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Record W2022037039 · doi:10.4236/chnstd.2013.21001

Key Dimensions and Validity of the Chinese Version of the Individualism-Collectivism Scale

2013· article· en· W2022037039 on OpenAlexaff
Huang Renzhi, John R. Z. Abela, Fallyn Leibovitch

Bibliographic record

VenueChinese Studies · 2013
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsMcGill University
Fundersnot available
KeywordsCollectivismCronbach's alphaMultivariate analysis of variancePsychologyIndividualismConfirmatory factor analysisScale (ratio)Social psychologyIndividualistic cultureVariance (accounting)PerceptionHofstede's cultural dimensions theoryDevelopmental psychologyPsychometricsStructural equation modelingStatisticsMathematicsGeographyPolitical science

Abstract

fetched live from OpenAlex

A Chinese version of the Individualism-Collectivism Scale (ICS) to assess cultural dimensions was developed and its psychometric properties were evaluated. The English version of the ICS was translated and back translated prior to its administration to 1760 participants who were divided into 5 age groups. Results indicated that the ICS-C exhibited moderate to high internal consistency with Cronbach’s alpha coefficients ranging from 0.64 to 0.83. The ICS-C also exhibited strong test-retest reliability with ICCs from 0.45 to 0.80. Confirmatory factor Analyses found the four-factor model was the best fit of the data across gender and age, thus supporting the multi-dimensional perspective of horizontal and vertical individualism and collectivism. Furthermore, a multivariate analysis of variance (MANOVA) revealed a significant main effect of age and gender. A gradual increase is present in subjective perception of societal emphasis on the cultural dimensions across five age groups, except age groups of 14 - 15 and 16 - 17 in vertical individualism. With respect to gender effect, female students showed a higher perception of the vertical collectivism than male students (p

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 score0.026
Threshold uncertainty score0.216

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 head0.062
GPT teacher head0.354
Teacher spread0.293 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

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