Sentencing chronic offenders: 30 strikes and you're out?
Bibliographic record
Abstract
Canadian legislation surrounding sentencing has been prefaced by a statement of the purposes and principles of sentencing since 1996. This legislation identifies proportionality as the fundamental principle in sentencing, and states that sentences should be proportional to the gravity of the offence and the degree of responsibility of the offender. Although prior criminal record may be considered as an aggravating factor by the judiciary when deciding upon an appropriate sentence, our current legislation does not mirror other sentencing systems such as those seen in the United States, where a criminal record may at times form the sole basis for the increasing length of incarceration. The Canadian experience with the sentencing of chronic offenders is an important indicator of sentencing policy in practice. If proportionality is the primary goal of sentencing, how are Canadian judges handling those chronic property offenders who commit dozens or even hundreds of offences over their criminal history? Are sentences strictly controlled by the gravity of the instant offence or are they being inflated by the offender’s criminal history? The aim of this study is to examine if indicators of sentence inflation can be observed in the sentencing patterns for one such group of chronic offenders. In general, the results appear mixed, as some increasing severity outside of the nature of the offence can be seen in terms of denial of bail and imposition of a custodial sentence. However, analysis of the length of the custodial sentences does not clearly demonstrate substantial inflation over those that would be expected solely on the basis of proportionality even for the most incorrigible offenders. What this creates, however, is a revolving door for many of these offenders. The difficulty comes with trying to balance the needs of the public in terms of protection from such chronic offenders (Street Crime Working Group, 2005), while still adhering to the legislated purposes and principles of sentencing.
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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 | 0.006 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".