Beyond the Big Five: The Dark Triad and the Supernumerary Personality Inventory
Bibliographic record
Abstract
The Dark Triad of personality, comprising Machiavellianism, narcissism, and psychopathy, was investigated in relation to the Supernumerary Personality Inventory (SPI) traits, because both sets of variables are predominantly distinct from the Big Five model of personality. Correlational and principal factor analyses were conducted to assess the relations between the Dark Triad and SPI traits. Multivariate behavioral genetic model-fitting analyses were also conducted to determine the correlated genetic and/or environmental underpinnings of the observed phenotypic correlations. Participants were 358 monozygotic and 98 same-sex dizygotic adult twin pairs from North America. As predicted, results revealed significant correlations between the Dark Triad and most SPI traits, and these correlations were primarily attributable to common genetic and non-shared environmental factors, except in the case of Machiavellianism, where shared environmental effects emerged. Three correlated factors were extracted during joint factor analysis of the Dark Triad and SPI traits, as well as a heritable general factor of personality - results that clarified the structure of the Dark Triad construct. It is concluded that the Dark Triad represents an exploitative and antisocial construct that extends beyond the Big Five model and shares a theoretical space with the SPI traits.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".