Bibliographic record
Abstract
It is known that having a psychopathic partner is physically and emotionally detrimental, and that psychopaths receive harsher sentences than those who do not have the psychopathic label.And yet, jurors, or laypeople more broadly, do not have a thorough understanding of psychopathy.Thus the goals of this research were twofold: 1) to examine laypeople's understanding and attitudes about psychopathy, and 2) to test if an educational experimental manipulation can improve laypeople's conception of this disorder.Study 1 revealed that in a sample of 286, lay participants continue to have a poor understanding and inaccurate attitudes about psychopathy in similar areas as previous research suggests.In Study 2, a sample of 259 lay participants was randomly assigned to watch a control video describing myths associated with dog training or a video describing myths associated with psychopathy.Compared to a control video, watching a short educational video about psychopathy helped reduce lay participants' confusion of psychopathic with non-psychopathic traits, and ameliorate lay participants' misguided attitudes about psychopathy.This has promising implications for mental health research more generally in the context of reducing stigma and its associated negative consequences.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".