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Record W3014384867 · doi:10.1108/jkm-06-2019-0337

Knowledge sabotage as an extreme form of counterproductive knowledge behavior: the perspective of the target

2020· article· en· W3014384867 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 Knowledge Management · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Violence and Bullying
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsPerspective (graphical)OriginalityValue (mathematics)InnocenceGratificationPublic relationsIncentiveBusinessPsychologyKnowledge managementSocial psychologyPolitical scienceCreativityComputer scienceEconomics

Abstract

fetched live from OpenAlex

Purpose This study aims to explore the existence of knowledge sabotage in the contemporary organization from the perspective of the target. Design/methodology/approach This study collected and analyzed 172 critical incidents reported by 109 employees who were targets of knowledge sabotage in their organizations. Findings Over 50 per cent of employees experienced at least one knowledge sabotage incident. Knowledge sabotage is driven by three factors, namely, gratification, retaliation against other employees and one’s malevolent personality. Knowledge saboteurs are more likely to provide intangible than tangible knowledge. Knowledge sabotage results in extremely negative consequences for individuals, organizations and third parties. Organizations often indirectly facilitate knowledge sabotage among their employees. Both knowledge saboteurs and their targets believe in their innocence – saboteurs are certain that their action was a necessary response to targets’ inappropriate workplace behavior, whereas targets insist on their innocence and hold saboteurs solely responsible. Practical implications Organizations should recruit employees with compatible personalities and working styles, introduce inter-employee conflict prevention and resolution procedures, develop anti-knowledge sabotage policies, clearly articulate the individual and organizational consequences of knowledge sabotage and eliminate zero-sum game-based incentives and rewards. Originality/value This is the first study documenting knowledge sabotage from the target’s perspective.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score0.574

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.045
GPT teacher head0.337
Teacher spread0.292 · 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