Contesting COVID-19 vaccine hesitancy: realities and experiences among racialized immigrant and racialized non-immigrant individuals in Peel Region Canada
Bibliographic record
Abstract
This article examines perceptions surrounding trusted COVID-19 information sources, factors underpinning competing COVID-19 sentiments, and perceived choice in COVID-19 vaccines among racialized immigrant and racialized non-immigrant communities. While vaccine equity is critical to control COVID-19, racialized and immigrant groups are less likely to have confidence in or receive a COVID-19 vaccine. Research on vaccine gaps often center on homogenizing vaccine hesitancy discourses, reinforcing assumptions that hesitancy amounts to blanket vaccine refusal. Fewer studies examine the spectrum of vaccine sentiments and decision making informed by wider sociocultural, historical, and political place-based dynamics in Canada. Drawing on in-depth interviews (n = 79) with racialized immigrants and racialized non-immigrants in the Peel Region Ontario Canada, the results reveal a complicated narrative of vaccine inequity and factors underpinning vaccine choices. Findings indicate vaccine (dis)trust is shaped by various personal, socio-structural and historical factors converge to shape vaccine acceptance and opposition. Findings indicate vaccine mandates increase COVID-19 vaccine uptake, even among people who distrusted the vaccine, yet undermine choice and reinforce cynicism, distrust, and anger towards government. This study suggests that multipronged, equity informed policy approaches rooted in anti-racist and anti-oppressive frameworks are needed to address COVID-19 vaccine inequities.
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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 | 0.005 | 0.003 |
| 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 | 0.000 |
| 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".