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Record W4405913780 · doi:10.1136/bmjph-2024-001341

Recognising the heterogeneity of Indigenous Peoples during the COVID-19 pandemic: a scoping review across Canada, Australia, New Zealand and the USA

2024· review· en· W4405913780 on OpenAlex
Joonsoo Sean Lyeo, Eric N. Liberda, Fatima Ahmed, Nadia Ali Muhammad Ali Charania, Robert J. Moriarity, Leonard J. S. Tsuji, Jerry P. White, Aleksandra M. Zuk, Nicholas D. Spence

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBMJ Public Health · 2024
Typereview
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsWestern UniversityQueen's UniversityToronto Metropolitan UniversityPublic Health OntarioUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsPandemicCoronavirus disease 2019 (COVID-19)IndigenousGeography2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)OutbreakVirologyBiologyMedicineEcology

Abstract

fetched live from OpenAlex

Objectives: The COVID-19 pandemic has had a disproportionate impact on the health of Indigenous Peoples in Canada, Australia, New Zealand and the USA, as reflected in the growing literature. However, Indigenous Peoples are often homogenised, with key differences often overlooked, failing to capture the complexity of issues and may lead to suboptimal public health policy-making. The objective of this review was to assess the extent to which the heterogeneity of the Indigenous Peoples in Canada, Australia, New Zealand and the USA has been reflected in COVID-19 research. Design: This study took the form of a scoping review. Data sources: Medline, Embase, CINAHL and Web of Science were searched for studies investigating COVID-19 pandemic outcomes among Indigenous Peoples in Canada, Australia, New Zealand and the USA. The search dates included January 2019 to January 2024. Eligibility criteria: All citations yielded by this search were subjected to title and abstract screening, full-text review and data extraction. We included original, peer-reviewed research investigating COVID-19-related outcomes among Indigenous Peoples in Canada, Australia, New Zealand or the USA. Data extraction and synthesis: Data extraction was conducted as an iterative process, reaching consensus between two of the study authors. All included studies were analysed through a combination of quantitative descriptive summary and qualitative thematic analysis. Results: Of the 9795 citations found by the initial search, 428 citations were deemed eligible for inclusion. Of these citations: 72.9% compared Indigenous participants to non-Indigenous participants; 10.0% aggregated Indigenous and non-white participants; and 17.1% provided findings for Indigenous participants exclusively. Conclusions: By overlooking the heterogeneity that exists among Indigenous Peoples in Canada, Australia, New Zealand and the USA, researchers and policy-makers run the risk of masking inequities and the unique needs of groups of Indigenous Peoples. This may lead to inefficient policy recommendations and unintentionally perpetuate health disparities during public health crises.

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.

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)0.020
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0130.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.239
GPT teacher head0.503
Teacher spread0.264 · 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