From Guerrillas to Government: post-conflict stability in Liberia, Uganda and Rwanda
Bibliographic record
Abstract
Post-conflict stability remains an elusive goal for many African countries. The political and socioeconomic preconditions of African civil wars have often persisted after the end of open hostilities and have frustrated regional and international efforts at peace building. The growing role of non-state armed groups in post-conflict governments raises further questions on the important role of guerilla groups in either exacerbating or ameliorating the ‘structural’ preconditions of protracted African wars. The cases of Liberia, Uganda and Rwanda offer important insights on the complex interplay between armed groups and governments that underlie these conflicts. All three countries have been marked by devastating civil wars and the subsequent formation of post-conflict governments led by respective insurgent groups, but only Rwanda and Uganda have made any effort to mitigate the conditions that ultimately led to intra-state violence and state collapse. While the conflict dynamic may heavily condition an insurgent group, these factors alone do not play a determining role in the success or failure of peace building efforts.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".