Externalizing behavior and the higher order factors of the Big Five.
Bibliographic record
Abstract
The comorbidity of various externalizing behaviors stems from a broad predisposition that is strongly genetically determined (R. F. Krueger, B. M. Hicks, C. J. Patrick, S. R. Carlson, W. G. Iacono, & M. McGue, 2002). This finding raises the question of how externalizing behavior is related to broad personality traits that have been identified in normal populations and that also have a genetic component. Using structural equation modeling, the authors applied a hierarchical personality model based on the Big Five and their two higher order factors, Stability (Neuroticism reversed, Agreeableness, and Conscientiousness) and Plasticity (Extraversion and Openness). Cognitive ability was included to separate variance in Openness associated with Extraversion (hypothesized to be positively related to externalizing behavior) from variance in Openness associated with cognitive ability (negatively related to externalizing behavior). This model was used to predict a latent externalizing behavior variable in an adolescent male sample (N = 140) assessed through self- and teacher reports. As hypothesized, externalizing behavior was characterized by low Stability, high Plasticity, and low cognitive ability.
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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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".