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Record W3080340307 · doi:10.21083/csieci.v13i1.4893

Krithi: Cows at the Beach

2020· article· en· W3080340307 on OpenAlexvenueno aff
Toby Wren, Suresh Vaidyanathan

Bibliographic record

VenueCritical Studies in Improvisation / Études critiques en improvisation · 2020
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsnot available
Fundersnot available
KeywordsImprovisationDialogicNegotiationMusicalProcess (computing)SociologyAestheticsPsychologyVisual artsArtComputer sciencePedagogySocial science

Abstract

fetched live from OpenAlex

Intercultural creative practice is a topic that has attracted a lot of recent scholarly attention. As improvising musicians from very different cultures and traditions, we decided to analyse a recent collaborative performance that we were involved in to unpack the ways that we were interacting through music. As performers, we were interested primarily in the ways that such an analysis would help us to work more effectively in intercultural situations, but we also wanted to understand the synergies and dissonances that exist between improvising cultures more broadly. For the essay we adopt the musical form of a krithi, a Carnatic compositional form that allows for joint statements and improvised exchanges. Through this dialogic process, we propose improvisation as a kind of negotiation that occurs between musicians, and between musicians and their culture, highlighting some of the specific challenges and rewards that we faced.

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.815
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.080
GPT teacher head0.361
Teacher spread0.280 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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