Toll of the COVID-19 Pandemic on the Primary Caregiver in Yazidi Refugee Families in Canada: A Feminist Refugee Epistemological Analysis
Bibliographic record
Abstract
Existing discourse on refugee resettlement in the West is rife with imperialist and neoliberal allusions. Materially, this discourse assumes refugees as passive recipients of resettlement programs in the host country denying them their subjectivities. Given the amplification of all social and economic inequities during the pandemic, our paper explores how Canada's response to the pandemic vis-a-vis refugees impacted the everyday of Yazidis in Calgary - a recently arrived refugee group who survived the most horrific genocidal atrocities of our times. Based on interviews with Yazidi families in Calgary and with resettlement staff we unpack Canada's paternalistic response to COVID-19 toward refugees. We show how resettlement provisions and social isolation along with pre-migration histories have furthered the conditions of social, economic, and affective inequities for the Yazidis. We also show how Yazidi women who were most impacted by the genocide and the subsequent pandemic find ways of asserting their personhood and engage in healing through a land-based resettlement initiative during the pandemic. Adopting a Feminist Refugee Epistemology and a southern moral imaginary as our discursive lenses, we highlight the need to dismantle the existing paternalistic structures and re(orient) resettlement practices and praxis to a social justice framework centering the voices of refugee women and families in their resettlement process.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.040 | 0.022 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".