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Record W4414007064 · doi:10.36939/cjis/vol1no1/art38

Rethreading Relations: The Kokum Scarf as a Call to Action for Building Good Relations

2025· article· en· W4414007064 on OpenAlexaffabout
Avery Shtykalo, Gabrielle Legault

Bibliographic record

VenueThe Canadian Journal of Indigenous Studies · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsOkanagan University CollegeOkanagan CollegeOkanagan Science CentreUniversity of Victoria
Fundersnot available
KeywordsAction (physics)Call to actionComputer scienceBusinessAdvertisingPhysics

Abstract

fetched live from OpenAlex

When Ukrainian settlers arrived in what is currently called Canada in the late 19th century, they brought with them cultural traditions, including a brightly coloured, floral-patterned scarf. As they settled on Indigenous lands, cross-cultural relationships developed through trade, reciprocity, and shared survival, leading to the gifting and exchange of these scarves with Indigenous communities. Over time, this item became known in Indigenous communities as the Kokum Scarf, taking on new meanings within Indigenous culture and identity. Most recently, in February 2022, the scarf emerged as a symbol of Indigenous solidarity with Ukrainians during the Russian invasion of Ukraine. Using Indigenous research methodologies based in relationality, this paper draws on interviews with three women, Ukrainian, Indigenous, and both, to explore the histories, meanings, and transformations of the Kokum Scarf. By centring lived experiences and oral histories, we contextualize the scarf’s role in past and present Indigenous-Ukrainian relations and examine its potential as a lens for decolonization, allyship, solidarity and reconciliation. Through these stories, we consider how the Kokum Scarf can inform new possibilities for rebuilding meaningful and reciprocal Indigenous-settler relationships.

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)0.005
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0350.033
Scholarly communication0.0090.007
Open science0.0020.011
Research integrity0.0030.006
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 head0.090
GPT teacher head0.439
Teacher spread0.349 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes2
Has abstractyes

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