Moral Agency, Cognitive Distortion, and Narrative Strategy in the Rehabilitation of Sexual Offenders
Bibliographic record
Abstract
Abstract Employing a framework at the intersection of psychological anthropology and narrative theory, I provide a critique of Cognitive Behavior Therapy (CBT) approaches to sexual offender rehabilitation. I demonstrate that what forensic psychologists refer to as a “cognitive distortion” or “thinking error” is often embedded within a broader narrative, and that these narratives reveal the existence of identifiable strategies designed to communicate something salient, enduring, and moral about the offender. Through the examination of narratives offered by imprisoned sexual offenders, several such narrative strategies containing the seeds of moral agency are identified. It is suggested that CBT's current focus on cognitive distortions effectively eliminates this narrative context and thus serves to disguise and even eradicate the positive, moral notions of self that most offenders exhibit in some form or another. A rehabilitative approach that works with narrative, facilitating development of shared narratives among offenders and therapists, would allow for the emergence of a plan for morally agentive living, transcending what is currently possible within the hostile, challenging framework of CBT. [narrative theory; cognitive behavior therapy; moral agency; sexual offenders; prisons]
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".