Deterrence as a Principle of Youth Sentencing: No Effect on Youth, but a Significant Effect on Judges
Bibliographic record
Abstract
The use of deterrence as a factor in youth sentencing is controversial. Social science research consistently indicates that an increase in the severity of punishment imposed on adolescents does not affect the youth crime rate: youth who are prone to committing offences do not consider the likelihood or consequences of being apprehended. A survey of Canadian youth court judges’ attitudes regarding sentencing under the Young Offenders Act (YOA) reveals substantial variation in the extent to which they took deterrence into account. Judges’ own views on deterrence, rather than the nature of the offence, were most likely to influence the sentence. Even in light of these realities, deterrence is still being put forward, particularly within the political arena, as a means of reducing youth crime . In order to help address sentencing variation and the overuse of youth custody, the Youth Criminal Justice Act (YCJA) refrains from including deterrence as a principle of youth sentencing. The Supreme Court of Canada, in R. v. B.W.P., recently confirmed this position. Under the YCJA there has been a very significant decline in the use of youth custody, without an overall increase in the level of youth crime. Despite the large body of research doubting the value of deterrence in reducing youth crime, the Conservative government has proposed new legislation which will reintroduce deterrence as a principle of youth sentencing. The authors argue that the assumptions underlying this proposal are flawed, and further submit that if such a law is enacted, judges should take a narrow approach to the use of deterrence as a factor in sentencing youths. There is concern that using deterrence as a factor in youth sentencing will not reduce levels of youth crime, but will instead increase the use of custody. This will unnecessarily expose incarcerated youths to a culture of criminality and impose heavy personal costs on them, as well as financial burdens upon society .
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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 | 0.010 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".