Wounds: Commemorative Tattoos, Collective Trauma, and the Afghan-Canadian Identity
Bibliographic record
Abstract
The painting Wounds reimagines how nonwhite and “vulnerable” bodies are expected to exist in society. Inspired by The Tattoo Project and how commemorative tattoos meaningfully integrate love and loss into “good grief” (Davidson, 2016), the painting re-imagines commemorative tattoos as wounds that result from collective and intergenerational trauma. The painting Wounds uses a social justice lens to depict how traumatic histories can be embodied in the cultural identities of future generations of the Afghan diaspora and how tattoos materialize these memories. I demonstrate this by critically analyzing my lived experience of my cultural identity. This collective trauma is so strongly embedded into my ancestors’ collective identities as Afghans, that I also see the traumatic history to be part of who I am. This autobiographical artwork and accompanying critical analysis allow for the reclamation of my Afghan cultural identity by resisting Western pressures to conform. In being vulnerable about my past, I redefine vulnerability. I remember and honour the courage, sacrifice, and resilience of my Afghan ancestors who have endured violence and wars; which has contributed to the formation of my hyphenated, Afghan-Canadian identity. I recognize that the Afghan-Canadian identity is multidimensional, multi-faceted, and incredibly nuanced. My own experiences of my Afghan-Canadian identity deeply inform and enrich this critical analysis. In this critical analysis, I am by no means generalizing the experiences of Afghan-Canadians, as every individual’s experience is valid and distinct The three commemorative tattoos depict the Canadian maple leaf, my name “Mehdia” written in Persian, and the geographical shape of Afghanistan. The painting reimagines and redefines what it means to collectively heal, both literally and figuratively. It questions whether healing is still necessary because it implies that wounds disappear, and with them, the disappearance of deep social histories that construct my Afghan-Canadian identity. Using my original painting as an arts-integrated method of inquiry, I offer a multidisciplinary portrayal of how memory is materialized on the body. This written analysis and painting creatively and critically articulate the strength and beauty that comes with vulnerability when historical and cultural wounds are resurfaced. This work further provokes deeper discussion and dialogue about the need to make meaning of the collective trauma that is ingrained within one’s cultural identity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.046 | 0.026 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".