Beauty and Art as Pathways to Healing After Sexual Violence: A Comparative Study in the DRC and Canada
Bibliographic record
Abstract
Conflict-related sexual violence against men in the Democratic Republic of the Congo (DRC) has profound psychological, emotional, relational, and spiritual consequences. Nevertheless, male survivors can achieve post-traumatic growth through processes that rebuild fractured identities, foster resilience, and cultivate renewed purpose. This article adopts a comparative framework by combining (a) original Canadian qualitative data—an Interpretative Phenomenological Analysis (IPA) study entitled “Silent No More: Surviving Male Rape,” conducted with survivors and trauma-informed practitioners—and (b) a phenomenologically informed synthesis of peer-reviewed studies, NGO/UN reports, and survivor testimonies from the DRC. The Canadian component focuses on the journey from victimhood to survivorship, demonstrating how breaking silence, being believed, and receiving compassionate, trauma-informed care foster meaning-making, resilience, and post-traumatic growth. The DRC component foregrounds culturally rooted pathways to recovery—especially communal and music-based practices—within conflict-affected settings. Across contexts, we identify convergent themes: beauty as a relational and embodied experience that regulates affect and restores safety; creative practices (music, visual arts, storytelling, ritual, and nature-based activity) as vehicles for dignity, connection, and purpose; and self-transcendent emotions (awe, gratitude, and wonder) that support the transition from threat to contemplation and agency. Divergences reflect cultural and structural conditions: in the DRC, healing often unfolds through community-embedded practices amid insecurity and stigma; whereas in Canada, clinical resources are more accessible, but masculine norms and isolation can impede disclosure. We argue that aesthetic and communal practices can complement clinical care and propose practice implications for arts-based, culturally grounded interventions, as well as a comparative research agenda.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.026 | 0.007 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".