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LES NÉGOCIATIONS POUR LA PAIX EN RD CONGO

2025· article· W4415431333 on OpenAlex
Vital KAMERHE

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

VenueCongo-Afrique · 2025
Typearticle
Language
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsBibliothèque et Archives nationales du Québec
Fundersnot available
KeywordsPopulationContext (archaeology)First world war

Abstract

fetched live from OpenAlex

a Rpublique dmocratique du Congo a connu beaucoup de guerres et de conflits arms et plusieurs tentatives furent inities pour recouvrer la paix ou la consolider.Avec ma petite exprience dans les ngociations de paix en ma double qualit d'ancien Commissaire Gnral du Gouvernement Adjoint charg des relations avec la MONUC et d'ancien Commissaire Gnral du Gouvernement charg du suivi du processus de paix dans la rgion des Grands Lacs, je vais essayer de me focaliser uniquement sur les faits tels que je les ai vcus en tant que tmoin, et tels que la population congolaise les a perus au regard de ses attentes.C'est ainsi que mon adresse va s'articuler autour de 2 points, savoir :1. L'aperu historique ; 2. Les ngociations de paix proprement dites. I. Aperu historique01.A la suite du gnocide rwandais de 1994, de triste mmoire, prs de deux millions de rfugis rwandais, majorit des hutus, vont se dverser dans les provinces du Nord-Kivu et du Sud-Kivu, l'Est du pays.02.Ces rfugis, parmi lesquels les ex Forces Armes Rwandaises (FAR), l'arme de l'ancien prsident Habyarimana, taient venus sous l'encadrement des militaires franais travers l'opration Turquoise entrine par le Conseil de Scurit des Nations Unies.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.871
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.312
Teacher spread0.301 · 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