How Does Wives’ Unemployment Affect Marriage in Reforming Urban China?
Bibliographic record
Abstract
This cross-cultural study explores the relationship between wives’ unemployment and marital quality in reforming urban China. Using random survey data from Chengdu (N = 300), we estimate the effects of wives’ unemployment, changing marital dynamics, and spousal responses to the wife’s unemployment on marital affection and marital tension. Under the guidance of an integrated theoretical framework, our ordered logistic and Ordinary Least Squares (OLS) regression results show that the wives’ unemployment and subsequent economic hardship, the deteriorated mother-child relationship, the husbands’ negative responses, and the wives’ symptoms of psychological distress have deleterious effects on urban Chinese marriages. Moreover, our ancillary analyses indicate that the wives’ unemployment is indirectly associated with marital affection through the husband’s negative responses to the wife’s unemployment. This result suggests that from the husband’s perspective the wife’s economic contributions and co-breadwinner role are vitally important for urban Chinese marriages. We conclude that as anticipated the wife’s unemployment is indeed negatively associated with marital quality in reforming urban China.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".