The Umpires Strike Back: Canadian Judicial Experience with Risk-Assessment Instruments
Bibliographic record
Abstract
As Canadian correctional policy makers have begun to embed usage of risk-assessment instruments in various forms of penal and probation decision making, judges are frequently being asked to rule upon their admissibility and evidentiary relevance in a variety of contexts, most particularly sentencing. Judges have commented in a number of contexts to date: non-disclosure (by counsel or by correctional officials) of the fact that a risk-assessment instrument is being used; the use of “ministry override” policies for certain offences; the qualifications of the assessor; and the information used to formulate the assessment. At a broader level, judges have joined academic commentators in expressing concerns that over-reliance on risk assessment may trump proportionality.
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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 | 0.082 | 0.144 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.043 | 0.016 |
| Scholarly communication | 0.019 | 0.004 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 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".