Bibliographic record
Abstract
Psychopathy is a disorder of personality characterized by a lack of conscience, with emotional (interpersonal and affective) and behavioural (lifestyle and antisocial) characteristics.Psychopathy can also be scored along a continuum as a dimension of personality.Previous research has identified a link between psychopathy and reduced processing of emotional stimuli, as well as low empathy.Yet, one feature psychopathy is the ability to reproduce correct emotional responses despite reduced emotional and empathic experience, likely as a result of social learning.The present study evaluated perception of emotion and empathy relative to psychopathic traits in a sample of undergraduate students, and examined whether increasing the ambiguity of the stimuli would reveal deficits in emotion processing and empathy associated with psychopathy, which would provide further evidence of a learned response to emotional stimuli in individuals high in psychopathy.Rather than static images, the stimuli were dynamic video clips incorporating two types of emotion cues, facial expression and vocal affect, with varying levels of ambiguity in the expression of the emotion.These stimuli were used in four experiments in which emotion recognition and empathic response were measured in large samples of undergraduate participants.Across the four experiments, the predicted interaction between psychopathy and ambiguity of emotion cues was not observed.However, in all experiments, participants with higher levels of psychopathy had reduced emotion recognition accuracy and lower levels of empathy.The present study provides further evidence of an overall deficit in emotion processing in individuals high in psychopathy, and evidence of impaired empathic response using a novel objective measure of empathy.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".