Historiese oorsig oor die hantering van psigiatriese pasiënte met misdadige neigings
Bibliographic record
Abstract
This article gives a historic overview of the origin and development pertaining to the management of accused persons in criminal trials and who suffered from mental illness or mental deficiency at the time when the offence was committed. What makes the issue complicated is that legal insanity cannot be equated with mental illness or deficiency, for legal insanity is a test of capacity for action and choice and it is a formulation designed to determine responsibility. Therefore it is not whether a person suffered from some form of mental illness but whether as a result of a mental illness, the person lacked discernment and control over her/his actions at the time he/she acted. The author traces back the origin of Anglo-American law to the Greek and Roman philosophies and legal systems. Subsequently developments are discussed which took place during the medieval period and amongst others the views of Henrici Bracton, Edward Coke and Matthew Hale are expounded upon. Furthermore attention is also given to the McNaghten rules, the Irresistible impulse rule, the Durham rule and the American Law Institute formula. Regarding the insanity defense this article also addresses briefly the legal systems of a few selected countries (USA, UK, Canada, Sweden, Israel and South Africa) with divergent legal systems and it is revealing to reflect on the approaches of these systems and their own national identities.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".