Recovering the HEXACO Personality Factors – and Psychoticism – From Variable Sets Assessing Normal and Abnormal Personality
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
Abstract. We examined the joint factor structure of the 30 facets of the NEO Personality Inventory – Revised (NEO-PI-R; or the NEO-PI-3) with either (a) the 25 facets of the Personality Inventory for DSM-5 (PID-5) or (b) the 15 facets of the Schedule for Nonadaptive and Adaptive Personality (SNAP) plus several dissociation scales, using self-reports from participant samples of previous research. The NEO-PI-R[3]/PID-5 variable set produced seven factors that represented the HEXACO factor space plus a “psychoticism” dimension. The NEO-PI-R/SNAP/dissociation variable set produced a similar set of seven factors. The results indicate that even some questionnaire variable sets not constructed to measure the HEXACO factors can recover those personality dimensions. Researchers interested in integrating the domains of normal and abnormal personality are advised to adopt a model consisting of six HEXACO-like dimensions plus a dimension of psychotic tendency.
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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 | 0.000 | 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