Criminal responsibility evaluations: Benchmarking in different countries
Bibliographic record
Abstract
INTRODUCTION: Forensic psychiatrists, as well as other mental health professionals, provide the legal system with clinical information and assessments concerning the offenders’ functioning, mental state and capacities at the time of the alleged offense and/or trial. These forensic assessments play a crucial role in court, influencing subsequent decision-making on sentencing, placement, or treatment of mentally disordered offenders. OBJECTIVES: Determining criminal responsibility at the time of arrest Exploring the role of psychiatric disposals in different countries. METHODS: The information was primarily gathered through written sources: peer review articles, reports, and legislation. A literature search was performed in PubMed and PsycINFO using the following keywords: criminal responsibility (reports/evaluations), pre-trial assessment,psychiatric expert, (forensic) psychiatric assessment, sanity evaluation and insanity defense. Additional articles were identified through reference lists This resulted in 36 peer review articles and nine reports or book chapters. In addition, a leading expert (i.c. psychiatrist) from every country was contacted for providing information and validating the information from this article pertaining to their country. They suggested eight more articles or book chapters. The respondents represent the authors of this article. RESULTS: See table. CONCLUSIONS: In summary, it appears that there are distinct differences between the abovementioned countries with respect to criminal responsibility assessments. Although Canada is considered a pioneer with regard to forensic mental health, Britain, the Netherlands and Sweden appear to have a well-established system in conducting these assessments. In Sweden the system is very strict, meaning that all reports are delivered by a governmental agency with their own staff. The court orders the report from the agency and not from the experts. DISCLOSURE OF INTEREST: None Declared
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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 | 0.029 | 0.086 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.019 | 0.022 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".