COVID-19 Vaccine Hesitancy among Marginalized Populations in the U.S. and Canada: Protocol for a Scoping Review
Bibliographic record
Abstract
Introduction: Despite the development of safe and highly efficacious COVID-19 vaccines, extensive barriers to achieving optimal coverage threaten the effectiveness of vaccines in controlling the pandemic. Notably, marginalization produces structural and social inequalities that render certain populations disproportionately vulnerable to COVID-19 incidence, morbidity and mortality, and less likely to be vaccinated. The purpose of this scoping review is to provide a comprehensive overview of definitions/conceptualizations, elements, and determinants of COVID-19 vaccine hesitancy among marginalized populations in the U.S. and Canada. Materials and Methods: The proposed scoping review follows the framework outlined by Arksey and O’Malley, and further developed by the Joanna Briggs Institute. It will comply with reporting guidelines from the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The overall research question is: What are the definitions/conceptualizations and factors associated with vaccine hesitancy in the context of COVID-19 vaccines among adults from marginalized populations in the U.S. and Canada. Search strategies will be developed using controlled vocabulary and selected keywords, and customized for relevant databases, in collaboration with a research librarian. The results will be analyzed and synthesized quantitatively (i.e., frequencies) and qualitatively (i.e., thematic analysis) in relation to the research questions, guided by a revised WHO Vaccine Hesitancy Matrix. Discussion: This scoping review will contribute to honing and advancing the conceptualization of COVID-19 vaccine hesitancy and broader elements and determinants of underutilization of COVID-19 vaccination among marginalized populations, identify evidence gaps, and support recommendations for research and practice moving forward.
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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 | 0.115 | 0.110 |
| Meta-epidemiology (narrow) | 0.006 | 0.007 |
| Meta-epidemiology (broad) | 0.012 | 0.015 |
| Bibliometrics | 0.018 | 0.018 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.070 | 0.013 |
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".