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Record W3111136092 · doi:10.7202/1073927ar

The Complete Artistic Self: Five Collaborators Talk about Barbara Hannigan

2020· article· en· W3111136092 on OpenAlexvenueno aff
Emanuelle Majeau-Bettez

Bibliographic record

VenueCircuit Musiques contemporaines · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicMusicology and Musical Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeorge (robot)Performing artsFormative assessmentVisual artsCharacter (mathematics)Performance artPersonalityArtAestheticsPsychologyArt historyPsychoanalysisPedagogy

Abstract

fetched live from OpenAlex

Who is Barbara Hannigan, as a singer, performer, conductor, mentor, and community-involved musician? What is the impact of her personality on the music scene? How has her artistic character evolved throughout her formative and professional years? With these questions in mind, I interviewed five of Hannigan’s closest, and most important collaborators and mentors: Hans Abrahamsen, George Benjamin, Gary Kulesha, Mary Morrison and Thomas Morris. Individually, the interviews shed light on specific phases and events in Hannigan’s career, from her undergraduate studies to the present. Taken as a whole, they open the door to understanding Barbara Hannigan as a complete—and completely fearless—artist.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0260.014
Scholarly communication0.0080.004
Open science0.0010.006
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.001

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 head0.049
GPT teacher head0.226
Teacher spread0.176 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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