Geographies of Trauma and Healing: Resistance, Resilience, ‘Ustawi wa’, and the Lived Experiences of African Women Refugees from the EHAGL Region in Canada
Bibliographic record
Abstract
This dissertation explores the lived experiences of African women refugees from the East and Horn of Africa and Great Lakes (EHAGL) region resettled in Ontario, Canada, with particular focus on the complex intersections of trauma, resilience, and healing within global refugee governance. It asks: How do the gendered and spatial dynamics of refugee protection and Canadian settlement systems sustain structural violence against African women refugees, and how do their transnational experiences challenge and reshape dominant frameworks of care, well-being, and institutional response? Through a multi-scalar analysis—macro (legal governance frameworks), meso (institutional actors), and micro (women’s narratives)—the study explores how trauma is shaped, silenced, and contested across the forced migration trajectory: pre-flight, during flight, and post-flight. Central to this research is the Trauma and Epistemic Justice of Displacement (trauma-EJD) framework, which integrates Black feminist and decolonial epistemologies with a rights-based approach to center African women refugees’ voices, knowledge systems, and lived realities. Situated within the broader landscape of forced migration and global refugee governance, this research foregrounds the invisibility and hyper-visibility of African women refugees, and the epistemic erasure of their experiences within dominant systems. Methodologically, the study weaves the trauma-EJD framework into a relational and reciprocal ethnographic approach. Ethnographic fieldwork that included 52 in-depth interviews (34 women refugees and 18 key informants and stakeholders [KIS]), combined with legal governance instruments analysis, reveals systemic erasures, gendered violence, racialized gatekeeping, and fragmented care within global refugee governance. In contrast, African women refugees’ testimonies illuminate practices of resistance, spiritual resilience, and collective healing, grounded in culturally rooted understandings of ‘ustawi wa’ and the continuity of ethics of care across borders and time. The findings articulate the spatio-temporal dynamics of trauma and displacement, offering a re-theorization of care and justice rooted in African women’s lived experiences within global refugee governance. The dissertation calls for structural transformation at global, regional, and national levels—toward trauma-responsive and justice-centered approaches that affirm African women refugees’ epistemic dignity. The trauma-EJD framework offers a roadmap for reimagining refugee governance rooted in dignity, relational care, and lived knowledge.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.038 | 0.031 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".