Latent profiles of the Dark Triad: Further person-centered exploration
Bibliographic record
Abstract
Person-centered approaches may offer unique insight into the nature of the Dark Triad by considering how the traits of Machiavellianism, narcissism, and psychopathy, which are present alongside a general D factor, combine. Yet, little past work has leveraged person-centered methods, like latent profile analysis (LPA), adequately. In this work, we focus on responses from 11,394 individuals to the Dirty Dozen measure of the Dark Triad. After using bifactor exploratory structural equation modeling (B-ESEM) we identified four distinct profiles of the Dark Triad: Self-Absorbed, Exploiter, Manipulator, and Troublemaker, which partially aligned with the previous findings of McLarnon (2022). We also explored how age and sex predicted profile membership, and how the profiles were differentially associated with vulnerable narcissism, self-centeredness, and rejection sensitivity. Our findings underscore the potential value of using person-centered approaches to study the Dark Triad and offer insight into the generalizability, construct validity, and nomological network of the Dark Triad profiles.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".