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Record W2014104710 · doi:10.1108/13527590410527568

Organizational culture, group diversity and intra‐group conflict

2004· article· en· W2014104710 on OpenAlexaff
You‐Ta Chuang, Robin Church, Jelena Zikic

Bibliographic record

VenueTeam Performance Management · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversity of TorontoYork University
Fundersnot available
KeywordsDiversity (politics)Social psychologyGroup (periodic table)Organizational cultureGroup conflictGroup processGroup developmentPsychologyCultural diversityCultural conflictOrganizational conflictTeam effectivenessConflict managementSociologyPolitical sciencePublic relationsSocial scienceKnowledge managementAnthropology

Abstract

fetched live from OpenAlex

Past research on group diversity tends to overlook organizational contextual and group process variables. Although recent studies have revealed the main effects of group diversity on intra‐group conflict, it is important to examine the contextual factors reducing or facilitating those effects on intra‐group conflict. This paper presents a conceptual analysis and research proposals that build on past research on intra‐group conflict and organizational culture to examine the relationships between organizational culture, intra‐group conflict, and group diversity. The paper proposes that organizational cultural intensity and content have direct impact on intra‐group conflict and moderate the relationship between group diversity and intra‐group conflict, depending on the degree of value congruence and the value content shared among group members.

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)0.004
metaresearch head score (Gemma)0.013
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 score0.004
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0000.001
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 head0.046
GPT teacher head0.246
Teacher spread0.200 · 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

Citations90
Published2004
Admission routes1
Has abstractyes

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