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Decolonizing Research Practice: Indigenous Methodologies, Aboriginal Methods, and Knowledge/Knowing

2020· book-chapter· en· W4248480771 on OpenAlexaffabout
Michael D. Evans, Adrian Miller, Peter Hutchinson, Carlene Dingwall

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan Campus
Fundersnot available
KeywordsIndigenousTraditional knowledgeSociologyWork (physics)Environmental ethicsEngineeringEcology

Abstract

fetched live from OpenAlex

Abstract Indigenous approaches to research are fundamentally rooted in the traditions and knowledge systems of indigenous peoples themselves, although indigenous methodologies and methods have become both systems for generating knowledge and ways of responding to the processes of colonization. Very specific indigenous methods emerge from language, culture, and worldview. This chapter describes two such indigenous research approaches drawn from the work of two indigenous scholars with their communities in Australia and Canada. Although creative and new, these approaches draw deeply from their communities and thus express and enact traditional knowledge systems in contemporary terms. This approach may result in more pertinent research, better take-up and dissemination of research results, and a general improvement in the situations of indigenous communities and peoples.

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)0.026
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.994
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0060.041
Scholarly communication0.0080.005
Open science0.0020.005
Research integrity0.0020.003
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 head0.162
GPT teacher head0.449
Teacher spread0.288 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations21
Published2020
Admission routes2
Has abstractyes

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