Having a real say: findings from first nations community panels on pandemic influenza vaccine distribution
Bibliographic record
Abstract
BACKGROUND: Recent deliberations by Australian public health researchers and practitioners produced an ethical framework of how decisions should be made to distribute pandemic influenza vaccine. The outcome of the deliberations was that the population should be considered in two categories, Level 1 and Level 2, with Level 1 groups being offered access to the pandemic influenza vaccine before other groups. However, the public health researchers and practitioners recognised the importance of making space for public opinion and sought to understand citizens values and preferences, especially First Nations peoples. METHODS: We conducted First Nations Community Panels in two Australian locations in 2019 to assess First Nations people's informed views through a deliberative process on pandemic influenza vaccination distribution strategies. Panels were asked to make decisions on priority levels, coverage and vaccine doses. RESULTS: Two panels were conducted with eighteen First Nations participants from a range of ages who were purposively recruited through local community networks. Panels heard presentations from public health experts, cross-examined expert presenters and deliberated on the issues. Both panels agreed that First Nations peoples be assigned Level 1 priority, be offered pandemic influenza vaccination before other groups, and be offered two doses of vaccine. Reasons for this decision included First Nations people's lives, culture and families are important; are at-risk of severe health outcomes; and experience barriers and challenges to accessing safe, quality and culturally appropriate healthcare. We found that communication strategies, utilising and upskilling the First Nations health workforce, and targeted vaccination strategies are important elements in pandemic preparedness and response with First Nations peoples. CONCLUSIONS: First Nations Community Panels supported prioritising First Nations peoples for pandemic influenza vaccination distribution and offering greater protection by using a two-dose full course to fewer people if there are initial supply limitations, instead of one dose to more people, during the initial phase of the vaccine roll out. The methodology and findings can help inform efforts in planning for future pandemic vaccination strategies for First Nations peoples in Australia.
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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 | 0.127 | 0.218 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.019 | 0.011 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".