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Record W3035617400 · doi:10.1002/jocb.453

Conscientiousness in Teams Completing Creative Tasks: Does it Predict?

2020· article· en· W3035617400 on OpenAlexaff
Simon Taggar

Bibliographic record

VenueThe Journal of Creative Behavior · 2020
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsConscientiousnessCreativityTeamworkPsychologyDependabilitySelf-efficacySocial psychologyNomological networkPersonalityBig Five personality traitsApplied psychologyManagementStructural equation modelingEngineeringComputer scienceExtraversion and introversion

Abstract

fetched live from OpenAlex

Abstract The relationship between conscientiousness and creativity remains equivocal. This is surprising because conscientiousness is a good predictor of job performance across most criteria and occupations. In this longitudinal study, I found support for the achievement striving and the dependability aspects of conscientiousness affecting team member creativity in different ways. Specifically, the achievement striving aspect of conscientiousness positively predicts creative self‐efficacy, but the dependability aspect negatively predicts creative self‐efficacy. Conversely, dependability positively predicts teamwork self‐efficacy, while achievement striving is unrelated to teamwork self‐efficacy. Creative self‐efficacy partially mediates between achievement striving and team member creativity. Both creative self‐efficacy and teamwork self‐efficacy mediate between dependability and team member creativity.

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)0.018
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.057
GPT teacher head0.383
Teacher spread0.326 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

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