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Record W2149148249 · doi:10.1002/per.1893

The Core of Darkness: Uncovering the Heart of the Dark Triad

2012· article· en· W2149148249 on OpenAlexaff
Daniel N. Jones, Aurelio José Figueredo

Bibliographic record

VenueEuropean Journal of Personality · 2012
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMachiavellianismDark triadPsychopathyNarcissismPsychologyPersonalityFacet (psychology)Social psychologyPersonality psychologyDominance (genetics)Big Five personality traitsDevelopmental psychology

Abstract

fetched live from OpenAlex

The Dark Triad consists of three overlapping but distinct personality variables: narcissism, Machiavellianism and psychopathy. To date, however, no research has empirically identified what leads these three variables to overlap or whether other variables share the same core. The present research addresses why and how dark personalities overlap. Drawing from classic work in psychopathy, Hare's Factor 1 or manipulation and callousness were found to be the common antagonistic core. A series of latent variable procedures, including Multisample Structural Equation Models, revealed that for both samples, manipulation and callousness, completely accounted for the associations among the facet scores of the psychopathy, narcissism and Machiavellianism scales. Sample 2 also included Social Dominance Orientation, and results further confirmed that Social Dominance Orientation has the same common core as the Dark Triad. In sum, Hare's Factor 1—manipulation–callousness—emerged as common dark core that accounts for the overlap among antagonistic traits. Copyright © 2012 European Association of Personality Psychology

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)0.009
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0020.006
Scholarly communication0.0040.004
Open science0.0010.007
Research integrity0.0000.003
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 head0.083
GPT teacher head0.344
Teacher spread0.261 · 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

Citations659
Published2012
Admission routes1
Has abstractyes

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