Assessing Psychopathic Traits and Criminal Behavior in a Young Adult Female Community Sample Using the Self‐Report Psychopathy Scale
Bibliographic record
Abstract
This study assessed psychopathic traits in a nonforensic female population (N = 343). Respondents completed the Self-Report Psychopathy Scale-4: Short Form (SRP-SF) and also reported on their Criminal Behavior. The results revealed relatively higher scale elevations for the Interpersonal and Lifestyle SRP-SF facets, compared to the Affective and Antisocial facets. Also, those with a history of Criminal Behavior had significantly higher SRP-SF facet scores on all four psychopathy domains, compared to those without such history. Consistent with a number of previous studies, the structural equation modeling results revealed good fit for the four-factor SRP-SF model. In addition, a super-ordinate SRP-SF factor, which accounted for the majority variance of all four SRP-SF first-order factors, also accounted for 50% of the variance in a latent Criminal Behavior factor. Taken together, findings support use of the SRP-SF to assess psychopathic features in a moderately large sample of Belgium women.
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How this classification was reachedexpand
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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".