Survival of the Scheming: A Genetically Informed Link Between the Dark Triad and Mental Toughness
Bibliographic record
Abstract
The present study is the first behavioral genetic investigation of the Dark Triad traits of personality, consisting of Machiavellianism, narcissism, and psychopathy, and the variable of mental toughness, reflecting individual differences in the ability to cope when under pressure. The purpose of this investigation was to explore a potential explanation for the success of individuals exhibiting the Dark Triad traits in workplace and social settings. Participants were adult twins who completed the MACH-IV, the Narcissistic Personality Inventory, and the Self-Report Psychopathy Scale assessing Machiavellianism, narcissism, and psychopathy, respectively, as well as the MT48, measuring mental toughness. Correlational analyses of the data revealed significant positive phenotypic associations between mental toughness and narcissism. Psychopathy and Machiavellianism, however, both showed some significant negative phenotypic correlations with mental toughness. Bivariate behavioral genetic analyses of the data were conducted to assess the extent to which these significant phenotypic correlations were attributable to common genetic and/or common environmental factors. Results indicate that correlations between narcissism and mental toughness were attributable primarily to common non-shared environmental factors, correlations between Machiavellianism and mental toughness were influenced by both common genetic and common non-shared environmental factors, and the correlations between psychopathy and mental toughness were attributable entirely to correlated genetic factors. Implications of these findings in the context of etiology and organizational adaptation are discussed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".