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Record W2599896977 · doi:10.3138/jcfs.41.5.717

How Does Wives’ Unemployment Affect Marriage in Reforming Urban China?

2010· article· en· W2599896977 on OpenAlexvenueno aff
Xiaohe Hu, Xuhui Zeng, Zheng Li, Christy Flatt

Bibliographic record

VenueJournal of Comparative Family Studies · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsnot available
Fundersnot available
KeywordsWifeUnemploymentChinaAffectionAffect (linguistics)Demographic economicsEconomicsOrdinary least squaresPsychologySocial psychologyEconomic growthGeographyPolitical science

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.039
GPT teacher head0.361
Teacher spread0.322 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2010
Admission routes1
Has abstractyes

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