The International Criminal Court and African Conflicts: The Case of Uganda
Bibliographic record
Abstract
For more than two decades, the rebel Lord's Resistance Army (LRA) has been committing some of the most appalling human rights violations and war crimes against civilian populations in northern Uganda. The Ugandan Government has been unable to defeat the rebel movement and effectively protect the civilian populations from its carnage. This situation led the government to pass the Amnesty Act of 2000 in a bid to entice the group's leaders to end the fighting. Subsequently, the International Criminal Court (ICC), at the request of the Ugandan Government, issued arrest warrants in 2005 for the five main leaders of the movement, a move regarded by some as the main stumbling block to peace in Uganda, as the rebels are insisting on the annulment of these warrants before they can sign a definitive peace agreement. This article examines the dilemma that this situation seems to have created in the peace process in Uganda. It concludes that the ICC should be firm in combating impunity, but flexible in accepting other alternatives to attributive justice whenever necessitated by the situation, as its own statute acknowledges.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".