Explanations of the criminality of the mentally ill
Bibliographic record
Abstract
HYPOTHESES This chapter critically reviews explanations of the criminality and violence perpetrated by persons suffering from major mental disorders. Three principal hypotheses are examined. Hypothesis 1: facilitated arrest and conviction Persons suffering from major mental disorders are not more likely to commit crimes than persons without these disorders. However, they are more likely to be detected by the police and successfully prosecuted. Consequently, studies find that greater proportions of persons with major disorders than persons without these disorders are convicted of crimes. It is further hypothesised that facilitated detection and successful prosecution of persons with major mental disorders also explains why offenders with these disorders accumulate, on average, more convictions than do offenders without these disorders. Hypothesis 2: inadequate and inappropriate treatment The implementation of the policy of deinstitutionalisation in the mental health field has led to a situation in which many persons with major mental disorders receive no treatment or inadequate and/or inappropriate treatment. This lack of care is associated with the commission of illegal acts. (2a) It is further hypothesised that because of this lack of adequate and appropriate treatment, persons with major mental disorders become symptomatic while living in the community. The development of psychotic symptoms generally but especially threat-control-override (TCO) symptoms is associated with aggressive behaviour. (2b) The lack of adequate and appropriate treatment has also created a context in which many persons with major mental disorders are using and abusing alcohol and drugs. Substance abuse is associated with criminal activity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".