Bibliographic record
Abstract
In September 2010, at a two-day seminar on wrongful convictions at the National Institute of Justice, Washington DC, the first author witnessed an impassioned critique of the Criminal Cases Review Commission (‘the Commission’) that sowed the seeds for this book. With only forty or so participants, most of them US academics, criminal justice practitioners, and staff at the Department of Justice, it was a restrained event, with several presentations and time for discussion. Given the primary focus on the US, contributions from the Chair of the Commission and a lay member of its sister Commission in Scotland were a welcome counterpart to debates about the efficacy of innocence projects across the US. But while most talks were met with polite questions and comments, the presentation by the Chair of the Commission, elicited an astonishing onslaught from the only other English academic present. The Commission’s Chair, Richard Foster, had explained to those present that it reviews possible wrongful convictions in England, Wales, and Northern Ireland and refers back to the Court of Appeal (‘the Court’)1 cases in which it considers there to be a ‘real possibility’ that the Court will deem the conviction to be unsafe. While the talk was informative, it was also unremarkable: a description of the aims of the Commission and a summary of the numbers of cases received and the proportion referred for fresh appeals. The critic’s impassioned outburst claimed that for some applicants at least, the Commission was a failing and unaccountable body that should not be the model for reform elsewhere. He attacked its rationale and remit, and claimed that there was an unacceptably low proportion of deserving cases referred back to the Court. His most intriguing point was the reason he adduced for this alleged failing: an accusation that the Commission simply did not care about innocence. Later, as experts from New Zealand and Canada told of their countries’ interest in the Commission as a model for reform of their own post-conviction review procedures, he took further opportunities to diminish the Commission’s apparent strengths.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.694 | 0.518 |
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".