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Record W4283780324 · doi:10.1016/j.kint.2022.05.030

Indigenous Peoples’ perspectives of living with chronic kidney disease: systematic review of qualitative studies

2022· review· en· W4283780324 on OpenAlexaboutno aff
Marianne Kerr, Nicole Evangelidis, Penelope Abbott, Jonathan C. Craig, Michelle Dickson, Nicole Scholes‐Robertson, Victoria Sinka, Rahim T. Vastani, Katherine Widders, Jacqueline H. Stephens, Allison Jauré

Bibliographic record

VenueKidney International · 2022
Typereview
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsIndigenousKidney diseaseQualitative researchMedicineSociologyAnthropologyBiologyInternal medicineEcology

Abstract

fetched live from OpenAlex

Indigenous Peoples are defined as those who first lived in a region and have distinct cultural traditions, knowledge, and language that provide a basis for positive self-image and healthy identity.1 Indigenous Peoples have retained much of their cultural identity and displayed remarkable resilience in managing health using holistic approaches,2 despite being dispossessed of their lands through ongoing colonization that threatens their livelihoods and cultures.3 Indigenous Peoples are challenged by low health literacy, poor access to health care, lack of cultural safety in mainstream health services, and systemic racism and cultural misunderstanding.

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 imitation

Not 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.

metaresearch head score (Codex)0.042
metaresearch head score (Gemma)0.091
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.042
Threshold uncertainty score0.222

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.091
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0080.011
Science and technology studies0.0020.002
Scholarly communication0.0020.004
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.059
GPT teacher head0.430
Teacher spread0.371 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations22
Published2022
Admission routes1
Has abstractyes

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