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Record W2161178205 · doi:10.1002/per.1860

Sex, Power, and Money: Prediction from the Dark Triad and Honesty–Humility

2012· article· en· W2161178205 on OpenAlexafffund
Kibeom Lee, Michael C. Ashton, Jocelyn Wiltshire, Joshua S. Bourdage, Beth A. Visser, Alissa Gallucci

Bibliographic record

VenueEuropean Journal of Personality · 2012
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsTrent UniversityBrock UniversityUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDark triadPsychologyMachiavellianismPsychopathyNarcissismSocial psychologyPersonalityHonestyBig Five personality traitsDevelopmental psychology

Abstract

fetched live from OpenAlex

Data were collected from two undergraduate student samples to examine (i) the relations of the ‘Dark Triad’ variables (Machiavellianism, Psychopathy, and Narcissism) with the HEXACO personality dimensions, as well as (ii) the ability of the aforementioned characteristics and of the Big Five personality factors to predict outcome variables related to sex, power, and money. Results indicated that the common variance of the Dark Triad was very highly correlated with low Honesty–Humility and that the unique variance of each of the Dark Triad variables also showed theoretically meaningful relations with the other five HEXACO factors. Furthermore, the Dark Triad and Honesty–Humility were strong predictors of three domains of outcome variables—Sex (short–term mating tendencies and sexual quid pro quos), Power (Social Dominance Orientation and desire for power), and Money (conspicuous consumption and materialism)—that were not well predicted by the dimensions of the Big Five. Copyright © 2012 John Wiley & Sons, Ltd.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.304
Teacher spread0.260 · 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

Citations445
Published2012
Admission routes2
Has abstractyes

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