The HEXACO Personality Space Before and After Re-Rotation to Approximate the Big Five Dimensions
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
We re-oriented the HEXACO personality dimensions to approximate the Big Five, using two measures of the Big Five as targets in a derivation sample and then in cross-validation samples. The HEXACO approximations of Big Five Agreeableness represented blends of HEXACO Agreeableness, Emotionality, and Honesty-Humility. The HEXACO approximations of Big Five Neuroticism represented blends of Emotionality with low Agreeableness and low Extraversion. The residual sixth dimension, unrelated to the Big Five, contrasted Honesty-Humility with HEXACO Agreeableness. We then examined, in additional samples, some correlates of the original and re-rotated HEXACO dimensions. In the original HEXACO factor space, Honesty-Humility was the strongest correlate of unethical behaviors (selfishness and cheating), participant age, and "assumed similarity" to a friend or partner. Upon re-rotation of the HEXACO factors, associations involving these variables were divided between Big Five Agreeableness and the residual sixth dimension. Sex differences were mainly associated with Emotionality but after re-rotation of the HEXACO factors were divided between Big Five Agreeableness and Neuroticism. We discuss the relative merits of the original and Big Five-targeted HEXACO dimensions with reference to the practical utility of Big Five Agreeableness and Neuroticism and the simplicity and theoretical interpretability of the original HEXACO factors.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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