Healing Psychosocial Trauma in the Midst of Truth Commissions: The Case of <i>Gacaca</i> in Post-Genocide Rwanda
Why this work is in the frame
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Bibliographic record
Abstract
Post-conflict governments and multilateral organizations have advocated truth commissions since the end of the Cold War. The mandate of truth commissions has been to combine the rule of law with psychosocial goals in the hope that they will break systemic cycles of violence and facilitate reconciliation. While these commissions emphasize the dimensions of truth telling, apology, forgiveness, and reconciliation, in practice, they are often challenged to fulfill the mandate of healing psychosocial traumas through these dimensions in countries that suffer not only from the traumatic experience of wars and genocide, but also from the multiple psychosocial issues that result from these forms of mass violence. The present article examines the psychosocial role of gacaca, a form of truth commission that was introduced in post-genocide Rwanda in 2002, and argues that relying on gacaca alone to heal psychosocial trauma in Rwanda underestimates the depth of suffering that genocide created both at the individual and collective levels in Rwandan communities. Writing as a Rwandan community-based mental health researcher and practitioner concerned with the mental well-being of individuals and communities that survive mass violence and genocide, I suggest that well-assessed models adapted to the issues at hand should be considered to promote the healing of psychosocial wounds and supplement the work of gacaca in the rebuilding of peace and reconciliation in the country and in similar contexts elsewhere. Mental well-being is central to the sustainable rebuilding and development of countries recovering from wars and genocide.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it