Political Hearts of Darkness: The Dark Triad as Predictors of Political Orientations and Interest in Politics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: This study investigated the relationships between the Dark Triad of personality (sub-clinical psychopathy, Machiavellianism, and narcissism) and four political variables: socio-religious conservatism, support for greater economic equality, overall liberal-conservative orientation, and interest in politics. A theoretical approach that focused on the influence of the Dark Triad in large groups was provided to interpret those relationships. Methodological issues found in previous research that related to the use of abbreviated scales to measure the dark traits and the use of unidimensional indicators of political orientations were addressed. METHODS: A hierarchical regression analysis was conducted to determine whether any of the three dark traits could explain variance in the aforementioned political attributes over and above that accounted for by the Big Five, sex, age, and nationality, using the full personality scales and measures of political orientation that captured both social and economic liberalism-conservatism. RESULTS: Machiavellianism uniquely predicted lower levels of socio-religious conservatism, and both Machiavellianism and narcissism uniquely predicted lower levels of overall conservatism. CONCLUSIONS: There were important links between the Dark Triad and politics.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it