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Record W2021072506 · doi:10.1177/1470595814564767

The role of self-concept in cross-cultural communication

2015· article· en· W2021072506 on OpenAlexaff
Andre Pekerti, David C. Thomas

Bibliographic record

VenueInternational Journal of Cross Cultural Management · 2015
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCollectivismSocial psychologyPsychologySelf construalInterdependenceConsistency (knowledge bases)IndividualismArgumentativeContradictionIntercultural communicationCross-culturalSociologyMathematicsEpistemologyCommunicationPolitical science

Abstract

fetched live from OpenAlex

Empirical evidence supports the notion that communication behaviors in intercultural encounters are effectively extensions of cultural values as well as epistemologies. Study 1 established communication behaviors of Asians and New Zealanders (NZs) as consistent with vertical collectivism and horizontal individualism, respectively. In particular, argumentativeness is positively related to independent self-construal (SC) and negatively related to interdependent SC. This supports Markus and Kitayama’s SC theory. Study 2 showed that NZs exhibited more idiocentric and argumentative behavior, while Asians displayed more sociocentric and less argumentative behavior during two actual interactions; specifically, participants diverged in their communication styles to be more consistent with their cultural values during intercultural interactions. Analyses of decision outcomes provide support that culture moderates cognitive consistency behaviors such that NZs exhibited more inconsistency-reduction behaviors, which is rooted in adherence to noncontradiction. In contrast, Asians exhibited more inconsistency-support behaviors, suggesting that naive dialecticism rooted in acceptance of contradiction is customary in Asian social interaction.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.065
GPT teacher head0.439
Teacher spread0.373 · 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

Citations16
Published2015
Admission routes1
Has abstractyes

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