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Record W2464250145 · doi:10.1177/1073191116659134

Psychometric Properties of the HEXACO-100

2016· article· en· W2464250145 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAssessment · 2016
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsBrock UniversityUniversity of Calgary
Fundersnot available
KeywordsPsychologyPsychometricsClinical psychology

Abstract

fetched live from OpenAlex

Psychometric properties of the 100-item English-language HEXACO Personality Inventory-Revised (HEXACO-PI-R) were examined using samples of online respondents ( N = 100,318 self-reports) and of undergraduate students ( N = 2,868 self- and observer reports). The results were as follows: First, the hierarchical structure of the HEXACO-100 was clearly supported in two principal components analyses: each of the six factors was defined by its constituent facets and each of the 25 facets was defined by its constituent items. Second, the HEXACO-100 factor scales showed fairly low intercorrelations, with only one pair of scales (Honesty-Humility and Agreeableness) having an absolute correlation above .20 in self-report data. Third, the factor and facet scales showed strong self/observer convergent correlations, which far exceeded the self/observer discriminant correlations.

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.

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)0.000
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 score0.509
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.089
GPT teacher head0.382
Teacher spread0.293 · 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