A Quantitative Review of the Comprehensiveness of the Five-Factor Model in Relation to Popular Personality Inventories
Why this work is in the frame
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Bibliographic record
Abstract
Reports of associations between the five-factor model (FFM) and the scales of popular personality inventories have generated controversy regarding the comprehensiveness of the FFM. The controversy is fueled by a preoccupation with capturing scale variance and differentiating between specific scales, whereas the focus should instead be on whether the FFM captures the common variance and the dimensions that exist in personality constructs. Analyses of published data revealed that the portions of scale variance captured by the FFM (mean = 38%) were substantial when evaluated in relation to the portions of common variance that exist in most personality inventories (mean = 50%). Furthermore, interbattery factor analyses indicated that the factor structures in most personality inventories can be closely replicated using data derived solely from scale associations with the FFM. Exceptions to this finding occurred for only 2 of 28 personality inventories. The findings support the comprehensiveness of the FFM.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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