Practice report: an Alberta Métis model for COVID-19 vaccine delivery
Bibliographic record
Abstract
SETTING: In January 2021, the COVID-19 vaccine became available to First Nations, Métis, and Inuit (FNMI) over the age of 65 living in First Nations communities or Métis settlements in Alberta. In March, vaccine eligibility in Alberta expanded to include FNMI peoples of younger ages and in urban settings. The Métis Nation of Alberta (MNA) and other Indigenous organizations recognized that FNMI populations might be better served by tailored vaccine programs. INTERVENTION: The MNA is the government for the Métis people in Alberta. During the COVID-19 pandemic, the MNA has supported its citizens, through financial and mental wellness support, access to personal protective equipment, and messaging regarding public health orders. When vaccines became available, culturally appropriate virtual vaccine information sessions were provided. In March 2021, the MNA delivered the first Métis-led COVID-19 vaccination clinic. Unique to the clinic's success was the location, online booking process, and community presence. The clinic focused on cultural safety, including the availability of Indigenous health professionals to community members, and cultural reference points throughout the clinic. OUTCOMES: In the first MNA clinic, over 1300 people were vaccinated. Visitors shared appreciation for the culturally specific aspects of the clinic, which contributed to increased safety and comfort. IMPLICATIONS: Based on the success of the first Métis-led vaccination clinic, similar services in communities with high numbers of Métis people have been approved. This innovative practice initiative could provide a model of COVID-19 vaccine service delivery that could be used to meet the needs of Métis citizens in other jurisdictions in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".