Restorative Justice in Australia and New Zealand
Bibliographic record
Abstract
Within the global growth of restorative justice, Australia and Aotearoa/New Zealand (henceforth New Zealand) are often considered as exemplars of restorative justice practices. These countries were among the first to widely implement the use of restorative justice in the late 1980s and 1990s, and both countries remain among the few where restorative justice is legislated across all jurisdictions for use in youth offending. Contrary to grassroots development in Canada and the United States, restorative justice programmes in Australia and New Zealand were initially implemented in a more ‘top-down’ approach through legislation. This top-down approach has resulted in restorative justice being widely available for young people and those they have harmed. However, existing research and evaluation studies demonstrate that restorative justice programmes in both countries face several challenges related to the relatively high level of institutionalisation. Some of these challenges – in particular, the co-option of restorative justice for other administrative or criminal justice system goals – are common throughout literature on the topic in many countries. Other challenges and problems, explored herein, remain more specific to the context of Australia and New Zealand.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".