Between facets and domains: 10 aspects of the Big Five.
Bibliographic record
Abstract
Factor analyses of 75 facet scales from 2 major Big Five inventories, in the Eugene-Springfield community sample (N=481), produced a 2-factor solution for the 15 facets in each domain. These findings indicate the existence of 2 distinct (but correlated) aspects within each of the Big Five, representing an intermediate level of personality structure between facets and domains. The authors characterized these factors in detail at the item level by correlating factor scores with the International Personality Item Pool (L. R. Goldberg, 1999). These correlations allowed the construction of a 100-item measure of the 10 factors (the Big Five Aspect Scales [BFAS]), which was validated in a 2nd sample (N=480). Finally, the authors examined the correlations of the 10 factors with scores derived from 10 genetic factors that a previous study identified underlying the shared variance among the Revised NEO Personality Inventory facets (K. L. Jang et al., 2002). The correspondence was strong enough to suggest that the 10 aspects of the Big Five may have distinct biological substrates.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".