An arts-based approach with youth born of genocidal rape in Rwanda: The river of life as an autobiographical mapping tool
Bibliographic record
Abstract
Given the tragedy of war and genocide, words often cannot adequately capture the complexity of war-related experiences. Researchers are increasingly utilizing the arts to enable multiple forms of expression, as well as for its therapeutic and empowering qualities. This paper outlines the use of the "river of life," an arts-based autobiographical mapping tool, conducted with 60 youth born of rape during the genocide against Tutsi in Rwanda who continue to live with this intergenerational legacy of sexual violence. The article begins with a review of current arts-based methods and their relevance for war-affected populations and an overview of the genocide, sexual violence, and the lived realities of children born of rape. We then outline the "river of life" mapping tool, where participants drew their life histories using the metaphor of a river, addressing the ebbs and flows of their lives and the obstacles and opportunities they encountered. Developed in collaboration with local researchers, participants were invited to share the meaning of their drawing with researchers, explaining key events throughout their life course, utilizing metaphors, and symbolism to convey their experiences. The article highlights how the "the river of life" facilitated key insights into the post-genocide experiences of children born of rape, and the long-term impacts at the family, community and societal levels, and proved to be especially helpful in enabling youth participants to process and communicate their histories of genocide and experiences of stigma and discrimination. The "river of life" was also reported by participants as having unintended positive effects, including closure and clarity in navigating their past and their futures. While not without limitations, we argue that this mapping tool represents an important addition to arts-based methods that can be used with populations who have experienced profound forms of violence and marginalization.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".