Treatment of psychopathic offenders: Evidence, issues, and controversies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Psychopathic offenders are a notoriously challenging population to treat, who are often recalcitrant to change and at high risk for program non-completion and recidivism. The present work is a review and synthesis of the evidence, issues, and controversies in the treatment of psychopathic offenders. The operationalization and measurement of the construct of psychopathy via the Hare Psychopathy Checklist–Revised is reviewed to give context to the population being treated and to identify latent features of the syndrome that have risk and treatment implications. A discussion of the issues and challenges in the treatment of psychopathic offenders is then provided to contextualize the source of therapeutic pessimism with this population, followed by a review of the existing psychopathy treatment literature. The characteristics of unsuccessful and encouraging treatment programs, including a promising model of treatment, are subsequently reviewed, and the article finishes with a synopsis of recent treatment outcome findings published subsequent to previous psychopathy treatment reviews or inadvertently overlooked by past reviews. Although psychopathic offenders are a challenging population to treat, I argue that they are not immune to making positive lifestyle and behavioural changes, and that these individuals have the potential to benefit if they can be retained in treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it