De zes belangrijkste persoonlijkheidsdimensies en de HEXACO Persoonlijkheidsvragenlijst
Bibliographic record
Abstract
The six most important personality dimensions and the HEXACO Personality Inventory The six most important personality dimensions and the HEXACO Personality Inventory R.E. de Vries, M.C. Ashton & K. Lee, Gedrag & Organisatie, volume 22, September 2009, nr. 3, pp. 232-274 Recent lexical research on the structure of personality has revealed six independent and cross-cultural corresponding dimensions of personality in the same datasets that have led to the emergence of the Big Five model of personality. These six dimensions, Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness to Experience, constitute the HEXACO model of personality. In two studies, the psychometric properties of the Dutch HEXACO Personality Inventory (HEXACO-PI) and the Dutch HEXACO Personality Inventory-Revised (HEXACO-PI-R) and the relations of its factor- and facet-scales with background variables, the NEO-PI-R, the Dutch Personality Questionnaire (DPQ), and the Sensation Seeking Scale (SSS) are investigated. The results show that the HEXACO-PI(-R) has sound psychometric properties and is meaningfully related to the abovementioned questionnaires. Implications for personality research and assessment are discussed.
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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 | 0.007 |
| 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 | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.006 |
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".