Restorative Justice, Reconciliation, and Peacebuilding
Bibliographic record
Abstract
All over the world the practice of peacebuilding is beset with common dilemmas: peace versus justice, religious versus secular approaches, individual versus structural justice, reconciliation versus retribution, and the harmonization of the sheer multiplicity of practices involved in repairing past harms. Progress toward the resolution of these dilemmas requires far more than reforming institutions and practices; rather, it requires clear thinking about the more basic questions: What is justice? And how is it related to the building of peace? The twin concepts of reconciliation and restorative justice, both involving the holistic restoration of right relationship, contain not only a compelling logic of justice but also great promise for resolving peacebuilding’s tensions and for constructing and assessing its institutions and practices. This volume furthers this potential by developing not only the core content of these concepts but also their implications for accountability, forgiveness, reparations, traditional practices, human rights, and international law. While the volume’s central orientation is theory, it contains much of interest to a wide range of scholars as well as practitioners. It is both interdisciplinary and accessibly written. It situates its analysis in countries as diverse as South Africa, El Salvador, Canada, and East Timor and in the work of institutions and communities such as the United Nations, the Catholic Church, various indigenous communities, and the international law community. It contains chapters by leading scholars of restorative justice, international law, transitional justice, political philosophy, and theology.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.030 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".