong Kong-Chinese. Multiple regression analyses assessed the association of cultural and structural factors with behaviours among the total sample and each of the three cultural groups. Limited support was found for an association between care-giving attitudes and care-giving behaviours. Attitudes are related to emotional support only among the two Chinese groups as well as to financial support among Chinese-Canadian respondents and to companionship among Hong Kong-Chinese respondents. Attitudes are not the strongest predictors and are unrelated to assistance with basic and instrumental activities of daily living. However, cultural group per se is a strong predictor of care-giving behaviours as are: parental ill health, living arrangements, and relationship quality. This study suggests gerontological assumptions about the role of societal norms and personal attitudes in parental care-giving should be questioned. It also suggests the need for further inquiry into unpacking those aspects of ‘cultural group’ that are related to behavioural differences, and the importance of examining multiple types of care-giving behaviours and of distinguishing task-oriented helping behaviour from other types of assistance.
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".