Climbing the Dark Ladder: How Status and Inclusion Aspirations, Perceived Attainment, and Behaviors Relate to the Dark Triad
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".