Psychopathic Traits in Nursing and Criminal Justice Majors: A Pilot Study
Bibliographic record
Abstract
Prior findings suggest presence of psychopathic personality traits may be prevalent outside of the criminal sphere, such as in the business world. It is possible that particular work environments are attractive to individuals with higher psychopathic personality traits. To test this hypothesis, the current study investigated whether psychopathic personality scores could predict students' choices between two university majors, criminal justice or nursing (N= 174; 53 men, 121 women). Nursing education espouses nurturance and care, while criminal justice education teaches students informal and formal social control. Given these two educational mandates, it was predicted that students who scored higher on a scale of psychopathy would tend to enter criminal justice rather than nursing. Using logistic regression, results showed students with higher overall scores on the Psychopathic Personality Inventory, specifically higher scores on the subscale Machiavellian Egocentricity, were more likely to have chosen to major in criminal justice than nursing. Effects were generally weak but significant, accounting for between 5% to 25% of the variance in choice of major. Furthermore, this finding was not due to sex differences.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".