The COVID-19 Pandemic: Challenges and Needs Experienced by Indigenous People of Urban Areas
Bibliographic record
Abstract
The world was caught off guard by the swift spread of the COVID-19 pandemic at the beginning of 2020. For vulnerable populations such as the urban Indigenous, the first wave of the pandemic was even more challenging for multiple reasons. Many of their usual culturally safe services were interrupted, thus they found themselves struggling on different levels. Our team conducted a needs assessment to shed light on how urban Indigenous people living in the X region, in the province of Quebec, Canada, dealt with this situation and what were the most important services regarding holistic health they wished they could have relied on. To respect Indigenous culture, data collection was completed through sharing circles in addition to a web-based survey. The results indicated that participants experienced anxiety and psychological distress during the pandemic. They identified unmet needs related to family services, support in homeschooling, access to traditional medicine and spiritual and cultural practices to name a few. Future work should involve the implementation of culturally safe services, adapted to the pandemic era, for Indigenous people living in urban areas
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".