Remorse, psychopathology, psychopathic characteristics, and recidivism among adolescent offenders
Bibliographic record
Abstract
Remorse has long been considered important to the juvenile justice system.However, the nature of this construct has not yet been clearly articulated, and little research has examined its associations with other theoretically and legally relevant variables.The present study was intended to address these issues by examining relationships among remorse, psychopathology, psychopathic characteristics, and recidivism in a sample of adolescent offenders (N = 97) using the theoretically and empirically established framework of guilt and shame (Tangney & Dearing, 2002).Findings indicated that guilt was negatively related to recidivism, psychopathic characteristics, anger problems, depression, and anxiety.Furthermore, guilt provided incremental validity beyond established risk factors for offending and existing measures of "remorse" in the prediction of recidivism.In contrast to guilt, shame was positively related to recidivism, behavioural features of psychopathy, and numerous mental health problems.Moreover, the externalization of blame that is considered an important feature of shame provided incremental validity in the prediction of recidivism beyond established risk factors for offending as well as existing measures of "remorse".These results suggest that assessment of guilt, shame, and externalization of blame may be of greater utility than "remorse", and also underscore these features as potentially important treatment targets for adolescent offenders.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".