Bibliographic record
Abstract
This chapter examines influential legislative remedies: the 1907 creation of the Court of Criminal Appeal, the 1995 creation of the Criminal Cases Review Commission (CCRC) and the 2024 legislation to annul and compensate miscarriages of justice caused by the Post Office’s faulty computer system. The Court of Appeal’s restrictive approach to overturning convictions and admitting new evidence is critiqued. The role of wrongful convictions in abolishing the death penalty is examined. The CCRC’s performance, including some of its failures and underfunding, is assessed. The migration of similar institutions to Scotland, Norway, New Zealand and Canada is also examined. Failed attempts in 2006 to limit appeals to innocence and successful attempts in 2014 to require it for compensation are critically assessed. The tension between the Innocence Network of the United Kingdom’s (INUK) focus on innocence and the legal system’s focus on the safety of convictions is analysed in light of INUK’s demise and future evolution of innocence organisations. Finally, the Post Office Scandal and the implications of enacting legislation to depart from ordinary methods of correcting and compensating miscarriages of justice are assessed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.478 | 0.253 |
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".