Decolonization and Restorative Justice: A Proposed Theoretical Framework.
Bibliographic record
Abstract
The concept of decolonization has been used in numerous disciplines and settings, including education, psychology, governance, justice, transitional justice, restorative justice as well as research methods. Fanon (1963) saw decolonization as a process of both unlearning and undoing the harms of colonization. For Monchalin (2016), decolonization is both a goal and process to bring about a fundamental shift in colonial structures, ideologies and discourses. According to Alfred (2009, p. 185), decolonization requires “nation-to-nation partnership” for “justice and peace”. In the context of Restorative Justice (RJ), decolonization entail a) addressing historical harms of colonization; b) recognizing grievances of indigenous and marginalized communities about the justice system as genuine; and c) acknowledging that state- or INGO-funded RJ practices may do more harm than good. This paper begins with a brief overview of decolonization discourses from micro and macro perspectives to then locate decolonization in justice settings, arguing against “copying and pasting” Eurocentric models of RJ practices. Grounded in the findings of RJ visionaries and practitioners in Bangladesh and the work of Cunneen (2002), and Tauri and Morris (1997), this study proposes a decolonizing framework for RJ practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".