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Record W2139142990 · doi:10.1177/1059601108329811

Contextual Inhibitors of Employee Creativity in Organizations

2008· article· en· W2139142990 on OpenAlexaffabout
Jin Nam Choi, Troy Anderson, Anick Veillette

Bibliographic record

VenueGroup & Organization Management · 2008
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsMcGill UniversityCarleton University
Fundersnot available
KeywordsCreativityPsychologyPerspective (graphical)Set (abstract data type)Organisation climateSocial psychologyApplied psychologyComputer science

Abstract

fetched live from OpenAlex

This study highlights the importance of negative predictors of employee creativity. The authors identified a set of work environment characteristics that may inhibit employee creativity. Using data collected from 123 Canadian employees in various industries, the authors empirically tested the relationships between these inhibiting factors and peer-rated creative performance. Aversive leadership and unsupportive organizational climate were negatively related to creativity, whereas close monitoring was positively associated with creativity. Interaction analyses indicate that creative ability of employees may either enhance or attenuate the detrimental effects of inhibitory contextual factors. Complementing the existing studies that have largely focused on facilitators of creativity, the present study introduces a more balanced perspective to the organizational creativity literature by examining inhibitory contextual factors.

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)0.001
metaresearch head score (Gemma)0.009
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.000
Open science0.0000.002
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 head0.024
GPT teacher head0.297
Teacher spread0.273 · 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

Citations182
Published2008
Admission routes2
Has abstractyes

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