Bibliographic record
Abstract
This essay develops a liberal account of the mens rea requirement of criminal liability and identifies the fault level required by that account. By “a liberal account” is meant one that interprets the meaning of mens rea in a way that reconciles liability to coercion with the individual's inviolability. The article argues that the wrongdoer's choice to interfere or to risk interfering with another agent's capacity to act on his own ends is the level of fault required to make punishment implicitly self-imposed by the recipient and thus distinguishable from the wrongdoer's violence. Such a choice is one to which a denial of rights of agency may be logically imputed, a denial by which the wrongdoer implicitly authorizes his own coercibility. This version of subjectivism is, I argue, invulnerable against criticisms leveled against other versions. While staking out defensible subjectivist ground, the article criticizes the character, choice, and opportunity theories of mens rea proposed by Fletcher, Moore, and Hart, and elaborates the interpretations of exculpatory conditions flowing from the subjectivist thesis. Finally, it addresses arguments advanced by Ripstein, Duff, and Horder for eliminating the requirement of a conscious choice to do that which amounts to a denial of rights.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.043 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".