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Record W137831763 · doi:10.3138/jcfs.43.2.185

Wives’ Relative Income and Marital Satisfaction among the Urban Chinese Population: Exploring Some Moderating Effects

2012· article· en· W137831763 on OpenAlexvenueno aff
Huiping Zhang, Sandra Tsang, Peilian Chi, Yee Tak Derek Cheung, Xiulan Zhang, Paul Yip

Bibliographic record

VenueJournal of Comparative Family Studies · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsnot available
Fundersnot available
KeywordsChinaMarital statusContext (archaeology)Demographic economicsHousehold incomePopulationMultilevel modelPsychologySocioeconomicsDemographyRelative deprivationEconomicsGeographySocial psychologySociology

Abstract

fetched live from OpenAlex

In contemporary urban China, the employment of married women has led to wives making an economic contribution to the family in both absolute and relative terms. However, little is known about the effect of wives’ relative income on marital satisfaction in the Chinese context. This study aims to address two key questions: (a) is wives’ relative income associated with marital satisfaction in the Chinese population? (b) Is this association dependent on any condition? Hierarchical multiple regression, using the data of 272 men and 340 women from five large cities in the 2004 Chinese Urban Household Survey, indicates that, after controlling for other variables, wives’ income relative to household income is negatively associated with marital satisfaction. We also find that this association has more negative impact on married women than married men. The implications of this study for further research and practice are discussed.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.097
GPT teacher head0.359
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations9
Published2012
Admission routes1
Has abstractyes

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