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Record W2406588417

Unpacking the relationship between knowledge-sharing efforts and creativity: The critical roles of relationship quality and perceived organizational politics

2016· other· en· W2406588417 on OpenAlexaff
Zahid Rahman

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2016
Typeother
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsBrock University
Fundersnot available
KeywordsUnpackingCreativityPoliticsQuality (philosophy)PsychologyKnowledge managementPolitical scienceSocial psychologyComputer scienceEpistemology
DOInot available

Abstract

fetched live from OpenAlex

This thesis contributes to creativity research by investigating the link between employees’ knowledge-sharing efforts and creativity and how this link is moderated by two aspects of relationship quality (informality and emotional openness) and the belief that organizational decision making is marked by destructive political games. It proposes that the usefulness of knowledge-sharing efforts for stimulating creativity is higher when employees maintain informal relationships with their colleagues and feel comfortable expressing a diverse range of emotions with them. In addition, extensive knowledge-sharing efforts are less likely to enhance creativity when employees believe that organizational decision making is guided by destructive political games. Finally, the harmful effect of perceived organizational politics on the knowledge-sharing efforts–creativity relationship is mitigated when employees can rely on high levels of relationship quality. This research holds useful implications for organizations regarding the circumstances in which the application of employee knowledge to the generation of novel solutions to problem situations is most effective.

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)0.000
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: Observational
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.398
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.047
GPT teacher head0.285
Teacher spread0.238 · 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
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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