Bibliographic record
Abstract
Critical studies in improvisation seek to understand the potential of certain forms of music to decentre, even transform, entrenched social hierarchies and power structures. Such an ambitious project requires the development of new tools for analysis that, among other things, maintain the ability to critique the utopian tendencies that attend upon all intellectual projects of social reform. Towards that end, in this paper I develop an analytical framework based on a feminist erotics of creative improvisation that is committed to analysing the power dynamics within musical communication, and to recognizing and honouring difference. Eroticism is ontological: it is the realm of our most urgent desires that lead to the transgression of boundaries, ecstatic identification with others, and ultimately a confrontation with the self. I argue that creative improvisation similarly operates at the boundary between discipline and desire: the incessant confrontation with now that is characteristic of both eroticism and improvisation. After first addressing articulations of feminine jouissance in music scholarship that make this work possible, I bring dissonant theories of eroticism by Georges Bataille and Luce Irigaray into a productive tension in order to define a feminist erotics of improvisation. Finally, I employ this framework in analysing an instructive case study, the fascinating music and performance practice of violist Charlotte Hug.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.109 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".