The Lost Art of the Plea Inquiry: Learning From the Past to Prevent Wrongful Convictions in the Future
Bibliographic record
Abstract
A guilty plea wrongful conviction occurs when an innocent person pleads guilty to a crime that they did not commit. Canada’s main procedural protection against guilty plea wrongful convictions is an inquiry, codified in sections 606(1.1) and (1.2) of the Criminal Code, that courts must conduct before accepting a plea from the accused. This plea inquiry requires that a court be satisfied of three conditions before accepting a guilty plea from an accused: (1) that the plea is voluntary, (2) that the plea is informed, and (3) that the facts support the charge. The goal of this article is to show that sections 606(1.1) and (1.2) offer insufficient protection against false guilty pleas and can be improved by learning from the early common law courts’ approach to plea inquiries. This article argues that when sections 606(1.1) and(1.2) were enacted in 2002, guilty plea wrongful convictions were poorly understood and, as a result, Parliament crystalized a plea inquiry that systematically fails to account for many recently recognized causes of false guilty pleas. However, this article suggests that sections 606(1.1) and (1.2) can be improvedby looking to the early common law, when courts were skeptical of guilty pleas and the risk of wrongful conviction. In particular, this article recommends three ways that sections 606(1.1) and (1.2) can be improved: (1) to conduct a full plea inquiry in every case, (2) to individualize the inquiry to the accused by considering their circumstances and motive for pleading guilty, and (3) to foster a skeptical attitude towards guilty pleas amongst the judiciary. This article further argues that these lessons can, at least in part, be implemented by challenging the constitutionality of sections606(1.1) and (1.2) under section 7 of the Charter.
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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 | 0.025 | 0.106 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.009 | 0.024 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".