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Record W2336117274 · doi:10.30535/mto.14.4.2

Charting the Score in a Multimedia Context

2008· article· en· W2336117274 on OpenAlexaff
Nicolas Donin, Jonathan Goldman

Bibliographic record

VenueMusic Theory Online · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsContext (archaeology)MusicologyActive listeningVisual artsEpistemologySociologyAestheticsArtComputer scienceHistoryCommunicationPhilosophyArchaeology

Abstract

fetched live from OpenAlex

Interested in what a contemporary practice of paradigmatic analysis might look like, the authors describe their research project aimed at studying past practices as well as conceiving of future possibilities in the form of a software tool. This article provides working, interactive samples of a prototype of this tool, which can be accessed by clicking on the applications contained in the article. By examining the “situatedness” of the analyst, the paradigmatic approach is seen not only as a precursor of the automatizing ambitions of late 20th-century music theory and musicology, but also as a structuralist reinvention of a tradition of listening that began with the analytical practices which emerged in Wagnerian Europe at the end of the 19th century.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0020.005
Scholarly communication0.0110.007
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.003

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 head0.239
Teacher spread0.159 · 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
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

Citations8
Published2008
Admission routes1
Has abstractyes

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