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Record W2075134121 · doi:10.1037/0022-3514.91.6.1138

Higher-order factors of the Big Five in a multi-informant sample.

2006· article· en· W2075134121 on OpenAlexfundno aff
Colin G. DeYoung

Bibliographic record

VenueJournal of Personality and Social Psychology · 2006
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyConscientiousnessAgreeablenessExtraversion and introversionHierarchical structure of the Big FiveBig Five personality traitsNeuroticismOpenness to experienceAdjectiveSocial psychologyDevelopmental psychologyPersonalityLinguistics

Abstract

fetched live from OpenAlex

In a large community sample (N=490), the Big Five were not orthogonal when modeled as latent variables representing the shared variance of reports from 4 different informants. Additionally, the standard higher-order factor structure was present in latent space: Neuroticism (reversed), Agreeableness, and Conscientiousness formed one factor, labeled Stability, and Extraversion and Openness/Intellect formed a second factor, labeled Plasticity. Comparison of two instruments, the Big Five Inventory and the Mini-Markers, supported the hypotheses that single-adjective rating instruments are likely to yield lower interrater agreement than phrase rating instruments and that lower interrater agreement is associated with weaker correlations among the Big Five and a less coherent higher-order factor structure. In conclusion, an interpretation of the higher-order factors is discussed, including possible neurobiological substrates.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.098
GPT teacher head0.382
Teacher spread0.284 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

Quick stats

Citations941
Published2006
Admission routes1
Has abstractyes

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