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Record W2768622469 · doi:10.1177/0022002717739088

Justice Matters: Peace Negotiations, Stable Agreements, and Durable Peace

2017· article· en· W2768622469 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Conflict Resolution · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicPeacebuilding and International Security
Canadian institutionsInternational Institute for Sustainable Development
Fundersnot available
KeywordsNegotiationProcedural justiceEconomic JusticeDistributive justicePolitical scienceLawLaw and economicsSociologyCriminologyPsychology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.374
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it