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Record W3007112033

Six-factor model of personality and psychometric properties of The HEXACO Personality inventory – Revised

2016· article· en· W3007112033 on OpenAlexaboutno aff
Tereza Záškodná, Daniel Dostál

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsPersonality Assessment InventoryPersonalityPsychologyClinical psychologySocial psychology
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.458
GPT teacher head0.543
Teacher spread0.085 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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