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Record W2938054049 · doi:10.1386/jivs.4.1.101_1

A singer’s perspective on Sirens and singing: An interview with coloratura soprano/conductor Barbara Hannigan

2019· article· en· W2938054049 on OpenAlexaboutno aff
Sophia Edlund, Barbara Hannigan

Bibliographic record

VenueJournal of Interdisciplinary Voice Studies · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicTheater, Performance, and Music History
Canadian institutionsnot available
Fundersnot available
KeywordsSingingSiren (mythology)ArtVisual artsVocal musicMeaning (existential)MythologyHistoryMusicLiteratureAestheticsPsychologyMusic educationAcoustics

Abstract

fetched live from OpenAlex

The Sirens appear in one of the most iconic literary episodes on music-making and music-hearing, in Homer’s twelfth book of The Odyssey (2018: 194), singing an irresistible and lethal song. While the myth of the Sirens’ song has continued to exist for almost three millennia in various formats, this Voicing queries the relevance of the myth as a reference for the practice of singing and examines the experiences of a classical singer who works within contemporary music and has embodied Sirens in performance. Following a short scholarly introduction that questions the role of the singing voice in the Siren song, practitioner-scholar Sophia Edlund interviews Canadian interpreter of contemporary music, soprano/conductor Barbara Hannigan, specifically asking her to consider the meaning of the Sirens and their symbolic value for singing. In this interview, Barbara Hannigan compares her music-making practice with the speculative practice of ‘Siren-ing’, pointing to similarities, such as being in a state of metamorphosis during singing, as well as divergences in terms of how singing is practised and understood.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.090
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.048
GPT teacher head0.311
Teacher spread0.263 · 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.

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

Citations0
Published2019
Admission routes1
Has abstractyes

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