Beyond Openness to Experience and Conscientiousness: Testing links between lower‐level personality traits and American political orientation
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
INTRODUCTION: Research has consistently revealed positive correlations between political liberalism and Openness to Experience, and between conservatism and Conscientiousness. Most of this research has made use of domain-level models of the Big Five personality traits. Recent work suggests, however, that each Big Five trait domain can be divided into distinct aspects or facets, which offer more nuanced characterizations of each trait. METHODS: Across four studies (Ns ranging from 1,123 to 116,406), the present research examined the degree to which distinct lower-level traits would be associated with meaningful differences in political orientation. United States residents completed two different hierarchical Big Five personality measures (the Big Five Aspect Scales and the Big Five Inventory-2), as well as a range of measures of political orientation. RESULTS: Across both personality measures, liberal political orientation showed distinct positive associations with the lower-level traits Openness/Aesthetic Sensitivity, Intellect/Intellectual Curiosity, Compassion, and Withdrawal/Depression, as well as distinct negative associations with Orderliness/Organization, Politeness, and Assertiveness. DISCUSSION: By examining individual differences at a higher level of granularity, these data provide insight into specific motivations that predispose individuals toward different ends of the political spectrum.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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