Forensic psychiatry, ethics and protective sentencing: what are the limits of psychiatric participation in the criminal justice process?
Bibliographic record
Abstract
As clinicians, psychiatrists are unequivocally dedicated to relieving the suffering of those who are afflicted with mental disorders. However, the public and those individuals, who are assessed, find it difficult to draw a distinction between forensic psychiatrists acting in a clinical role and the very same professionals acting in an evaluative role, on behalf of the state. This paper examines the ethical issues raised by psychiatric involvement in the sentencing process. It rejects the view that a forensic psychiatrist, who undertakes an evaluation for the state, is to be considered as an advocate of justice who is not bound by conventional ethical duties to the individual whom he or she assesses. It contends that the forensic psychiatrist has an important role to play in presenting evidence that may result in the mitigation of the sentence that may be imposed on a person who is mentally disordered. The paper will focus on these issues in the particular context of the situation in England and Wales, Canada and the United States.
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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 | 0.032 | 0.086 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.069 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.012 | 0.010 |
| 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".