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Record W3156381385 · doi:10.1177/13684302211001944

My way or the highway: Narcissism and dysfunctional team conflict processes

2021· article· en· W3156381385 on OpenAlexaff
Jennifer Lynch, Alexander McGregor, Alex J. Benson

Bibliographic record

VenueGroup Processes & Intergroup Relations · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsWestern University
Fundersnot available
KeywordsAdmirationRivalryNarcissismPsychologySocial psychology

Abstract

fetched live from OpenAlex

Individuals higher in grandiose narcissism strive to create and maintain their inflated self-views through self-aggrandizing and other-derogating behaviors. Drawing from the dual-process model of narcissistic admiration and rivalry, we proposed that individuals higher in narcissism may contribute to more competitive and less cooperative conflict processes. We tracked over 100 project design teams from inception to dissolution, gathering data at three time points. We evaluated how team levels of narcissism (i.e., maximum team score, team mean, and team variance) related to latent team means of cooperative and competitive conflict processes. Team mean scores of narcissistic rivalry corresponded to less cooperative and more competitive team conflict processes as teams approached their final project deadline. Our results show how narcissistic rivalry (but not admiration) alters the types of team conflict processes that arise within groups, and is particularly consequential as teams approach major project deadlines.

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)0.003
metaresearch head score (Gemma)0.019
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 score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
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 head0.029
GPT teacher head0.286
Teacher spread0.257 · 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

Citations26
Published2021
Admission routes1
Has abstractyes

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