Subjective Well-Being among Empty-Nest Elderly and Its Related Factors：Taking Guangdong Province as an Example
Bibliographic record
Abstract
Objective: To explore the the status of happiness and social support of empty nesters in Guangdong Province and analyze the relationship between the above two variables.Method: Totally 1148 empty nesters (776 males, 734 females) from 5 cities in Guangdong province are selected by stratified random sampling and conducted with Memorial University of Newfoundland Scale of Happiness (MUNSH), Social Support Rating Scale (SSRS), Mini-Mental State Examination (MMSE) and a self-edited questionnaire on the general information.Results: The total score of MUNSH is (10.20±6.37). The total score and the scores of the 3 dimensions of objective support, subject support, the use of support in SSRS are (30.79±5.51), (9.24±2.37), (19.38±4.95) and (9.22±2.15) respectively. Multiple variable linear regression show that are positively associated with the total scores of MUNSH (B= .227, .115, .098, .158, .082, respectively, P< .05). was negatively associated with total score of MUNSH (B=-.097, P< .05).Conclusion: It suggests that the sort of leisure, gender, progress rank, family characteristics, such as family economic condition and father’s career may be related factors of undergraduates life satisfaction.
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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 | 0.000 | 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) | 0.001 | 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".