Sentencing Juvenile Offenders: Comparing Public Preferences and Judicial Practice
Bibliographic record
Abstract
The juvenile justice systems of most Western nations have been under considerable pressure to impose harsher penalties on juvenile offenders. Much of this pressure has come from politicians who argue that the public and juvenile courts are out of step, with the latter being more lenient than the public desire. This article reports findings from a representative national survey of the public, which permitted comparisons between the sentencing preferences of the public and the actual practice of youth courts. Respondents were asked to sentence offenders described in vignettes. The sentencing component employed a 2 × 2 × 2 design. The variables manipulated were age of offender (juvenile or adult), criminal history (first offender or recidivist), and nature of offence (burglary or assault). Results indicated concordance between the incarceration rates favored by members of the public and the practice of the courts. In addition, respondents were also asked questions about criminal victimization within the previous 12 months. Consistent with the findings of previous research, crime victims were no more punitive than respondents who did not report having been victimized.
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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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".