The COVID-19 Pandemic: An Immigrant Family Story on Reconnection, Resistance, and Resiliency
Bibliographic record
Abstract
The COVID-19 pandemic has created a significant effect on the vulnerable portion of society, particularly on Indigenous and visible minority immigrants. We, as a minority family from Bangladesh who are on Indigenous land in Saskatchewan Canada, explore family-based pandemic resiliency, mainly focusing on Indigenous notions of resistance and reconnection. This article discusses our family-based resiliency on family interaction, social distancing, and isolation during the COVID-19 pandemic. This paper explores a family-based decolonizing autoethnography as a methodology for understanding health and wellness from an immigrant family’s perspective. We discussed why Indigenous and immigrant stories matters for building resiliency and resistance within a family. How do we know it is effective? How can it be helpful for others? Here, we highlight how Indigenous Elders, Knowledge-Keepers, and ancestors’ stories helped us for building our resistance and reconnection to be active, hopeful, and joyful during the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".