The family structural and socioeconomic characteristics of the family well‐being of Hong Kong people
Bibliographic record
Abstract
Abstract This study investigated the family well‐being of Hong Kong people through a randomized telephone survey of 2008 adults, using a standardized six‐domain index developed specifically for this population. Multiple regression analyses were conducted to examine the heterogeneity of family well‐being according to demographic, family structural, and socioeconomic characteristics. The results showed significant gender and age differences in people's perception of family well‐being. Education, family income, and hiring a domestic helper were also associated with higher family wellbeing index scores, while the impacts of economic activity status, family size, and caring for young children were found to be insignificant. The impact of marital status was somewhat complicated. This article discusses variations observed in the influence of the set of demographic, family structural, and socioeconomic characteristics on overall and domain‐specific family well‐being. Implications for future studies and for social policy formulation and social work practice are suggested.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".