The Long-term Health Effects of Mass Political Violence: Evidence From China’s Cultural Revolution
Bibliographic record
Abstract
There is much interest in the causes of several adverse health outcomes in middle and old age. In searching for new explanations for adverse health outcomes later in life, researchers have started to look beyond behavioural risk factors to examine the effect of shocks to health in utero and in childhood on health in old age. In this paper we extend this literature to examine the long-term health effects of mass political violence experienced in utero and in childhood using China’s Cultural Revolution as a natural experiment. We find that individuals who were in utero in the Cultural Revolution have reduced lung capacity later in life, but we find no evidence that being in utero has adverse effects on other health indicators later in life. We find more evidence that being an adolescent in the Cultural Revolution has an adverse effect on health later in life. Specifically, we find that individuals who were adolescents in the Cultural Revolution have higher blood pressure and reduced ability to engage in activities of daily living later in life. We also find that males who were adolescents in the Cultural Revolution have reduced cognitive skills later in life, while females who were adolescents in the Cultural Revolution have reduced lung capacity in middle and old age. specific recommendations for the Canadian context.
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.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".