“Mr. Big” Confessions, R v Hart, and a Proposal for a New Right of Appeal based upon Fundamental Post-conviction Changes to the Law
Bibliographic record
Abstract
In a 2014 decision, R v Hart, the Supreme Court of Canada (SCC) held that confessions obtained from undercover “Mr. Big” sting operations would henceforth by presumptively inadmissible as evidence in criminal trials. The new exclusionary rule was motivated by concerns about wrongful convictions arising from this type of confession, which is often unreliable and highly prejudicial to the accused. The advent of this new rule, however, casts doubt upon the reliability of past criminal convictions based upon “Mr. Big” confession evidence. Presently, there are only very limited avenues for post-conviction review based on subsequent fundamental changes to the law. Accordingly, a new statutory right of appeal is proposed to allow for reopening past cases when merited by fundamental post-conviction changes to the law.
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 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.032 | 0.026 |
| 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".