What to Ask Women Composers: Feminist Fieldwork in Electronic Dance Music
Bibliographic record
Abstract
This article reflects upon the research methods employed for microfemininewarfare (2013), an interactive database documentary that investigates female electronic dance music (EDM) artists.The purpose of the documentary is to feature the contributions of women as composers, to show how they came to be composers and to reveal the tactics used to approach significant issues of gender in the EDM community.I highlight the theoretical and methodological processes that went into the making of this documentary, subtitled "exploring women's space in electronic music".By constructing "electronic music by women" as a category, two objectives are addressed: first, the visibility of women's contribution to the musical tradition is heightened; and, second, it allows an exploration of the broadening of discourses about female subjectivity.This article showcases feminist research-creation and friendship-as-method as effective research methods to glean meaningful content when applied to EDM fieldwork.
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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 | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.027 | 0.029 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| 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".