Restorative Justice as a Window Into Relationships: Student Experiences of Social Control and Social Engagement in Scotland and Canada
Bibliographic record
Abstract
The practice and popularity of restorative justice (RJ) in education has been growing in recent years. There is, however, no universal understanding of RJ and its objectives. RJ can be understood in dramatically different ways by those implementing it: as an approach that challenges taken-for-granted structures and systems of discipline and control in schools; or as simply another tool that emphasizes compliance and punishment. Little research has been conducted that makes these differences explicit, and what the impact these different understandings of RJ might have on students. This multi-site case study examined how RJ was applied, how it was understood and what its intended objectives were in two schools, set in different contexts – Scotland and Canada. Although data was collected from teachers and principals to understand the context, my primary focus was on the students, those whom RJ was most intended to affect. Through questionnaires, observations, learning circles and engaging students as co-researchers, this study situates the student experience of RJ within particular school, regional and national contexts. The study finds that RJ in schools is a window into what is most fundamental to students: relationships. Viewing relationships through the window of RJ reveals both their centrality to students and their character of being of social control or social engagement. The study argues that RJ, by itself, does not guarantee certain qualities of relationship, but it does allow us to examine those qualities and ask questions of how school relationships are used to engage and/or control.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.052 | 0.020 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".