Bibliographic record
Abstract
This paper examines the issue of criminal responsibility and the role of legal excuses from two theoretical viewpoints : the character theory and the choice theory of responsibility. The character theory claims that the moral assessment of an offender's character is a necessary prerequisite of criminal liability and punishment. Legal excuses preclude the attribution of moral and legal blame because, by negating voluntariness, they block the inference from a wrongful act to a flawed character. The choice theory, on the other hand, claims that criminal responsibility pertains to the voluntary violation of the law rather than to the doing of an immoral act as such. For the choice theorist criminal responsibility is concerned with choices rather than with character traits. From this point of view, excuses are taken to preclude criminal liability because, when these conditions are present, the actor does not have sufficient capacity or a fair opportunity to choose to act according to law. The paper concludes that the character theory, by placing the emphasis on those character traits that motivate a person's choices offers a better basis for understanding the moral significance of human actions and for explaining and justifying the attribution of criminal responsibility and punishment.
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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 | 0.001 | 0.003 |
| 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 | 0.014 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".