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Record W2009522795 · doi:10.5964/ijpr.v8i1.146

Factors Contributing to Personal Commitment in Chinese Interethnic Couples

2014· article· en· W2009522795 on OpenAlexaff
Xinmiao Zhong, Rebecca Malhi

Bibliographic record

VenueInterpersona An International Journal on Personal Relationships · 2014
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAcculturationSocial psychologyPsychologyCollectivismPersonal identityVariance (accounting)IndividualismSimilarity (geometry)Identity (music)Social identity theorySociologySelf-conceptEthnic groupSocial groupPolitical science

Abstract

fetched live from OpenAlex

Interethnic relationships are increasingly common in many societies, yet interethnic couples have a higher divorce rate compared to intraethnic couples. Given these facts and the dearth of research, this study aimed to identify factors that contribute to couples’ commitment in interethnic relationships. This study investigated the personal commitment of Chinese interethnic couples in the United Kingdom and the United States. Specifically, whether love, dyadic adjustment and “couple cultural identity” (i.e. acculturation to the partner and couple’s similarity on individualism/collectivism) would predict personal commitment and whether each variable would account for unique variance in personal commitment of the participants. Thirty-seven Chinese/non-Chinese heterosexual couples participated in the study and significant relationships between love and personal commitment, dyadic adjustment and personal commitment were found. Also, couple cultural identity was important for women’s personal commitment. Multiple regression and structural equation modelling showed that partners in interethnic relationships defined personal commitment in different ways with men emphasizing love and dyadic adjustment, and women emphasizing love and acculturation to their partner. The discovery of the importance of couple cultural identity in contributing to personal commitment, besides love and dyadic adjustment, helps researchers to gain a greater understanding of such relationships and to extend the research on interethnic relationships.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.070
GPT teacher head0.423
Teacher spread0.352 · 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.

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

Citations3
Published2014
Admission routes1
Has abstractyes

Explore more

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