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Record W2805203302 · doi:10.7577/rerm.2781

Braiding Designs for Decolonizing Research Methodologies: Theory, Practice, Ethics

2018· article· en· W2805203302 on OpenAlexaff
Heather E. McGregor, Brooke Madden, Marc Higgins, Julia Ostertag

Bibliographic record

VenueReconceptualizing Educational Research Methodology · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of AlbertaUniversity of Ottawa
Fundersnot available
KeywordsReciprocity (cultural anthropology)SociologyMetaphorIdentity (music)IndigenousEpistemologyPhotovoiceAestheticsSocial scienceVisual artsLinguisticsArtPhilosophy

Abstract

fetched live from OpenAlex

Describing methodological design in decolonizing research as the intersection of theory, practice, and ethics, we share four focused micro-stories from our respective research projects. The metaphor of braiding represents the methodological design process within each of our research stories, significantly influenced by Dwayne Donald’s (2012) Indigenous métissage. Heather grapples with notions of reciprocity, Brooke considers the role of place in the construction of teacher identity, Marc engages with reworking photovoice, and Julia brings relationships with plants into her methodological design. Intentionally interrupting each other and ourselves, we feature the moments and movements of research design that are iterative, recursive, messy, and sometimes stuck, in contrast to the linear, untainted and dogmatic methodologies that assert themselves around us. Meanings and relationships may be produced in braiding our micro-stories together, exceeding what might be possible if they were presented separately. Readers may be invited into imagining the design of decolonizing methodologies beyond those we enacted.

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)0.269
metaresearch head score (Gemma)0.259
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.989
Threshold uncertainty score0.902

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2690.259
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.004
Science and technology studies0.0110.103
Scholarly communication0.0200.021
Open science0.0040.020
Research integrity0.0060.012
Insufficient payload (model declined to judge)0.0050.002

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 head0.990
GPT teacher head0.833
Teacher spread0.157 · 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

Citations24
Published2018
Admission routes1
Has abstractyes

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