The Poetics of Engagement: Improvisation, Musical Communities, and the COVID-19 Pandemic
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".