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Record W2582770922 · doi:10.16995/bst.17

Sonic technologies of Postmodernity and the grain of the voice in Robert Lepage’s <a href="http://lacaserne.net/index2.php/theatre/lipsynch/">Lipsynch</a><a href="#_edn1" name="_ednref1" title=""><sup>1</sup></a>

2016· article· en· W2582770922 on OpenAlexaboutno aff
Glenn D’Cruz

Bibliographic record

VenueBody Space & Technology · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)Identity (music)LinguisticsComputer scienceLiteraturePhilosophyArtAesthetics

Abstract

fetched live from OpenAlex

This paper unpacks the relationships between the human voice and sound technologies by re-reading and re-evaluating Roland Barthes seminal essay, ‘The Grain of the Voice’ an oft cited but frequently misunderstood text, in the light of Robert Lepage’s <em>Lipsynch</em> (Canada, 2012). This production explicitly uses analogue and digital sound technologies to reveal the complexities and contradictions operating within the sonic economy of the performance with particular reference to the way it uses digital dubbing, miming, voice-overs and lip-reading to unsettle assumptions about the connections between the language, speech and the human voice. The paper will also unsettle any simple understanding of the voice as the locus of identity, and uncover the manner in which sonic digital technologies enable us to better apprehend ‘the body in the voice as it sings, the hand as it writes, the limb as it performs’ (Barthes, 185) while remaining sceptical about the existence of a primordial, unconstructed body.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.008
Scholarly communication0.0000.000
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.212
Teacher spread0.201 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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