A Critical Analysis of Post-Conviction Review in New South Wales, Australia
Bibliographic record
Abstract
Wrongful convictions leave an indelible mark on society. They are a tangible demonstration that the criminal legal system has failed, and a poignant reminder that all human institutions are fallible. Robust post-conviction review mechanisms are essential to provide an opportunity for justice to be eventually achieved for those who are wrongfully convicted. Through a critical examination of the post-conviction review mechanisms in NSW, which includes determining the existence of independence, transparency and accountability in the system, some deficiencies will be identified and analysed. Drawing on insights from the author’s role as a lawyer for Kathleen Folbigg (a woman convicted in 2003 of the murder of three of her infant children, and the manslaughter of her first child), this article will outline some of the key problems with the current system of post-conviction review in NSW. It then critically compares the existing system with the United Kingdom Criminal Cases Review Commission (“UK CCRC”). The UK CCRC has been chosen because it is a pioneering model which is designed to identify and remedy wrongful convictions in an independent, transparent, and accountable way. The article concludes that a version similar to the UK CCRC should be implemented in NSW to achieve justice for those wrongfully convicted.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.005 |
| 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) | 0.006 | 0.000 |
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".