The constitutionality of minimum mandatory sentencing regimes: a rejoinder
Bibliographic record
Abstract
This rejoinder is a reply to an article published in the JJA by Anthony Gray and Gerard Elmore, which argued that minimum mandatory sentencing provisions undermine judicial independence and breach the principle of separation of powers, resulting in a loss of public confidence in the independence of the judiciary. This rejoinder challenges such an argument on five grounds. First, historically, the Crown and later the Parliament decreed the sentence for a particular offence, such as death for murder, which judges were bound to enforce. Second, there is nothing in the Commonwealth of Australia Constitution Act, and Chapter III in particular, to indicate Parliamentary control of sentencing impacts in any way on the 'autochthonous expedient'. Third, s51 of the Australian Constitution, which lists the legislative powers of the Federal Parliament, does not include criminal laws which are the province of the States. Fourth, no support can be found in overseas jurisdictions such as the United States, the United Kingdom, and Canada. Fifth, public confidence in the judiciary has been undermined by inadequate and inconsistent sentencing by the judiciary, which has led some State Parliaments to introduce legislation setting down mandatory sentences and/or sentencing guidelines.
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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 | 0.053 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.026 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.009 | 0.013 |
| Research integrity | 0.064 | 0.078 |
| Insufficient payload (model declined to judge) | 0.003 | 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".