Bibliographic record
Abstract
I'm a dancer who engages improvisation every time I put on my shoes to brush, step, click, and knock the floor. Not surprisingly, my work until March 2020 was primarily with fellow sound-makers, usually folk musicians from Ireland, Scotland, what's now called Canada, and what's now called Appalachia. COVID-19 has forced me to listen to the extemporaneous music I make anew, in the absence of collaborators, within a soundscape of profound uncertainty. In this contribution, I offer a voice from the floor, enunciated by my lowest limbs contacting the surface upon which I stand. This is where my work as an LGBTQ2IA+ improvising step dancer finds its meaning. In this essay, I respond to the incisive queer horizon Thomas F. DeFrantz casts, as "imagining outside of what came before." I share ways I have been thinking about improvisation and offer thoughts on how we might learn from DeFrantz to imagine and improvise “outside of” critically, queerly, and generatively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.114 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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".