MétaCan
Menu
Back to cohort
Record W4414140136 · doi:10.3390/bs15091221

Climbing the Dark Ladder: How Status and Inclusion Aspirations, Perceived Attainment, and Behaviors Relate to the Dark Triad

2025· article· en· W4414140136 on OpenAlexaff
Nikhila Mahadevan, Christian H. Jordan

Bibliographic record

VenueBehavioral Sciences · 2025
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsDark triadExtraversion and introversionMachiavellianismClimbingGreat RiftTriad (sociology)Interpersonal communicationBig Five personality traits

Abstract

fetched live from OpenAlex

Individual differences in the Dark Triad may partially reflect differences in interpersonal motivational patterns such as a strong desire for status. These studies examine how desires for status and inclusion, perceived attainment of status and inclusion, and status-seeking and inclusion-seeking behavior relate to the Dark Triad (grandiose narcissism, Machiavellianism, and psychopathy). Two studies (N = 591) find that individuals high in Dark Triad traits generally desire status, feel they have attained high status, and report behaving in status-seeking ways (once desires for inclusion, perceived attainment of inclusion, and inclusion-seeking behavior are controlled, respectively). They generally do not desire inclusion, do not feel they have attained inclusion, and do not report behaving in inclusion-seeking ways (once desires for status, perceived attainment of status, and status-seeking behavior are controlled, respectively). These associations are largely observed for the dimensions of the Dark Triad involving agentic extraversion and antagonism, but not for those involving impulsivity. This research delineates the motivational, social, and behavioral profile of the Dark Triad and its dimensions with implications for understanding the “core” of the Dark Triad.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.081
GPT teacher head0.402
Teacher spread0.320 · 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.

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

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueBehavioral SciencesSame topicPersonality Traits and PsychologyFrench-language works237,207