Fifty Shades of Risk? Psychopathic Traits, Gender, and Risky Behaviour
Bibliographic record
Abstract
The purpose of this study was to determine what effect psychopathic traits and gender have upon risk-taking behaviours across multiple domains. Although psychopathy is associated with risk for violent/criminal behaviours, few studies have addressed psychopathic traits in relation to other types of risk, including whether different risk patterns are manifested across genders. Participants (N = 540) were assessed for psychopathic traits and then were asked to complete measures evaluating risk-related attitudes/behaviours (i.e., domain-specific, sexual behaviours, drug use). Results indicated that males generally reported higher levels of risk taking, although scored similarly to females on social risk and below females on sexual risk. Those high in psychopathic traits engaged in more risk across the board, which was primarily related to traits of fearlessness, rebellious nonconformity, and egocentricity. Risk consequence information impacted reported behaviours in the negative condition, possibly due to several reporting biases. Implications concerning methods of assessing risk and factors predictive of risk are discussed. Faculty Mentor: Kristine Peace Department: Psychology
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".