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Record W2609831456 · doi:10.18584/iipj.2017.8.2.5

Indigenous Research Methods: A Systematic Review

2017· review· en· W2609831456 on OpenAlexafffundvenueabout
Alexandra S. Drawson, Elaine Toombs, Christopher J. Mushquash

Bibliographic record

VenueInternational Indigenous Policy Journal · 2017
Typereview
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsLakehead University
FundersCanadian Institutes of Health ResearchSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsIndigenousStorytellingContext (archaeology)Participatory action researchCitizen journalismCommunity-based participatory researchPolitical scienceSociologyGeographyAnthropologyNarrativeLawEcology

Abstract

fetched live from OpenAlex

Indigenous communities and federal funding agencies in Canada have developed policy for ethical research with Indigenous Peoples. Indigenous scholars and communities have begun to expand the body of research regarding their peoples, and novel and innovative methods have begun to appear in the published literature. This review attempts to catalogue the wide array of Indigenous research methods in the peer-reviewed literature and describe commonalities among methods in order to guide researchers and communities in future method development. A total of 64 articles met inclusionary criteria and five themes emerged: General Indigenous Frameworks, Western Methods in an Indigenous Context, Community-Based Participatory Research, Storytelling, and Culture-Specific Methods.

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)0.066
metaresearch head score (Gemma)0.159
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.934
Threshold uncertainty score0.351

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.159
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0090.006
Bibliometrics0.0280.026
Science and technology studies0.0040.003
Scholarly communication0.0070.008
Open science0.0040.005
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.344
GPT teacher head0.638
Teacher spread0.293 · 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.

Study designSystematic review
DomainMethods
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

Citations298
Published2017
Admission routes4
Has abstractyes

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