COVID-19 vaccine behaviour among citizens of the Métis Nation of Ontario: A qualitative study
Bibliographic record
Abstract
BACKGROUND: The burden of the current COVID-19 pandemic is not shared equally in Canadian society, with Indigenous Peoples being disproportionately affected. Moreover, there is a lack of research pertaining to vaccination behaviour in Métis communities. This Métis-specific and Métis-led qualitative study endeavours to understand COVID-19 vaccine behaviour among citizens of the Métis Nation of Ontario (MNO). METHODS: Data was collected via one-on-one interviews. Participants were recruited via the MNO's existing social media channels. Participants filled out a screening survey indicating their intention to vaccinate against COVID-19 as yes, no, or unsure. Sixteen participants (9 yes, 3 unsure, 4 no) were interviewed. Interviews averaged 30 min, and the questions and probes were developed in collaboration with the MNO. The interviewer received Métis-specific cultural safety training. Interviews were transcribed verbatim and uploaded to NVivo 12. RESULTS: A deductive analysis using the Social Ecological Model framework (SEM) for vaccine behaviour and two blinded coders was used to understand the data. An additional factor, COVID-19 public health measures, was added to the framework to better capture the experiences of participants during the COVID-19 pandemic. Overall, the factors with the greatest number of coded references included Vaccine roll-out and availability, Organization of the public into priority groups, Public discourse, Interpersonal influences, Interface with health professionals, Knowledge state, Trust, and Vaccine risk perception. Bandwagoning (following others' behaviour) and Freeloading (perceiving enough people have been vaccinated), both factors of the SEM, were not discussed. Yes, no, and unsure participant groups were compared to understand the influences of each factor based on COVID-19 vaccination intention. CONCLUSIONS: MNO citizens COVID-19 vaccine behaviour was negatively and positively influenced by a number of factors. This information will allow the MNO and public health units to better tailor their messaging for COVID-19 vaccine uptake campaigns and future pandemic emergencies.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".