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Record W2144347289 · doi:10.1177/0022022114542850

The Acculturation of Relational Mobility

2014· article· en· W2144347289 on OpenAlexaff
Rui Zhang, Liman Man Wai Li

Bibliographic record

VenueJournal of Cross-Cultural Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAcculturationNormativePsychologyContext (archaeology)Sociocultural evolutionSocial psychologyRelational modelEthnic groupAdaptation (eye)SociologyPolitical scienceRelational databaseGeographyComputer scienceAnthropology

Abstract

fetched live from OpenAlex

In this article, we extended the socioecological approach in cross-cultural psychology to the acculturation context. We focused on relational mobility among Asian Canadians and how it is related to their acculturation experience. Previous research shows that relational mobility, which is a feature of one’s social environment, is generally higher in North America than East Asia. In Study 1, we found that migration does not completely bridge the cross-national gap in relational mobility. Compared with European Canadians, Asian Canadians continued to perceive lower relational mobility around them. Study 2 explored the relations between relational mobility and Asian Canadians’ acculturation experiences. Relational mobility was correlated specifically with sociocultural adaptation, but not contact, acculturation orientations, psychological adaptation, or experience of discrimination. It was also uniquely associated with normative belief about relational mobility. Finally, we largely replicated the effects of relational mobility on self-esteem (Study 1) and close friendships (Study 2) in the acculturation context, with the latter effects further mediated by normative belief about relational mobility. Implications of our findings for relational mobility and acculturation research 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 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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.519
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.144
GPT teacher head0.497
Teacher spread0.353 · 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 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

Citations21
Published2014
Admission routes1
Has abstractyes

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