The National Trajectory Project of Individuals Found Not Criminally Responsible on Account of Mental Disorder. Part 5: How Essential are Gender-Specific Forensic Psychiatric Services?
Bibliographic record
Abstract
OBJECTIVE: To state the sociodemographic characteristics, mental health histories, index offence characteristics, and criminal histories of male and female forensic psychiatric patients. Clinicians and researchers advocate that mental health and criminal justice organizations implement gender-specific services; however, few studies have sampled forensic patients to evaluate the extent to which men's and women's treatment and management needs are different. METHOD: Data were collected from Review Board files from May 2000 to April 2005 in the 3 largest Canadian provinces. Using official criminal records, participants were followed for 3 to 8 years, until December 2008. The final sample comprised 1800 individuals: 15.6% were women and 84.4% were men. RESULTS: There were few demographic differences, but women had higher psychosocial functioning than men. Both men and women had extensive mental health histories; women were more likely diagnosed with mood disorders and PDs and men were more likely diagnosed with schizophrenia spectrum disorders and SUDs. The nature of the index offence did not differ by gender, except women were more likely to have perpetrated murders and attempted murders. For offences against a person, women were more likely to offend against offspring and partners and less likely to offend against strangers, compared with men. Women had significantly less extensive criminal histories than men. CONCLUSIONS: Not criminally responsible on account of mental disorder-accused women have a distinct psychosocial, clinical, and criminological profile from their male counterparts, which may suggest gender-specific assessment, risk management, and treatment in forensic services could benefit patients. The findings are also consistent with traditional models (Risk-Need-Responsivity) and ultimately demonstrate the importance of individual assessment and client-centred services.
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.
How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".