Reflecting on Bodily Listening in Place: An Intercultural and Intersensory Research-Creation Project
Bibliographic record
Abstract
This article discusses a research-creation process by three interdisciplinary artists who worked across hearing and deaf experience to reorient aurality in musicking through a process of inter-sensorial exploration. For most musicians listening is unquestionably oriented to the sensory regime of aurality. Increasingly, however, this orientation is being challenged through haptic, kinetic, and visual musicking by deaf musicians, and this inspired hearing flutist and vocalist Ellen Waterman to reorient the role of audition in her improvisational practice. In dialogue with multisensory performance artists and critical theorists Paula Bath (hearing) and Tiphaine Girault (deaf), Waterman embarked on a research-creation project to create Bodily Listening in Place, an instructional score for intersensory improvisation. We discuss our iterative and multi-model practice-based research process, which involved the exchange of sonic, haptic, kinetic, linguistic, and graphic media in response to bodies in place. Photographs, sound, and video examples further explain our process. As is well documented in the anthropology of the senses (Howes), sensory perception is constructed and lived differently in different periods and societies, reflecting the diversity through which people perceive and understand their environments. We argue that, through an expanded conception of listening as attentiveness (Hahn; Oliveros), we can move beyond current normative notions of aurality to develop a broader, intersensory awareness and conception of musicking. Such expanded listening affords a means to further establish the links between people, their histories, experiences, senses of place, and environments.
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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 | 0.045 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.024 | 0.051 |
| Scholarly communication | 0.013 | 0.015 |
| Open science | 0.004 | 0.039 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".