Jumping on The Bandwagon: How Canadian Lawyers Can & Should Get Involved in the Emerging Trend to Implement Therapeutic Jurisprudence Practices in Canadian Courts
Bibliographic record
Abstract
how Canadian lawyers can adapt to these changes in order to better represent their clients.Part III of this comment will acknowledge the criticism surrounding these recent judicial approaches.It will also recognize the problems foreseen regarding lawyers specifically, but will point out how the lawyers' acceptance and embracing of this process is crucial for both their clients' success, as well as their own.Finally, Part IV will explore the need for adjustment in legal education, in order to train Canadian law students to practice therapeutic jurisprudence from the onset of their careers. PART I: Historical FoundationA. Restorative Justice Restorative Justice practices in Canada have diverse theoretical, political, cultural, and historical roots.10 Although this term refers to a specific model, Restorative Justice is primarily a philosophical or theoretical approach to criminal justice.11 In many aspects, Therapeutic Jurisprudence principles can be traced back to indigenous and tribal justice systems which often used this approach.Restorative Justice initiatives aim to hold offenders accountable in a meaningful way while addressing the needs of victims and the larger 10
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.019 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.018 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 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".