Indigenous Strength: Braiding Culture, Ceremony and Community as a response to the COVID-19 Pandemic
Bibliographic record
Abstract
Purpose: The COVID-19 pandemic has impacted the physical, mental, emotional and spiritual health of urban Indigenous Peoples. We sought to examine innovations and changes in service delivery by Indigenous service providers in the community who are addressing community needs based on an Indigenous worldview. Basic Procedures: The research was a collaboration between an academic team, an Indigenous research associate, and an Indigenous oversight committee. Fifteen in-depth interviews were conducted with Indigenous service organizations, non-Indigenous organizations with Indigenous programming, Indigenous volunteer-based organizations and Indigenous volunteers. Participants were recruited based on having mandates that focussed on mental and emotional wellbeing, education, chronic health conditions, women and children and Indigenous cultural needs. Major Findings: Health inequities for urban Indigenous Peoples were compounded during the pandemic. The lack of local infrastructure contributed to increased volunteerism to deliver and improve access to services. Service interruptions and access barriers triggered innovative programming and a strengths-based response with activities embedded on the land, braided with language, ceremony and culture. Unmet community service needs and capacity development priorities were identified. Conclusions: Access to land, infrastructure and cultural programming is key to wholistic health for the urban Indigenous community. Despite continued inequities, the urban-based Indigenous response exemplifies the strengths-based approaches that helped to address pandemic impacts and demonstrated how Indigenous ways of knowing build strength and foster innovative program adaptations based on culture, ceremony and creating space for community.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| 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".