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Record W2763371275 · doi:10.1111/jade.12156

Transformation through Repetition: Walking, Listening and Drawing on Tlicho Lands

2017· article· en· W2763371275 on OpenAlexaboutno aff
Adolfo Ruiz

Bibliographic record

VenueInternational Journal of Art & Design Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeVisual artsActive listeningTransformative learningAnimationEmbodied cognitionSociologyAestheticsComputer scienceArtCommunicationLiterature

Abstract

fetched live from OpenAlex

Abstract As part of my PhD practice‐based research on Tlicho lands (a self‐governed Indigenous region in Canada's Northwest Territories), drawing is being used to embody intangible cultural heritage (which includes activities such as oral history and the social practice of walking). Recent work to emerge from this research consists of two drawings created by Tlicho elders, and an animated film made of 900 graphite drawings referencing regional oral history. The process of rendering these drawings embodied experiences on the land that are repetitive, albeit transformative, such as walking or listening to multiple versions of a single story. The entanglement of continually moving lines, evident through the animation, provides a counter‐narrative to colonial interpretations of the land – particularly narratives constructed through Cartesian coordinate systems (on which computer graphics and the geometry of built environments are based). This article will describe the production of this film, while also inquiring into how line‐making provides a trace of memory, rhythmic movement and epistemology.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.990
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.010
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.040
GPT teacher head0.383
Teacher spread0.344 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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Same venueInternational Journal of Art & Design EducationSame topicGeographies of human-animal interactionsFrench-language works237,207