On the relations between HEXACO agreeableness (versus anger) and honesty‐humility
Bibliographic record
Abstract
The HEXACO personality factors of Agreeableness-versus-Anger (A) and Honesty-Humility (H) are interpreted as two complementary aspects of reciprocal altruistic tendency. Here we consider several ways of representing the positive associations between the defining traits of A and of H, through common factor analysis of self-report HEXACO Personality Inventory-Revised (HEXACO-PI-R) facet scale scores (N ≈ 111,000). We describe orthogonal solutions that differ in the extent to which H facets show secondary loadings on A (and vice versa), as well as an oblique solution compatible with a higher-order "cooperativeness" factor. We discuss the psychological plausibility of these solutions, and we review research showing differential associations of several phenomena or outcomes with A and H. We conclude that the optimal representation of A/H trait associations is not yet known but that the value of separate A and H factor scales is well established.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".