The Subjective Well-Being of Elderly Migrants in Dongguan: The Role of Residential Environment
Bibliographic record
Abstract
To examine the association between community and individual-level residential environment in relation to subjective well-being (SWB) amongst 470 elderly migrants in China, this community-based survey was conducted. The manner and extent to which the SWB of these elderly migrants is influenced by their residential environment was the main area of focus. The Scale of Happiness of the Memorial University of Newfoundland was used to assess SWB. SWB was found to be associated significantly with environmental factors such as social cohesion, closeness to the nearest facility of recreation, the density of recreation facilities, financial facilities, and health facilities. The health facility density (B = 0.026, p < 0.001) and recreation facility density (B = 0.032, p < 0.001) had positive associations with SWB, while financial facility density (B = −0.035, p < 0.001) had a negative association. The primary determinants of SWB for elderly migrants ranged from individual to environmental factors. Through the enhancement of the accessibility to healthcare facilities in their new homes, in addition to promoting recreational activities and social services, the SWB amongst elderly migrants could be enhanced further.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".