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Record W2774816249 · doi:10.1177/1470595817745898

Cultural mosaic beliefs as a new measure of the psychological climate for diversity

2017· article· en· W2774816249 on OpenAlexaff
Pylin Chuapetcharasopon, Lukas Neville, Wendi L. Adair, Susan E. Brodt, Terri R. Lituchy, Aimy A. Racine

Bibliographic record

VenueInternational Journal of Cross Cultural Management · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsQueen's UniversityUniversity of ManitobaUniversity of Waterloo
Fundersnot available
KeywordsCultural diversitySocial psychologyDiversity (politics)PsychologyModerationScale (ratio)Discriminant validityMulticulturalismSociologyDevelopmental psychologyPsychometricsGeography

Abstract

fetched live from OpenAlex

This article introduces the concept of cultural mosaic beliefs (CMBs) as a component of effective multicultural work groups. Building on theories of group diversity and self-verification, and responding to calls to understand moderators that explain the impact of group diversity on performance outcomes, we conceptualize CMBs as a psychological climate that individual group members perceive to promote the recognition, acceptance and expression, and utilization of cultural diversity (values, traditions, and practices) in their work. We also propose that CMBs might attenuate conflict that can sometimes characterize culturally diverse work groups distinguishing groups that falter from those that flourish and benefit from the informational and other potential advantages associated with their diverse cultural composition. In a series of five studies ( N = 1119), we develop a 17-item CMB scale comprised of three factors: perceived group diversity, cultural acceptance and expression, and culture utilization. We present evidence of convergent and discriminant validity, showing that the CMB scale is related to but distinct from other measures of diversity. We also demonstrate predictive validity, showing that the CMB scale is related to work group members’ identification with the group, commitment to the group, satisfaction with the group, and learning from the group. We conclude by proposing applications of our CMBs concept and measure to multicultural workplaces and offer future directions for research on cultural diversity, specifically the study of group CMBs as a moderator of cultural diversity’s effects on groups.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.213
GPT teacher head0.448
Teacher spread0.235 · 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

Citations13
Published2017
Admission routes1
Has abstractyes

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