Defining a relationship between transitional justice and <i>jus post bellum</i> : A call and an opportunity for post-conflict justice
Bibliographic record
Abstract
While there is an acknowledged overlap of transitional justice and jus post bellum, there has been no real attention to delineating a clear relationship between the two or addressing the significant differences regarding aims, scope and audience. These differences must be acknowledged and a clear relationship between the two fields needs to be demarcated for both intellectual clarity and practical reasons. It seems right to question not only where these fields of inquiry fall in relation to each other but how the two can co-exist and inform each other in a meaningful way that works to the benefit of victims of conflict and mass atrocity. Done correctly, this overlap can be ushered into a coherent research agenda where the two perspectives can be brought together in a careful and concise manner. This article aims to start to address this gap.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.059 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.002 | 0.021 |
| Research integrity | 0.004 | 0.010 |
| 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".