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Record W2914275771 · doi:10.1177/1609406918821574

Decolonizing Research Paradigms in the Context of Settler Colonialism: An Unsettling, Mutual, and Collaborative Effort

2019· article· en· W2914275771 on OpenAlexafffundabout
Mirjam Held

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsDalhousie University
FundersSocial Sciences and Humanities Research Council of CanadaDalhousie University
KeywordsDecolonizationIndigenousTransformative learningColonialismSovereigntyContext (archaeology)SociologyEnvironmental ethicsEpistemologyPolitical scienceHistoryLawPedagogyEcologyPoliticsPhilosophyArchaeology

Abstract

fetched live from OpenAlex

All research is guided by a set of philosophical underpinnings. Indigenous methodologies are in line with an Indigenous paradigm, while critical and liberatory methodologies fit with the transformative paradigm. Yet Indigenous and transformative methodologies share an emancipatory and critical stance and thus are increasingly used in tandem by both Western and Indigenous scholars in an attempt to decolonize methodologies, research, and the academy as a whole. However, these multiparadigmatic spaces only superficially support decolonization which, in the Canadian context of settler colonialism, is a radical and unsettling prospect that is about land, resources, and sovereignty. Applying this definition of decolonization to the decolonization of research paradigms, this article suggests that such paradigms must be developed, from scratch, conjointly between Indigenous and Western researchers.

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)0.346
metaresearch head score (Gemma)0.213
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score0.807

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3460.213
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0050.005
Science and technology studies0.0240.138
Scholarly communication0.0280.036
Open science0.0060.045
Research integrity0.0060.018
Insufficient payload (model declined to judge)0.0020.000

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 head0.381
GPT teacher head0.636
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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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

Citations278
Published2019
Admission routes3
Has abstractyes

Explore more

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