The HEXACO Personality Factors in the Indigenous Personality Lexicons of English and 11 Other Languages
Bibliographic record
Abstract
Two studies tested the correspondence between six dimensions obtained in lexical studies of personality structure and the proposed HEXACO personality framework. Study 1 examined the English personality lexicon using 449 adjectives selected according to rated frequency of use in personality description. Six validimax-rotated factors derived from adjective self-ratings showed strong convergent and weak discriminant correlations with questionnaire markers of the HEXACO factors; the six adjective dimensions were also recovered from peer ratings. In Study 2, lay judges rated the conceptual similarity between HEXACO factor descriptions and adjective lists summarizing the six indigenous lexical personality factors of each of 12 languages. Across languages, a pattern of strong convergent and weak discriminant similarity ratings was observed; similarity ratings for the English factors of Study 1 were comparable to those for other languages' factors. Results indicate that the six dimensions of the HEXACO framework are recovered from the personality lexicons of various languages.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".