Drivers of Durable Peace: The Role of Justice in Negotiating Civil War Termination
Bibliographic record
Abstract
Attaining durable peace after a civil war has become a major challenge, as many negotiated settlements relapse into violence. How can civil war negotiations be conducted and peace agreements formulated so as to contribute to lasting, durable peace? Previous research has focused on the durability of peace agreements, measured as the absence of violence. This study develops an index to measure durable peace for a period of 8 years after the agreement had been reached, and evaluates the new measure using an existing data set. We ask whether impacts on durable peace are similar or different to those found for the durability of agreements. This question suggests a number of hypotheses that are evaluated with 16 cases of peace agreements. Stable agreements are shown to mediate the relationship between equality provisions in peace agreements and durable peace, and to also mediate the relationship between procedural justice and the reconciliation component of durable peace. Interestingly, economic stability is not a dividend of peace agreements.
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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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".