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Record W908099671 · doi:10.1016/j.ausmj.2015.06.003

Culture Change and Globalization: The Unresolved Debate between Cross-National and Cross-Cultural Classifications

2015· article· en· W908099671 on OpenAlexaffabout
Riadh Ladhari, Nizar Souiden, Yonghoon Choi

Bibliographic record

VenueAustralasian Marketing Journal (AMJ) · 2015
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsCollectivismHorizontal and verticalIndividualismHofstede's cultural dimensions theoryGlobalizationContext (archaeology)Cultural diversityCross-culturalEconomic geographySociologyGeographyPolitical scienceSocial scienceAnthropologyLawGeodesy

Abstract

fetched live from OpenAlex

This study intends to examine the assumptions of culture homogeneity within nations and its stability in the current global context. First, by using a sample of 720 respondents (207 in Canada, 263 in Japan, and 250 in Morocco), it empirically examines the cultural values of three countries at three different continents (Canada in North America, Japan in East Asia, and Morocco in North Africa) and compares the findings to Hofstede's framework. Second, it tests for the existence of cultural segments transcending the national boundaries. Cultural values are measured using the horizontal–vertical individualism and collectivism scale. The findings show that: (i) horizontal collectivism dominates the cultural environment of these three countries; (ii) horizontal collectivism and horizontal individualism coexist in Canada; and (iii) vertical individualism characterizes Morocco and Japan more than Canada. In addition, the study reports three segments that transcend national borders, each of them sharing the same cultural values. When compared with each other, the three clusters completely differ on horizontal collectivism, vertical collectivism, and horizontal individualism. The research concludes that some changes are occurring in cultural values/patterns in the three studied countries.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
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
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.248
GPT teacher head0.441
Teacher spread0.194 · 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

Citations29
Published2015
Admission routes2
Has abstractyes

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