Changing demographic characteristics and motives for suicide in rural China, 1980–2009
Bibliographic record
Abstract
Given the absence of a complete vital registration system in rural China, a unique large-scale ethnographic study was conducted to examine the incidents, trends, demographic characteristics and motives for suicide. This study was implemented in 55 villages from 23 prefectures in 11 provinces. Family members, relatives, friends, and neighbours of suicide victims, and key informants (cadres, village doctors, funeral/burial coordinators, and primary-school teachers) in a village were interviewed to obtain and verify the detailed life history of each suicide victim since the 1980s. Among 849 suicide victims we investigated, we found more female than male victims, which is reversed gender difference in traditional suicide literature. Both number of elderly suicide victims and suicide motives related to livelihood have dramatically increased in recent years. There were more middle-aged victims during the years 1995–9. This study suggests that suicide in rural China remains an urgent and enormous public health problem. Findings from this research cast doubt on the well-known sex disparity in China’s suicide victims and suggest a possible epidemic of elderly suicides in rural China. The shifting pattern of suicide motives tracks socio-cultural changes in rural China.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".