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Hepatitis C Diagnosis and Treatment Among Indigenous People in a Canadian Context: Challenges and Community-Led Solutions

2024· review· en· W4404495615 on OpenAlexaffabout
Kate P. R. Dunn, Mia J. Biondi, Samuel S. Lee

Bibliographic record

VenueMicroorganisms · 2024
Typereview
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of CalgaryYork UniversityUniversity Health Network
Fundersnot available
KeywordsIndigenousContext (archaeology)Public healthMedicineHealth careRacismPolitical scienceEconomic growthSociologyGeographyGender studiesNursing

Abstract

fetched live from OpenAlex

The historical and ongoing impacts of the influence of colonization are experienced by Indigenous people in systemic racism, inequity in healthcare access, and intergenerational trauma; originating in the disruption of a way of life and seen in a grief response, with links to disparate hepatitis C virus (HCV) prevalence. Despite this, the focus often remains on the increased incidence without a strengths-based lens. Although HCV is a global concern that can result in cirrhosis, liver failure, or cancer, diagnosing and linking people to care and treatment early can prevent advanced liver disease. Efforts to engage certain priority populations are occurring; however, historical context and current practices are often forgotten or overlooked. This is especially true with respect to Indigenous people in Canada. This review considers the published literature to elucidate the context of historical and ongoing colonizing impacts seen in the current HCV treatment gaps experienced by Indigenous people in Canada. In addition, we highlight strengths-based and Indigenous-led initiatives and programming that inspire hopefulness and steps toward community-engaged solutions to meet the World Health Organization Goals of eliminating HCV as a public health threat.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.966
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.092
GPT teacher head0.347
Teacher spread0.255 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2024
Admission routes2
Has abstractyes

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