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Record W2053952776 · doi:10.1057/palgrave.kmrp.8499999

Knowledge sharing in a multi-cultural setting: a case study

2003· article· en· W2053952776 on OpenAlexaff
Dianne P. Ford, Yolande E. Chan

Bibliographic record

VenueKnowledge Management Research & Practice · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsQueen's University
Fundersnot available
KeywordsKnowledge managementKnowledge sharingHofstede's cultural dimensions theoryOrganizational cultureOrganizational learningCultural knowledgeKnowledge value chainBusinessSociologyPsychologyPublic relationsSocial psychologyPolitical scienceComputer sciencePedagogy

Abstract

fetched live from OpenAlex

Organizational culture has been shown to influence the success of knowledge management practices. Hofstede's theory specifies that organizational culture is not independent of national culture. A case study of an international subsidiary was conducted to explore the extent to which knowledge sharing is dependent on national culture. Results indicate that language differences can create knowledge blocks, and cross-cultural differences can explain the direction of knowledge flows.

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)0.009
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0200.005
Scholarly communication0.0050.004
Open science0.0030.006
Research integrity0.0060.003
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 head0.264
GPT teacher head0.517
Teacher spread0.254 · 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 designQualitative
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

Citations261
Published2003
Admission routes1
Has abstractyes

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