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Stability and Change in Managerial Work Values: A Longitudinal Study of China, Hong Kong, and the U.S.

2006· article· en· W2111711157 on OpenAlexaff
David A. Ralston, James S. Pounder, Carlos Wing‐Hung Lo, Yim‐Yu Wong, Carolyn P. Egri, Joseph R. Stauffer

Bibliographic record

VenueManagement and Organization Review · 2006
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsChinaTypologyDivergence (linguistics)IdeologyCultural valuesSociocultural evolutionSociologyEconomic geographyDemographic economicsPolitical scienceGeographySocial scienceEconomicsLawAnthropology

Abstract

fetched live from OpenAlex

Abstract This study presents a 12-year (1989-2001) longitudinal comparison of managerial values systems in China, Hong Kong, and the U.S. Using hierarchical cluster analysis, we test the validity of the three competing perspectives - convergence, divergence, and crossvergence - on values system evolution in these three societies. We use the sociocultural influence and business ideology influence typology as the foundation for developing our hypotheses. Additionally, we assess the contribution of the specific values within the values system to the overall system values findings. Our data most strongly support the multicultural crossvergence perspective. During a time period of stability in the U.S. and substantial change in both Hong Kong and China, the values of Hong Kong and China became more similar, while the values of these two Greater China societies became more different from those of the U.S.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.248
Threshold uncertainty score0.494

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.063
GPT teacher head0.323
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), 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

Citations141
Published2006
Admission routes1
Has abstractyes

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