Dangerous Offenders: An Analysis of Judicial Sentencing Decisions
Bibliographic record
Abstract
Objective: The present study explored Dangerous Offender (DO) judicial sentencing decisions in Canada by examining judicial decision maker’s written comments regarding a) experts’ ratings of risk, treatment amenability, and risk management in the community, b) partisanship, c) experts’ discussion of static, dynamic, and protective factors, d) the effect of the 2008 legislation change, e) ethnicity, and f) jurisdictional differences. Method: The study was archival and retrospective. There were 140 written sentencing decisions identified in four Canadian provinces (BC, AB, SK, and MB) via CanLII (publicly accessible) between July 2, 2008 and July 2, 2018. Results: Results indicate that the judicial decision makers’ interpretation of experts’ ratings of risk, treatment amenability, and risk management in the community were strongly associated with and significantly contributed to penalty outcomes. Generally, the trend that appeared was that the judicial decision makers’ interpretation of lower risk ratings, higher ratings of treatment amenability, and higher risk manageability in the community resulted in a much lower likelihood a Defendant would receive an indeterminate sentence. Moreover, the results suggest that the judicial makers’ note a substantial amount of agreement on all three assessment areas when multiple experts are present. The judicial decision makers’ interpretation of the experts’ discussion of static, dynamic, or protective factors was not influential on outcomes. The 2008 legislation change appears to contribute little in terms of the designation stage but has influenced the penalty stage. Further, Defendants with an Indigenous heritage now have a 50% chance of receiving an indeterminate sentence compared to 84% prior to the legislation change. Saskatchewan continues to have not only a disproportionate number of DOs but also DOs of Indigenous heritage. The results indicate that BC, AB, and MB have not changed their penalty patterns significantly since the 2008 legislation change, but Saskatchewan has. Discussion: Results generally supported previous research indicating that the judicial decision makers’ interpretation of expert risk assessments influence preventative detention hearings and that partisanship continues to exist even though legislation changes have attempted to reduce it. Results also indicated that the 2008 legislation change has had an impact on penalty outcomes but not designation outcomes. Moreover, although Indigenous peoples are disproportionately represented, under the 2008 legislation change, they are as likely to receive a determinate sentence with an LTSO as an indeterminate sentence. Implications of the results are discussed in terms of the validity and application of special sentencing designations in Canada.
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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 | 0.004 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".