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Record W2748572955 · doi:10.1002/tie.21926

East vis‐à‐vis West: The evolution of work values within China regions

2017· article· en· W2748572955 on OpenAlexaff
David A. Ralston, Yim‐Yu Wong, Carolyn P. Egri, Carlos Wing‐Hung Lo, Yongjuan Li, Xuejiao Dutton, Jun Yang

Bibliographic record

VenueThunderbird International Business Review · 2017
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsChinaWork (physics)WorkforceHomogeneousValue (mathematics)Cultural valuesGeographyEconomic geographyEmerging marketsPolitical scienceSociologyEconomic growthGender studiesEconomicsEngineering

Abstract

fetched live from OpenAlex

Numerous studies have investigated between‐country cultural differences. However, the subnational cultural differences, particularly in emerging markets, have remained an underexplored research topic despite its importance. Likewise, multiperiod studies in the cross‐cultural management area have also remained an underexplored topic. This study concurrently addresses both of these voids in the literature. Specifically, we examine changes in work values of businesspeople in the economically developed East region and the less developed West region of China over the first decade of the 21st century (2000–2010). Our findings show that, across the eight work values dimensions analyzed in this study, three exhibited static crossvergence, while the other five value dimensions exhibited conforming crossvergence. An implication of these findings is that the dissimilar work values, which had been found across the regions of China of the past century, are moving toward a more countrywide set of homogeneous values among the workforce professionals of China.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.927
Threshold uncertainty score0.999

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.110
GPT teacher head0.384
Teacher spread0.274 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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