Bibliographic record
Abstract
Negligence is a conceptually problematic mode of liability in the criminal law. In cases of negligence, the accused acts inadvertently; that is, the accused is not subjectively aware of the unjustified risk that is created by his or her conduct. As such, some have argued that the accused is not blameworthy, and thus that negligence is never an appropriate basis for criminal liability. But even if, as others have argued, criminal negligence can in certain circumstances be justified as an appropriate basis for imposing criminal liability either for utilitarian or deontological reasons, other questions arise. First, we need to know what the parameters of criminally negligent liability are so as to be able to distinguish criminal negligence from other modes of liability that bear some resemblance to negligence, such as recklessness (or rashness) and strict liability. Second, we need to know what the standard of care should be in offences of criminal negligence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.026 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.041 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.013 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".