Intergenerational reproduction and self-assessed mental health in adulthood in China
Bibliographic record
Abstract
Physical and mental health disparities by socioeconomic status in China are well documented but the effects of the intergenerational reproduction in socioeconomic status on adult mental health have received little attention to date. We utilized cross-sectional data from the 2017 Chinese General Social Survey to examine the significance of intergenerational socioeconomic reproduction for differences in self-assessed mental health in a national sample of Chinese adults between the ages of 23 and 65. We documented substantial elasticities between the socioeconomic status of the survey respondents and their parents: father's education, mother's education and childhood social class were all associated with both respondent education and respondent household income. We also found that associations between parental socioeconomic status and their adult children's self-assessed mental health were partly explained by the children's own socioeconomic status. However, these pathways were noticeably moderated by age cohort. Among younger people, associations between parental socioeconomic status and mental health were mostly explained by educational attainment whereas among older people associations between parental socioeconomic status and mental health were mostly explained by household income. In general, parental socioeconomic status appear to have a greater influence on the mental health of people who grew up after the Chinese economic reform of the 1970s.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".