Re-mapping the body: feminine experience in music performance
Bibliographic record
Abstract
In this project report I analyse how the practice of Body Mapping impacts the bodily performances of women classical musicians. The purpose is to study how the characteristics that define normative gender affect the body and its movement; to interrogate the body as the site where a patriarchal society constructs gender roles (more specifically, femininity); and consequently to assess the effects that these may produce in music performance. Drawing on interviews with six women classical musicians, autoethnography, and Body Mapping as a method, I created a workbook for women Body Mapping students. The goal of my research is to look into the possibilities of how the three fields—music performance, Body Mapping and feminist thought—can connect together, thus laying the groundwork for possible future research in this area. Even more, I seek to apply new approaches to music performance and to contribute, at a practical level, to the development of women classical musicians.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.018 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".