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Record W3136219140 · doi:10.21083/csieci.v14i1.6345

Notes From The Couch

2021· article· en· W3136219140 on OpenAlexvenueno aff
Laura Menard

Bibliographic record

VenueCritical Studies in Improvisation / Études critiques en improvisation · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChoirSingingThe artsMusicalVisual artsSociologySpace (punctuation)Power (physics)Media studiesAestheticsPedagogyHistoryArtAcousticsLinguistics

Abstract

fetched live from OpenAlex

As Michel Serres states, “The one who has power is the one who has the source and emission of sound” (1982). The sudden soundlessness of our COVID-19 existence is one of the largest pandemic challenges facing musicians. While some argue that there should be a hiatus on creation, others are embracing music’s adaptations to less traditional forums and formats. As a public high school teacher and conductor-educator with a youth-focused private organization, I am experiencing first-hand the improvisations, challenges, triumphs—and attendant burn-out—of rapidly adapting new spaces in which to keep my musical communities intact. Fellow conductor-educators near and far, working with populations at all ages and stages, are also bravely forging onward, rejecting sound-less and ensemble-less realities by adapting online. This all begs the questions: What does the near future hold for choral singing? And what will singing ensembles look like on the other side of current restrictions? Drawing together personal experience, informal interviews, explorations of the transformations of public and private space, sound and media studies, drift methodology, and the proliferation of recent articles in news and arts media, this essay investigates the novel spaces being created by and for choral arts educators amidst the uncertainties of what new reality awaits us on the other side of the screen-scape.

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)0.001
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), 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 score0.705
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.265
GPT teacher head0.370
Teacher spread0.104 · 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
Published2021
Admission routes1
Has abstractyes

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