Beliefs Matter: Concrete theoretical discourse for clarity of restorative justice practice
Bibliographic record
Abstract
In Western neo-liberal contexts, discussions regarding beliefs are ignored, dismissed, or avoided as they are deemed irrelevant without empirical evidence. People are encouraged to treat beliefs as purely a private matter. Yet, denying that everyone holds beliefs does not mean that beliefs cease to exist. Conscious or unconscious, what individuals or societies believe fundamentally shapes how people engage with one another. In this article, I explain how beliefs matter in (a) defining restorative justice, (b) implementing restorative justice, and (c) sustaining restorative justice. I make the case for boldly declaring that the belief that all people and their environments are worthy and interconnected must reside at the core of restorative justice if it is to have the transformative effect advocates wish.
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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 | 0.017 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.010 | 0.085 |
| Scholarly communication | 0.015 | 0.021 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.009 | 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".