Adding Color to the White Paper: Time for a Robust Reciprocal Relationship between Procedural Justice and Therapeutic Jurisprudence
Bibliographic record
Abstract
This brief essay was prepared for a special issue of Court Review, the journal of the American Judges Association, dedicated to a recent White Paper on Procedural Fairness. The essay applauds the White Paper and the attention that courts must pay to procedural justice in their day-to-day operations. But the essay asserts that our incarceration crisis and the unfairness it breeds will not be overcome by procedural justice alone, and that judges must also become versed in the insights of therapeutic jurisprudence(TJ). The essay concludes by recommending that an excellent short Canadian TJ manual should be distributed to courts as a companion to the procedural justice White Paper.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.025 | 0.145 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.017 |
| Scholarly communication | 0.019 | 0.016 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.011 | 0.029 |
| Insufficient payload (model declined to judge) | 0.023 | 0.008 |
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".