Bibliographic record
Abstract
Our performance piece, entitled Trashed, initially grew from three central questions 1) What is the role of testimony in recording history and/or current affairs? 2) What role can theatre play in communicating personal testimony? and 3) How does a person (or people) perform testimony? To explore these questions, we took on the following personal testimony: A young man in high school was giving blood and 45 minutes in, the administrators re‐read his form, realized he had checked the box saying he had had sex with a man (since 1977) and promptly took his bag of blood and dropped it in a garbage can. We were all struck by this story and particularly by the image of blood in a garbage can; however, as five heterosexual women we were unsure if and how we could communicate the testimony to an audience. Working from the idea that our responsibility to the issue is our “ability to respond,” our performance piece became a manifestation of these abilities. We chose to use movement‐based clown to enter and explore the material from a neutral space—clown negates specific characteristics such as gender or social orientation. Combining objective fact with clown allowed us to visually represent the issue, our confusion surrounding the issue and our physical disconnect with the issue as performers. Our hope is to achieve a performance that serves the original testimony emotional justice while allowing an audience to engage with the related issue on multiple levels.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.108 | 0.027 |
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".