Justice Matters: Peace Negotiations, Stable Agreements, and Durable Peace
Bibliographic record
Abstract
Attaining durable peace (DP) after a civil war has proven to be a major challenge, as many negotiated agreements lapse into violence. How can negotiations to terminate civil wars be conducted and peace agreements formulated to contribute to lasting peace? This question is addressed in this study with a novel data set. Focusing on justice, we assess relationships between process (procedural justice [PJ]) and outcome (distributive justice [DJ]) justice on the one hand and stable agreements (SA) and DP on the other. Analyses of fifty peace agreements, which were reached from 1957 to 2008, showed a path from PJ to DJ to SA to DP: The justice variables were instrumental in enhancing both short- and long-term peace. These variables had a stronger impact on DP than a variety of contextual- and case-related factors. The empirical link between justice and peace has implications for the way that peace negotiations are structured.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".