Punishing Genocide: A Comparative Empirical Analysis of Sentencing Laws and Practices at the International Criminal Tribunal for Rwanda (ICTR), Rwandan Domestic Courts, and Gacaca Courts
Bibliographic record
Abstract
This article compares sentencing of those convicted of participation in the 1994 genocide in Rwanda. With over one million people facing trial, Rwanda constitutes the world’s most comprehensive case of criminal accountability after genocide and presents an important case study of punishing genocide. Criminal courts at three different levels— international, domestic, and local—sought justice in the aftermath of the violence. In order to compare punishment at each level, we analyze an unprecedented database of sentences given by the ICTR, the Rwandan domestic courts, and Rwanda’s Gacaca courts. The analysis demonstrates that sentencing varied across the three levels—ranging from limited time in prison to death sentences. We likewise find that sentencing at the domestic courts appears to have been comparatively more serious than sentencing at the ICTR and at the Gacaca courts, which calls into question consistency of sentences across levels of justice and should be explored in future research.
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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 | 0.007 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".