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Record W4416297632 · doi:10.1177/19485506251389441

With a Little Help From My Friends: Social Approval and Relationship Quality in Intercultural Romantic Relationships

2025· article· en· W4416297632 on OpenAlexaff
Hanieh Naeimi, Amy Muise, Alyssa Di Bartolomeo, Alexandria L. West, Emily A. Impett

Bibliographic record

VenueSocial Psychological and Personality Science · 2025
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsDalhousie UniversityYork UniversityUniversity of Toronto
Fundersnot available
KeywordsQuality (philosophy)Psychological interventionRomanceSocial approvalCultural diversitySocial relationshipCultural valuesSocial relationSocial support

Abstract

fetched live from OpenAlex

Despite their growing prevalence, intercultural couples continue to experience social disapproval and discrimination from their social networks. In this study ( N = 757), we examined how social approval from different sources (i.e., family, friends, and society) predicts relationship quality and whether these effects vary by individual (i.e., cultural background and gender) and couple-level (i.e., cultural pairing and relationship length) characteristics. Friend approval emerged as the most robust predictor of relationship quality, especially for couples in which both partners belonged to minority cultures. In contrast, family approval was only important for Latinx and Middle Eastern partners, and those in the earlier stages in relationships. These findings suggest that different sources of social approval can buffer or exacerbate relationship quality, depending on partners’ cultural backgrounds and relationship length. By identifying which sources of approval matter most and for whom, these findings can inform culturally sensitive interventions and support systems for intercultural couples.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.111
GPT teacher head0.460
Teacher spread0.350 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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