Barriers and Facilitators Associated with the History of Colonization on the Vaccination Process of COVID-19 among Indigenous Peoples in Canada
Bibliographic record
Abstract
Indigenous communities were identified as highly vulnerable during the COVID-19 pandemic, given their remote geographical location and high relative cumulative cases. Specific barriers and facilitators of vaccination in the communities must be studied to create better public health planning. This study conducted private, qualitative interviews in the Indigenous community with local adult residents. Convenience sampling was used and recruitment was conducted with support from trusted Indigenous community connections. Participants were included if they spoke English and spent the majority of their lifetime in the local community. We interviewed three participants (two women, and one man, ages of 54, 53, and 61 years old respectively), all of whom received two mandatory COVID-19 vaccines with two of them getting one booster shot. Interview questions asked for attitudes on the current vaccination process, the government and local health unit policies, the source of trust and mistrust, and future suggestions for vaccination policies. Participants identified cultural mistrust as a barrier as it refers to the hesitancy of residents due to historical and cultural contributors. Participants suggested mixed attitudes toward accessibility, source of information and local health unit policies, and vaccine mistrust and trust, identifying them as barriers and facilitators in different scenarios. This study brings vaccination-related issues to the attention of the Government of Canada and health officials, facilitating effective public health planning and long-term trust building with the Indigenous communities.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".