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Record W4283454383 · doi:10.36510/learnland.v15i1.1079

Carto-Elicitation: Improvised Performances/Narratives of Identity, Memory, and Sites of Fascination

2022· article· en· W4283454383 on OpenAlexaffvenue
Terry Sefton, Kathryn Ricketts

Bibliographic record

VenueLEARNing Landscapes · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsUniversity of ReginaUniversity of Windsor
Fundersnot available
KeywordsNarrativeWeavingVisual artsDanceIdentity (music)Movement (music)Memory workImprovisationEvent (particle physics)StorytellingHistoryAestheticsSociologyArtLiteratureLinguisticsEngineering

Abstract

fetched live from OpenAlex

This paper describes the pedagogical roots of the work we do, both as teachers and as performers; and how our work reaches beyond the classroom and into community, eliciting narratives and weaving them through improvised dance and music collaborations, eventually onto the walls of an art museum. Our concept was to solicit stories that told of some event that happened in a particular place, and that left a memory that was tethered to that place. We collected stories, pooled our own stories, “pinned” stories to their geographic locations, and then transformed these stories through improvised movement and sound.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.247
Teacher spread0.230 · 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 teacher head, 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

Citations2
Published2022
Admission routes2
Has abstractyes

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