Mass Relocation and Depression Among Seniors in China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The study applies the stress process model to investigate the relationship between state-organized relocation (mass internal migration) and depression among older people in a rural region of Central China. The study is based on primary data that our research team collected on 613 respondents from 25 villages in November-December 2011 and 507 respondents from 36 villages in March-April 2013. Two-stage probit least squares models assess the impact of relocation on depression and whether social support influences this relationship. Our findings demonstrate that migrants have higher levels of depression than nonmigrants, after controlling for selection into migration and risk factors. However, postmigration losses of emotional, instrumental, and financial support do not account for the gap in depression between migrants and nonmigrants. Levels of depression are similar between nonmigrants and migrants relocated for infrastructure projects, poverty alleviation, or disaster management. Only migrants relocated to conserve sensitive ecological areas have higher levels of depression than nonmigrants. This suggests that project-induced displacement is not as detrimental for the mental health of seniors as previous studies demonstrate it is for younger people. Agency is an important factor in postmigration outcomes. Migrants who can self-determine their place of resettlement have more favorable outcomes than others.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| 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 it