I Love the Way You Lie: Investigating the Relationship Between Psychopathic Tendencies and Lying Behaviour
Bibliographic record
Abstract
Lying is considered a common behaviour that individuals engage in on a daily basis.Prior research indicated that the presence of certain personality traits, such as psychopathy, impacts the inclination to lie.I examined subclinical psychopathy, plus other variables, in predicting self-reported lying frequency, level of enjoyment received from lying, and motivations for lying in different contexts, in a sample of undergraduate (n = 91) and community (n = 61) participants.I hypothesized that individuals with subclinical psychopathy will have a greater tendency to lie across situations and enjoy it.Subclinical psychopathy was the only consistent predictor for all lying behaviour measures across samples.However, psychopathy did not predict lying behaviour across all contexts in which one could engage in deception.These findings enhance our understanding that specific features of psychopathy exist in subclinical, non-forensic populations, and they can predict behaviours such as lying.
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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 | 0.009 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".