Moral self-convictions: uncontested pleas and Canadian criminal law
Bibliographic record
Abstract
An uncontested plea allows criminal defendants to self-convict without requiring the state to prove its case against them. Uncontested pleas may be inculpatory, exculpatory, or non-inculpatory. Guilty pleas are inculpatory uncontested pleas. When a defendant pleads guilty sincerely, they formally take responsibility for the offence and accept the consequences. Exculpatory and non-inculpatory uncontested pleas include best-interest pleas like \textit{Alford} and nolo contendere pleas, respectively. When a defendant enters one of these pleas, they agree to self-convict without formally taking responsibility for the offence. Statutory language formally forbids exculpatory and non-inculpatory uncontested pleas like nolo contendere pleas in Canada. I argue that the legal and ethical objections to these pleas and plea bargaining generally in Canada are largely misplaced. Nolo contendere pleas open new avenues of plea bargaining for defendants and prosecutors to explore, creating new opportunities for certainty, factual accuracy, agency, and mutual advantage in otherwise highly adversarial proceedings. Although formally forbidden, defendants may still enter nolo contendere informally and surreptitiously. I conclude by arguing that these pleas be formalized and proposing ways to do so.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.016 | 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".