Moral rightness and the significance of law: Why, how, and when mistake of law matters
Bibliographic record
Abstract
The question of whether a mistake of law should negate or mitigate criminal liability is commonly considered to be pertinent to the culpability of the agent, often examined in light of the (epistemic) reasonableness of the mistake. I argue that this view disregards an important aspect of this question; namely, whether a mistake of law affects the rightness of the action, particularly in light of the moral significance of the mistake. I argue that several plausible premises regarding moral rightness under uncertainty, the nature of law, and the moral significance of law entail a positive answer to this question. Specifically, I consider this argument: (1) one (subjective) sense of moral rightness depends on the (epistemically justified) belief of the agent concerning a non-moral fact that is morally significant; (2) a law is (partly) a non-moral fact; (3) a legal fact might be morally significant; (4) therefore, an action that is compatible with an applicable moral standard, in light of the mistaken (justified) belief of the agent concerning a morally significant law, is (subjectively) right or less wrongful; (5) the (subjective) moral rightness of an action counts against criminal liability for this action; (6) therefore, an action that is compatible with the applicable moral standard, in light of the mistaken (epistemically justified) belief of the agent, counts against criminal liability for the action if the law is morally significant.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".