Serious and Violent Young Offenders’ Decisions to Recidivate: An Assessment of Five Sentencing Models
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Five models of sentencing were assessed with respect to their impact on the decisions of young offenders to recidivate. The five sentencing models tested were fairness, deterrence, chronic offender lifestyle, special needs, and procedural rights. A sample of 400 incarcerated young offenders from the Vancouver, British Columbia, metropolitan area were asked questions regarding their attitudes toward these sentencing models and their intentions to recidivate after serving a period of incarceration. Principal components analyses suggested that although these models do not function independently, two composite models do shed some light on the issues that young offenders consider when contemplating their decisions and intentions to recidivate. Despite the ability of these models to predict half of the explained variance in young offenders’ decisions regarding recidivism, a majority of the sample appeared to not be affected exclusively by cost-benefit analysis, punishment, or reintegrative motivations. The authors conclude that without additional variables and even higher predictive validity, it is premature for policy makers to focus on any single model of sentencing in constructing juvenile justice laws.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it