A General Factor of Personality (GFP) from two meta-analyses of the Big Five: and
Why this work is in the frame
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Bibliographic record
Abstract
In two studies, we used structural equation models to test the hypothesis that a General Factor of Personality (GFP) occupies the apex of the hierarchy of personality. In Study 1, we found a GFP that explained 45% of the reliable variance in a model that went from the Big Five to the Big Two to the Big One in the 14 studies of inter-scale correlations ( N = 4496) assembled by Digman (1997). A higher order factor of Alpha/Stability was defined by Conscientiousness, Emotional Stability, and Agreeableness, with loadings of from 0.61 to 0.70, while Beta/Plasticity was defined by Openness and Extraversion with loadings of 0.55 and 0.77. In turn, the GFP was defined by Alpha and Beta with loadings of 0.67. In Study 2, a GFP explained 44% of the reliable variance in a similar model using data from a published meta-analysis of the Big Five ( N = 4000) by Mount, Barrick, Scullen, and Rounds (2005). Strong general factors such as these, based on large data sets with good model fits that cross validate perfectly, are unlikely to be due to artifacts and response sets.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it