How Joint Enterprise Liability Neutered the Criminal Cases Review Commission in England
Bibliographic record
Abstract
In 2016 the English Supreme Court changed the law concerning joint enterprise liablity ub R v Jogee. The decision appeared to provide a remedy for secondary parties that had been convicted under the, albeit faithful application of the old law. The requirement, however, to demonstrate a substantial injustice following the subsequent case of Johnson significantly curtailed the number of appeals based on this change in the law. The substantial injustice test is applied by the English Criminal Cases Review Commission (CCRC) prior to the application of the statutory real possibility test. Up until now, there has not been any research that examines the impact of this situation and the extent that it constricts any remedy for secondary parties convicted under joint enterprise liability. Using findings from the first study to explore this concept this work examines the limiting effect of the substantial injustice test on the CCRC, explores the application of the corrected law from Jogee, and shows the low number of applicants to the CCRC that identify as black British, despite existing research suggesting this demographic has the highest conviction rate for joint enterprise.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".