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Record W2766070078 · doi:10.3138/ctr.172.008

Rhythm and Rumination: A Three-Course Conversation

2017· article· en· W2766070078 on OpenAlexvenueno aff
Natalie Doonan

Bibliographic record

VenueCanadian Theatre Review · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsRuminationConversationRhythmVisual artsPsychologyArtCourse (navigation)PsychoanalysisCommunicationAestheticsEngineeringNeuroscience

Abstract

fetched live from OpenAlex

This article examines “specific productions” or products as these notions are called into question through artistic research. It reports on a pedagogical experiment that I conducted with a group of eighty students at Concordia University in the fall of 2016. Through writing, photography, and video, I document and reflect upon the relationships between pedagogy, research, and artistic production. These samples show that there are problems with attempting to distinguish between everyday acts and finished works. The process documented in the article calls into question the boundaries that we imagine between educating and artistic research. It does so by demonstrating the creative role of the educator in eliciting dialogue through the senses and in directing dialogue through attention to rhythm.

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)0.013
metaresearch head score (Gemma)0.038
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 score0.020
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.038
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0200.016
Scholarly communication0.0060.007
Open science0.0020.008
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0030.001

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 head0.037
GPT teacher head0.267
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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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