The HEXACO-60: A Short Measure of the Major Dimensions of Personality
Bibliographic record
Abstract
We describe the HEXACO–60, a short personality inventory that assesses the 6 dimensions of the HEXACO model of personality structure. We selected the 10 items of each of the 6 scales from the longer HEXACO Personality Inventory–Revised (Ashton & Lee, 2008 Ashton, M. C. and Lee, K. 2008. The prediction of Honesty-Humility-related criteria by the HEXACO and Five-Factor models of personality. Journal of Research in Personality., 42: 1216–1228. [Crossref], [Web of Science ®] , [Google Scholar]; Lee & Ashton, 2004 Lee, K. and Ashton, M. C. 2004. Psychometric properties of the HEXACO personality inventory. Multivariate Behavioral Research, 39: 329–358. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar], 2006 Lee, K. and Ashton, M. C. 2006. Further assessment of the HEXACO Personality Inventory: Two new facet scales and an observer report form. Psychological Assessment, 18: 182–191. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]), with the aim of representing the broad range of content that defines each dimension. In self-report data from samples of college students and community adults, the scales showed reasonably high levels of internal consistency reliability and rather low interscale correlations. Correlations of the HEXACO–60 scales with measures of the Big Five factors were consistent with theoretical expectations, and convergent correlations between self-reports and observer reports on the HEXACO–60 scales were high, averaging above .50. We recommend the HEXACO–60 for use in personality assessment contexts in which administration time is limited.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".