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Record W2093549468 · doi:10.1002/job.375

Cultural and individual differences in self‐rating behavior: an extension and refinement of the cultural relativity hypothesis

2006· article· en· W2093549468 on OpenAlexaffabout
Jia Lin Xie, Jean‐Paul Roy, Ziguang Chen

Bibliographic record

VenueJournal of Organizational Behavior · 2006
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsMemorial University of NewfoundlandUniversity of Toronto
FundersUniversity of Hong KongCity University of Hong Kong
KeywordsIndividualismPsychologySocial psychologyMainland ChinaRating scaleNarcissismMainlandChinaDevelopmental psychologyPolitical scienceLawEcology

Abstract

fetched live from OpenAlex

Abstract This study examined the relationships between culture, individual attributes, and self‐rating behavior among 1,786 university students in Canada, Hong Kong, Taiwan, mainland China, and Japan, and in doing so extended and refined the cultural relativity hypothesis. It explored the difference between vertical and horizontal individualists in self‐rating behavior, and examined the mediating effects of two individual attributes, self‐enhancement propensity and general self‐efficacy in the relationship between individualism and self‐rating behavior. The results confirmed that individualism is the cultural driver for self‐rating leniency, and that the individual‐level assessment of individualism is a stronger predictor of self‐rating leniency than are culture‐level differences. Vertical individualism was found to be positively related to self‐enhancement propensity, which in turn was positively related to self‐rating. Whereas, horizontal individualism was positively related to general self‐efficacy, which in turn had a positive relationship with self‐rating. We discuss the implications of the results for academic research and practical management. Copyright © 2006 John Wiley & Sons, Ltd.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.311

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 communication0.0000.000
Open science0.0000.000
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 head0.126
GPT teacher head0.343
Teacher spread0.217 · 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

Citations48
Published2006
Admission routes2
Has abstractyes

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