Dissociation: Defining the Concept in Criminal Forensic Psychiatry.
Bibliographic record
Abstract
Claims of amnesia and dissociative experiences in association with a violent crime are not uncommon. Research has shown that dissociation is a risk factor for violence and is seen most often in crimes of extreme violence. The subject matter is most relevant to forensic psychiatry. Peritraumatic dissociation for instance, with or without a history of dissociative disorder, is quite frequently reported by offenders presenting for a forensic psychiatric examination. Dissociation or dissociative amnesia for serious offenses can have legal repercussions stemming from their relevance to the legal constructs of fitness to stand trial, criminal responsibility, and diminished capacity. The complexity in forensic psychiatric assessments often lies in the difficulty of connecting clinical symptomatology reported by violent offenders to a specific condition included in the Diagnostic and Statistical Manual of Mental Disorders (DSM). This article provides a review of diagnostic considerations with regard to dissociation across the DSM nomenclature, with a focus on the main clinical constructs related to dissociation. Forensic implications are discussed, along with some guides for the forensic evaluator of offenders presenting with dissociation.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".