Homicide Law in Comparative Perspective
Bibliographic record
Abstract
A number of jurisdictions world-wide have changed or are considering changing their homicide laws. Important changes have now been recommended for England and Wales, and these changes are an important focus in this book, which brings together leading experts from jurisdictions across the globe – England, Wales, the US, Canada, France, Germany, Scotland, Australia, Singapore, and Malaysia – to examine key aspects of the law of homicide. Key areas include the structure of the law of homicide and the meaning of fault elements. For example, the definition of murder, or its equivalent, is very different in France and Germany when compared to the definition used in England and Wales. French law, like the law in a number of US states, ties the definition of murder to the presence or absence of premeditation, unlike the law in England and Wales. Unlike most other jurisdictions, German law makes the killer’s motive, such as a sadistic sexual motive, relevant to whether or not he or she committed the worst kind of homicide. England and Wales are in a minority of English-speaking jurisdictions in that these two countries do not employ the concept of ‘wicked’ recklessness, or of extreme indifference, as a fault element in homicide. Understanding these often subtle differences between the approaches of different jurisdictions to the definition of homicide is an essential aspect of the law reform process, and of legal study and scholarship in criminal law. Every jurisdiction tries to learn from the experience of others. Homicide Law in Comparative Perspective – edited by one of the UK’s leading law experts – contributes to that process and provides a lively and informative resource for scholars and students.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".