“There's a little bit of mistrust”: Red River Métis experiences of the H1N1 and COVID‐19 pandemics
Bibliographic record
Abstract
We examined the perspectives of the Red River Métis citizens in Manitoba, Canada, during the H1N1 and COVID-19 pandemics and how they interpreted the communication of government/health authorities' risk management decisions. For Indigenous populations, pandemic response strategies play out within the context of ongoing colonial relationships with government institutions characterized by significant distrust. A crucial difference between the two pandemics was that the Métis in Manitoba were prioritized for early vaccine access during H1N1 but not for COVID-19. Data collection involved 17 focus groups with Métis citizens following the H1N1 outbreak and 17 focus groups during the COVID-19 pandemic. Métis prioritization during H1N1 was met with some apprehension and fear that Indigenous Peoples were vaccine-safety test subjects before population-wide distribution occurred. By contrast, as one of Canada's three recognized Indigenous nations, the non-prioritization of the Métis during COVID-19 was viewed as an egregious sign of disrespect and indifference. Our research demonstrates that both reactions were situated within claims that the government does not care about the Métis, referencing past and ongoing colonial motivations. Government and health institutions must anticipate this overarching colonial context when making and communicating risk management decisions with Indigenous Peoples. In this vein, government authorities must work toward a praxis of decolonization in these relationships, including, for example, working in partnership with Indigenous nations to engage in collaborative risk mitigation and communication that meets the unique needs of Indigenous populations and limits the potential for less benign-though understandable-interpretations.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".