Is the PCL-R Really the “Unparalleled” Measure of Offender Risk?
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
The declaration that the Psychopathy Checklist–Revised (PCL-R) is the “unparalleled” measure of offender risk prediction is challenged. It is argued that such an assertion reflects an ethnocentric view of research in the area and has led to unsubstantiated claims based on incomplete attempts at knowledge cumulation. In fact, another more comprehensive risk measure, the Level of Service Inventory–Revised, notably surpasses the PCL-R in predicting general (φ = .37 vs. .23) and violent recidivism, albeit only modestly so in the case of the latter (φ = .26 vs. .21). In addition, other problematic issues regarding the PCL-R are outlined. Finally, it is suggested that a more useful role for psychopathy in offender risk assessment may be in terms of the responsivity dimension in case management. Finally, the authors suggest further research directions that will aid in knowledge cumulation regarding the general utility of offender risk measures.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it