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Record W7054747934

Beading as an Embodiment of Life: Understanding Indigenous Beadwork Through Felt Theory and an Indigenous Research Paradigm

2023· other· en· W7054747934 on OpenAlexaboutno aff

Bibliographic record

VenueUVic’s Research and Learning Repository (University of Victoria) · 2023
Typeother
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsAutoethnographyIndigenousStorytellingIdentity (music)CuriosityResistance (ecology)Cultural studies
DOInot available

Abstract

fetched live from OpenAlex

This project examines the significance of Métis beadwork as an embodiment of cultural identity and resurgence. My methodology includes autoethnography and storytelling to situate myself in my research and connect findings in the literature to my own experiences. I am beading a pair of moccasin vamps (also known as tops or tongues) as a part of my research, using Tiffany Dione Prete's (2019) theory of beadwork as a research paradigm. Jeff Corntassel's theory of acts of everyday resurgence, Dian Million's (2009) felt theory, and aspects of storywork by Jo-ann Archibald (2008). The findings of my research not only position Métis beadwork as a crucial factor in the resurgence of Métis culture and identity, but also as a way to understand knowledge transmission, resistance and resiliency, governance, and relationality. My initial interest in the topic, motivated by my own curiosity around Métis material culture as a young reconnecting Métis person, quickly developed into something much more significant. What I found were the threads that can help stitch back together symbolic Métis material culture and Métis epistemologies, ontologies, methodologies, and pedagogies, which have been fractured by colonization.

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)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0080.047
Scholarly communication0.0080.011
Open science0.0020.010
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 head0.055
GPT teacher head0.312
Teacher spread0.258 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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