One- Through Six-Component Solutions from Ratings on Familiar English Personality-Descriptive Adjectives
Why this work is in the frame
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Bibliographic record
Abstract
We report solutions for one through six components for self-ratings (N = 559) on 449 familiar English personality-descriptive adjectives (see Lee & Ashton, 2008 ). The first unrotated component mainly contrasted desirable with undesirable characteristics. The varimax-rotated two-component solution contained dimensions closely resembling the Social Self-Regulation and Dynamism constructs of Saucier et al. (2014) . The three-component solution contained dimensions closely resembling the Affiliation, Dynamism, and Order constructs of De Raad et al. (2014) . In the four-component solution, an Emotional Stability dimension emerged, absorbing some variance from dimensions of the three-component solution. The five-component solution added an Intellect/Imagination/Unconventionality (Openness) component, and thus resembled the classic Big Five structure (e.g., Goldberg, 1990 ). In the six-component solution, the variance of the Big Five Agreeableness and Emotional Stability components was reorganized, producing components corresponding to HEXACO Agreeableness and to rotated variants of HEXACO Emotionality and Honesty-Humility. Solutions based on peer ratings (N = 303) were generally similar to those based on self-ratings, but showed a much larger first unrotated component.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it