No Spouse, No Son, No Daughter, No Kin in Contemporary China: Prevalence, Correlates, and Differences in Economic Support
Bibliographic record
Abstract
OBJECTIVES: China's recent demographic and social changes might undermine the sustainability of its family-oriented system for elder care. We investigate kin availability among adults aged 45+ in contemporary China, with an emphasis on child gender. METHOD: Using nationally representative survey data from the China Health and Retirement Longitudinal Study (2011), we examine the prevalence and correlates of lacking different kin types and combinations, and we test associations between kin availability and received economic support. RESULTS: Kinlessness is low in China (less than 2% lack a spouse/partner and children), but kin availability is patterned by gender, age group, and sociodemographic characteristics. More than twice as many older adults have no spouse/partner and no daughter (3.2%) as those who have no spouse/partner and no son (1.4%). Adults without close kin are disadvantaged across health, wealth, and economic support. In contrast to traditional expectations, we find that those with only daughters are more similar to those with mixed sex children, whereas those with only sons are more similar to those without children in receipt of economic support. DISCUSSION: Access to kin forms the basis of an emergent system of stratification in China, which will be amplified as cohorts with only one child age into older adulthood.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".