Sound Acts, Part 1: Calling Back Performance Studies
Bibliographic record
Abstract
Let's jam.If performance studies has been a slow dance with "how to do things with words" (J.L. Austin), then we assert that it's way past time to "do things with sound."Austin's performative never imagined the way subjugated knowledges of the body, movement, affect, and sound have been used by minoritarian communities to incite social transformation.We celebrate the long heard resonances of sound in performance studies with a two-part field-defining publication, privileging how the materiality of sound acts as a form of aesthetic and political possibility.We come together through the "call back," an intersectional antiracist praxis guided by Black and Latinx feminist destabilizations of white supremacy and its colonialist, racist, sexist, ableist, and transphobic manifestations.In decentring whiteness, we recentre BIPOC and disabled futurity and radical joy. 1 We conceptualize the call back as a citational method of doing and making knowledge collaboratively, with care and attentiveness to receiving, registering, and reflecting radical thought across distance, difference, and time.Calling back is a long-term ethical commitment to interrupting oppression through revolutions in sound.Most of the essays in this collection are the product of more than three years of organizing sound and performance inquiries that riff on and with sound.We have engaged in continuous "call backs" with junior, emerging, and senior scholars at the American Society for Theatre Research (ASTR), American Studies Association (ASA), Modern Language Association (MLA), Association of Theatre in Higher Education (ATHE), and US Latina/o Literary Theory and Criticism Conference (LLTCC).These sonic exchanges culminated in a two-day symposium, Revolutions in Sound, at the University of Maryland (UMD) from February 28 to 29, 2020, co-organized by Caitlin Marshall and Iván Ramos.With an ASTR Collaborative Research Award and support from UMD and the University of Richmond, we came together to pump up (and keep up) the volume on the sustaining and incisive critiques levelled by women, LGBTQ+, Indigenous, Black, Latinx, and Asian American scholars represented in this first of two linked special issues.At the symposium, we called back to antiracist luminaries whose works have been formative to our own development: Alexandra T. Vazquez, author of Listening in Detail: Performances of Cuban Music (2013), and Christine Bacareza Balance, author of Tropical Renditions: Making Musical Scenes in Filipino America (2016).Vazquez and Balance staged a keynote duet that enacted symposium co-organizer Ramos's concept of "listening together," a shared sonic practice that activates care and sustains affinities across differences.In his keynote introduction, Ramos mobilized us to listen together, calling back Vazquez and Balance as mentors who created the conditions of possibility for his research in queer and Latinx studies.The keynote duet and Ramos's introduction modelled an
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.017 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".