Pain, Postmemory, Porattam: Unpacking historical trauma and community healing through a decolonizing, arts-based participatory action research project with 2nd-generation Tamil refugee young adults.
Bibliographic record
Abstract
How do we inherit the pain of events we have not experienced ourselves? How can we heal and put an end to our generational trauma? For Tamil refugee communities in Canada, suicides have been on the rise among 2nd-generation young adults. Employing a Decolonizing Participatory Action Research (PAR) methodology, the study investigates historical trauma and community healing among second-generation Tamil refugee young adults in Toronto, utilizing innovative arts-based methods such as memory box autobiography, body-mapping, and avatar-based community circles.\nThis dissertation is composed of five integrated manuscripts, in addition to introductory, body-map findings, and conclusion chapters, which aim to interrogate and decolonize the study of trauma with conflict-fleeing refugee populations, as well as to imagine what could be otherwise (but is not yet) prioritized in their community healing futures. The first manuscript establishes decolonizing theoretical foundations for this work. The second manuscript critically examines anticolonial perspectives on historical trauma, using Tamil refugee communities as a case study. The third manuscript introduces methodology as a form of repatriation, weaving personal and political positionalities to create healing-focused research methodologies. The body-map chapter and last two manuscripts present findings on how second-generation Tamil refugee young adults make sense of historical trauma and community healing. The fourth manuscript visually represents co-constructed memory boxes and highlights key threads in intergenerational healing. The body-mapping chapter reveals meanings and embodied understandings of Tamil refugees’ experiences with pain, porattam, and healing. The final manuscript uses avatar-based community circles to make visible a praxis of community healing for refugee communities, contextualized within a dialectic: where communities are required to live in both spaces of recognition and resistance to interlocking systems of oppression, as well as pursue radical hope for liberation.\nThis research advocates for decolonizing and liberatory approaches to intergenerational trauma and community healing, where there is deep commitment toward accountability, justice, and solidarity with oppressed populations with historical and present legacies of trauma. This work stands to inform pedagogy, programming, and practice for health professionals, researchers, and refugee-serving organizations. Overall, this PAR project intervenes to prioritize community healing and joy beyond the restraints of pain and survival.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".