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Record W4377022884 · doi:10.1177/10422587231173684

The Triad Divided: A Curvilinear Mediation Model Linking Founder Machiavellianism, Narcissism, and Psychopathy to New Venture Performance

2023· article· en· W4377022884 on OpenAlexaff
Katrina M. Brownell, Audra Quinn, Mark Bolinger

Bibliographic record

VenueEntrepreneurship Theory and Practice · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsWestern University
Fundersnot available
KeywordsMachiavellianismNarcissismPsychopathyPsychologyDark triadMediationSocial psychologyTraitPersonalityBig Five personality traitsPerspective (graphical)Facet (psychology)Sociology

Abstract

fetched live from OpenAlex

Across two studies, we apply self-regulation theory to test nonlinear relationships between founder Machiavellianism, narcissism, and psychopathy and new venture performance. Our hypotheses are supported for Machiavellianism and psychopathy, but contrary to our theorizing, we find a positive relationship between narcissism and performance. Furthermore, we identify an important explanatory mechanism in knowledge sharing, which mediates the curvilinear relationships at moderate and high levels. Our research has implications for how we understand the influence of problematic founder personality traits and how behavioral differences at varying levels of these traits can explain relationships with performance, and it presents a nuanced perspective to trait-based explanations for destructive entrepreneurial actions.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.000
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 head0.033
GPT teacher head0.289
Teacher spread0.255 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations22
Published2023
Admission routes1
Has abstractyes

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