A General Factor of Personality From Multitrait–Multimethod Data and Cross–National Twins
Bibliographic record
Abstract
In three studies, a General Factor of Personality (GFP) was found to occupy the apex of the hierarchical structure. In Study 1, a GFP emerged independent of method variance and accounted for 54% of the reliable variance in a multitrait-multimethod assessment of 391 Italian high school students that used self-, teacher-, and parent-ratings on the Big Five Questionnaire - Children. In Study 2, a GFP was found in the seven dimensions of Cloninger's Temperament and Character Inventory as well as the Big Five of the NEO PI-R, with the GFPtci correlating r = .72 with the GFPneo. These results indicate that the GFP is practically the same in both test batteries, and its existence does not depend on being extracted using the Big Five model. The GFP accounted for 22% of the total variance in these trait measures, which were assessed in 651 pairs of 14- to 30-year-old Japanese twins. In Study 3, a GFP accounted for 32% of the total variance in nine scales derived from the NEO PI-R, the Humor Styles Questionnaire, and the Trait Emotional Intelligence Questionnaire assessed in 386 pairs of 18- to 74-year-old Canadian and U.S. twins. The GFP was found to be 50% heritable with high scores indicating openness, conscientiousness, sociability, agreeableness, emotional stability, good humor and emotional intelligence. The possible evolutionary origins of the GFP 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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".