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Record W2141237315 · doi:10.1386/padm.8.1.31_1

Orpheus in New Media: Images of the voice in digital opera

2012· article· en· W2141237315 on OpenAlexaff
Jason R. D’Aoust

Bibliographic record

VenueInternational Journal of Performance Arts and Digital Media · 2012
Typearticle
Languageen
FieldPsychology
TopicSound Studies and Aurality
Canadian institutionsWestern University
Fundersnot available
KeywordsOperaDigital mediaArtVisual artsMultimediaComputer scienceComputer graphics (images)World Wide Web

Abstract

fetched live from OpenAlex

ABSTRACTAlthough musicological work on opera had been focused until recently on the analysis and criticism of music and voice to the detriment of its visual aspects, the meeting of opera with digital media calls for renewed attention to the voice. New media theories advocating meaningful embodiment in mediated experiences make use of implicit analogies rhetorically to attribute the characteristics of sound to our perception of visual objects. Theories of immersion in media also call for renewed vigilance in our understanding of digital media as part of a larger digital industry. This article discusses epistemological negotiations of the voice: how the voice was turned into an image for eidetic knowledge and how imparting the attributes of this signified voice can give the illusion of meaningful embodiment in fictional scenarios of immersion in media. By focusing on the figure of Orpheus, it also calls into question how literature — in. the widest sense of the term — already. participates in this mediation...

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.011
Scholarly communication0.0050.004
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.030
GPT teacher head0.299
Teacher spread0.270 · 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 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

Citations1
Published2012
Admission routes1
Has abstractyes

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