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Record W3159878512

Covid-19 pandemic: Implications for first nations communities in canada

2021· article· en· W3159878512 on OpenAlexaffvenueabout
Cole Anderson, Cale Leeson, Alexandra Valcourt, Diana Urajnik

Bibliographic record

VenueUniversity of Toronto Medical Journal · 2021
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsNOSM University
Fundersnot available
KeywordsPreparednessPandemicGovernment (linguistics)Public healthEconomic growthHealth carePolitical sciencePopulationEnvironmental healthCoronavirus disease 2019 (COVID-19)MedicineDiseaseNursingInfectious disease (medical specialty)Law
DOInot available

Abstract

fetched live from OpenAlex

A recent surge of Coronavirus disease 2019 (COVID-19) cases in First Nations communities during the second wave of the pandemic has raised concerns over the susceptibility of First Nations communities to COVID-19, as well as the preparedness of Canada’s healthcare system in supporting isolated First Nations communities during the pandemic. Despite government initiatives and funding throughout the pandemic, it is well established that First Nations communities continue to face longstanding health disparities when compared to the rest of the Canadian population. In this commentary, we argue for a multidimensional approach that encompasses the social determinants of health for understanding the susceptibility of First Nations to COVID-19 outbreaks, and potential solutions aimed at primary prevention and community preparedness that will benefit First Nations communities across Canada. Based on this approach, we recommend that healthcare providers and community members advocate at both provincial and federal levels for proper housing, access to clean water, implementation of culturally competent care into practice, adequate health teaching and understanding of public health recommendations (e.g. proper handwashing techniques) and robust monitoring of patients who may be at risk for COVID-19 infection. © 2021, University of Toronto. All rights reserved.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.670
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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.

Opus teacher head0.191
GPT teacher head0.432
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2021
Admission routes3
Has abstractyes

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