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
This study aimed to determine the cross-ethnic stability of the predictive relationship of psychopathy for violence. Participants were 424 adult male jail inmates. Psychopathy was assessed using the Psychopathy Checklist-Revised and criminal violence was assessed using a comprehensive database of arrests for violent crimes. Ethnic categories included the groups that make up the vast majority of U.S. inmates: European American (EA, n = 166), African American (AA, n = 174), and Latino American (LA, n = 84). Ethnically aggregated Cox regression survival analyses identified predictive effects for psychopathy. Disaggregated analyses identified ethnic differences: Psychopathy was more strongly predictive of violence among EA (R² = .13, 95% CI [.04, .22], p < .01) relative to AA inmates (R² = .05, 95% CI [.00, .11], p < .01) and was not related to violence among LA participants (R² = .02, 95% CI [.00, .08], p = .22). Receiver operating characteristic curve analyses yielded an equivalent pattern of results. These findings add to a growing literature suggesting cross-ethnic variability in the predictive power of psychopathy for violence.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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