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Timbral Thievery

2018· book-chapter· en· W4236176608 on OpenAlexaff
Jonathan De Souza

Bibliographic record

VenueOxford University Press eBooks · 2018
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsTimbrePolyphonyNatural (archaeology)ArtPhonographOrchestrationVisual artsAcousticsAestheticsLiteratureMusicalHistory

Abstract

fetched live from OpenAlex

Abstract Timbre often indexes an instrument’s materiality, and timbral variation often correlates with a player’s actions. Yet synthesizers complicate phenomenological links between sound and source. This chapter juxtaposes three instruments: an electromagnetic tuning-fork apparatus, developed by the nineteenth-century scientist Hermann von Helmholtz; the RCA Mark II, used by Milton Babbitt and other mid-twentieth-century composers; and the Yamaha GX-1, a large polyphonic synthesizer from the 1970s, played by Stevie Wonder and Keith Emerson. These synthesizers create new timbres and also imitate acoustic instruments, in a process that Robert Moog calls “timbral thievery.” Such imitations can provoke exaggerated or anxious discussions of synthetic and natural timbre. At the same time, performers may showcase the gap between timbre and instrument, exploiting a sense of uncanny or ambiguous sound sources for varied expressive ends. Ultimately, then, synthesizers help musicians both produce and conceptualize timbre.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.024
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0240.007

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 head0.186
Teacher spread0.145 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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