Self-rated health among elders in different outmigration areas—a case study of rural Anhui, China
Bibliographic record
Abstract
China has been a rapid growing economy in recent decades. Part of its economic development engine comes from internal rural-urban migration. The decades-long rural-urban migration is the result of China’s long-lasting uneven development between its urban and rural areas and its income and resource distribution inequality. Rural Anhui is one of the most affected outmigration regions of China. The absence of young and middle-aged villagers changed its natural villages’ demographics. It broke the self-sufficient rural family structure and their traditional lifestyle with no societal infrastructure to replace family support. Meanwhile, it created aging communities—particularly in relatively poorer villages. This study investigates rural elder villagers’ perception of their physical health in the context of rural-urban migration. It explores the reality of the left-behind rural aging population—their real life challenges and regional disparities reflected in their self-rated health status: those who are living in a relatively poorer region (county) tend to have significantly lower self-rated health (SRH) scores than their counterparts in wealthier areas. Women tend to have lower SRH scores than men, and living alone elders tend to perceive their own physical health to be poorer than others. These findings also show that regional economic condition affect individual lives, women are more vulnerable, and healthy personal interaction is an essential element for wellbeing.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".