Bibliographic record
Abstract
Violence and human rights violations in putatively internal armed conflicts often involve significant cross-border dimensions. Yet the transitional justice mechanisms that respond to past atrocities have generally been undertaken in national or international institutions and focus primarily on offenses within a single state and primarily by national actors of that state. Despite the proliferation of transitional justice mechanisms, they have generally not been designed or utilized to address transboundary or regionalized abuses. The result has been significant inconsistencies in practice, with some crimes addressed and others ignored, creating zones of impunity. In this article, we explore the relative absence of regional transitional justice mechanisms, and consider how regional approaches have been used to promote conflict resolution and might be used to shape accountability processes as well. Drawing on the experiences of Central America and the Democratic Republic of Congo, we argue that the potential for regional approaches is as yet untested but merits closer consideration.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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".