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Record W2123845521 · doi:10.1177/0022022113492894

The Culturally Intelligent Team

2013· article· en· W2123845521 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Cross-Cultural Psychology · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsUniversity of GuelphWilfrid Laurier UniversityUniversity of Waterloo
Fundersnot available
KeywordsOperationalizationPsychologyTeam effectivenessCultural diversityCultural intelligenceHomogeneousMetacognitionPsychological safetySocial psychologyCultural competenceCompetence (human resources)Knowledge managementCognitionSociologyPedagogyComputer science

Abstract

fetched live from OpenAlex

This study examines how the cultural heterogeneity of work teams moderates the way in which team cultural intelligence (CQ) affects the development of team shared values. Utilizing the four-factor model of CQ, we predict how each facet of CQ will impact the development of shared values in relatively early stages of team development differently for culturally homogeneous versus culturally heterogeneous work teams. We operationalize team shared values as the degree to which a broad set of cultural values are similarly endorsed by team members as guiding principles when working in their team. Results show that behavioral and metacognitive CQ had a positive effect on shared values in culturally heterogeneous teams; however, motivational and metacognitive CQ had a negative effect on shared values in culturally homogeneous teams. All effects were observed in the early stages of team development. Having uncovered positive and negative effects of CQ for shared values in work teams, we discuss implications for theory and practice around this form of cultural competence.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.621

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.054
GPT teacher head0.463
Teacher spread0.408 · 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