Sentencing Reform in New Zealand: An Analysis of the Sentencing Act 2002
Bibliographic record
Abstract
Sweeping changes have recently been made to punishment practices in many western nations. A number of these have reflected punitive, penal populism. The purpose of this essay is to examine recent reforms in New Zealand which reflect a philosophy of “bifurcation” with respect to the punishment of offenders. Harsher treatment is introduced with respect to the more serious forms of offending, while at the same time other elements of the Sentencing Act represent a more rational and moderate approach to sentencing reform. The Sentencing Act 2002 introduces a number of changes to the sentencing process in New Zealand. This article reviews some of the more important elements of the Act, beginning with the legislated statement of the purposes and principles of sentencing. The statutory purposes include the goals of rehabilitation, deterrence and incapacitation that have been cited in similar statements in other jurisdictions. The author explores the significance of various components of the Sentencing Act in light of experience in other jurisdictions such as Canada and England and Wales. In a number of areas the New Zealand statute offers a superior alternative to statutory language adopted in other countries.
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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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".