Examining factors impacting acceptance of COVID-19 countermeasures among structurally marginalised Canadians
Bibliographic record
Abstract
The COVID-19 pandemic highlighted and exacerbated inequities in health for structurally marginalised Canadians. Their location on society's hierarchies constrained their ability to access healthcare and follow recommended health behaviours. The aim of this article is to identify, from the perspective of marginalised populations, factors influencing the acceptance or rejection of COVID-19 countermeasures by structurally marginalised Canadians. Interviews were conducted with Canadians 18 + who identified as Black (n = 8), First Nations, Métis, or Inuit (n = 7) and low-income (<40,000 annual household income) (n = 8) between August and December 2021. Measures were said to impact well-being and interfere with revenue generating activities. Longstanding unfavourable living and environmental conditions as they relate to structural marginalisation was said to fuel anger toward the government and lead to a greater reluctance to accept countermeasures. Participants described concerns about government decisions being made without considering their unique contexts, or knowledge of the experiences of the population for whom these decisions were being made. Effective proactive action from government is important to foster trust with marginalised populations to support acceptance of health information and address growing inequities. Action that demonstrates government competence and commitment to the interests of marginalised populations is critical.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".