Justice centrée sur la faute ou justice centrée sur les victimes ? Le dilemme des commissions de vérité et de réconciliation
Bibliographic record
Abstract
Ce texte s’intéresse aux conditions de réussite des mécanismes de type commission de vérité et de réconciliation (CVR). Il présente deux grilles à partir desquelles il analyse et compare trois cas : la Truth and Reconciliation Commission d’Afrique du Sud, les tribunaux gacaca au Rwanda et la Commission de vérité et réconciliation du Canada sur les pensionnats indiens. La première grille évalue la capacité d’une CVR à promouvoir la justice et la responsabilité. La seconde, leur capacité à favoriser la réconciliation nationale. La thèse défendue est que les CVR relèvent davantage de l’éthique que du droit et du politique. La première grille applique des critères qui relèvent de ces deux derniers registres. Ce faisant, elle ne prend pas en compte la finalité de réconciliation des CVR et faillit à les évaluer correctement. La seconde grille, qui emprunte aux modalités de la justice réparatrice et à l’éthique, corrige ces lacunes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".