MétaCan
Menu
Back to cohort
Record W3171190877

The Poetics of Engagement: Improvisation, Musical Communities, and the COVID-19 Pandemic

2021· article· en· W3171190877 on OpenAlexfundno aff
Daniel Fischlin, Laura Risk, Jesse Stewart

Bibliographic record

VenueÉrudit (Université de Montréal) · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsImprovisationGrassrootsContext (archaeology)MusicalSociologyAestheticsCommonsMedia studiesPublic relationsPolitical scienceVisual artsHistoryArtLawPolitics
DOInot available

Abstract

fetched live from OpenAlex

The COVID-19 pandemic turned the music industry upside-down overnight and impacted music-making at all levels. In these special issues, we invited musicians, performers, scholars, arts presenters, and other cultural workers to reflect on the extraordinary challenges posed by the pandemic and to begin envisaging a post-pandemic musical landscape. The struggles to maintain connection and the unquantifiable intimacies of exchange that characterize live music at its best are counterpoised against, but also enacted via, the new necrophonics––or sounds made within, and in spite of, moribund, dying spaces––the pandemic has exposed. Improvisation, in this context, becomes even more salient as a practice of adaptation and resistance to the newly emergent norms. This volume is a start at assembling diverse voices that move from first principles to direct action, and we emphasize the remarkable scope of pragmatic, grassroots solutions proposed by contributors across a significant range of voices and experiences. We argue for a fundamental first principle in which direct actions that support the allocation of resources to the creative commons be lateralized to avoid top-down forms that limit access to, and use of, precious public commons resources.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.066
GPT teacher head0.197
Teacher spread0.130 · 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 designNot applicable
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

Explore more

Same venueÉrudit (Université de Montréal)Same topicDiverse Musicological StudiesFrench-language works237,207