Bibliographic record
Abstract
The utilization of moving pictures in live performances dates almost from the beginning of the filmic medium itself, but at the end of the twentieth century the rapidly evolving world of digital technology has provided a seemingly almost limitless range of possible interrelationships and interactions between the live body of traditional theatre and performance and the reproduced body of film and digital technology. Just as this work has radically altered (and continues to alter) the concept of the performing body itself, so it has radically altered (and continues to alter) the concept of the space in which that body operates. In the lead essay to the special issue of Theatre Journal devoted to "Theatre and Technology" Johannes Birringer looked to contemporary experimental work in dance, suggesting how the use of technology, especially digital technology, was opening new possibilities for the seeing and the experiencing of this form. "In the 1990s," he proposed, "working digitally and being digital evoke a new futurism of virtual performance possibilities; its new technological catchword is 'interactivity’". Diana Theodores has coined the term "technography" to refer to this major new development in dance, reinforcing the mutually informing new interrelationships of technology and choreography.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 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".