Six-factor model of personality and psychometric properties of The HEXACO Personality inventory – Revised
Bibliographic record
Abstract
According to the HEXACO six-factor personality model, the personality is best described by six dimensions. These are: Honesty-humility, Emotionality, Extraversion, Agreeableness, Conscientiousness and Openness to experience. The authors of the model – Michael C. Ashton and Kibeom Lee, refer to the possibility of a more differentiated depiction of personality structure and provide an alternative to other respected factorial models. While the sixfactor model is commonly used in Canada and in the USA, in the Czech Republic it is not. In the research, we strived to determine the basic parameters of the Czech version of the six-dimension method. Furthermore, we aimed to validate the HEXACO model structure using exploratory factor analysis. The participants consisted of 760 college students (221 males and 539 females) from more than 20 universities of the Czech Republic (e.g. Charles University in Prague, Masaryk University, Palacký University in Olomouc). The 100-item Personality Inventory HEXACOPI- R was used for measurement. It is self-report instrument that assesses the six major dimensions of personality. The internal-consistency reliabilities (Cronbach’s alpha) for the HEXACO-PI-R scales were high. The reliabilities ranged from .76 (Openness to Experience) to .88 (Extraversion) at the factor level. The 24 facet scales in the HEXACO-PI-R were submitted to a principal axis factor analysis. When these factors were rotated to a Varimax solution, a simple factor structure emerged (the sizes of the corresponding factor loading were big, ranging from .46 to .73). The mutual correlations among the six factor-level scales were low. The highest correlation (r = .28) was found between Honesty-Humility and Agreeableness. Discriminant validity was established. While the six dimensions of the HEXACO model showed high levels of the Cronbach’s alpha, some of the facet-level scales were low. Particularly the facet-levels of Openness to Experience seem a little problematic; alpha ranges from .40 (Unconventionality) to .62 (Aesthetic appreciation). But in general, Openness to Experience is the most controversial dimension in terms of the content interpretation. Ongoing work with the Czech translation of the items covered by this dimension is needed. To compare the two structures, the Czech and the original Canadian, we used the congruence calculation. It ranges from .93 (Honesty-Humility, Emotionality) to .96 (Conscientiousness). The Canadian and Czech factor structure show a high level of correspondence. Further work with the model should consider the critical comments concerning for example the inhomogeneous identification of the Honesty-Humility factor in different languages (De Raad et al., 2010). The Czech version of 100-item HEXACO-PI-R seems to be usable in our socio-culture conditions regarding its high Cronbach’s alpha, the validated six-factor model structure and the established discriminant validity.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".