Engaging Immigrant and Racialized Communities in Community-Based Participatory Research During the COVID-19 Pandemic: Challenges and Opportunities
Bibliographic record
Abstract
Community-based participatory research (CBPR) approaches have been important avenues for addressing community vulnerability during pandemics and times of crises. There has been little guidance, however, on how to approach CBPR within the context of the COVID-19 pandemic where physical distancing and closure of essential community organizations became the norm. This study discusses challenges and possibilities of using CBPR during a pandemic to address the needs of immigrant and racialized older adults in Alberta, Canada. Two case studies of active research projects that aim to engage immigrant and racialized older adults are presented. Three key challenges are identified related to research activities during the pandemic: (a) pivoting as new foci emerge, (b) recognizing inequity in research participation, and (c) reflecting on well-being in the research team. Approaches to addressing these challenges are highlighted with recommendations for future considerations in CBPR research within vulnerable communities.
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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 | 0.077 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".