A Sonic Sampling, a Nuancing of Space: Theoretical Insights and Elaborations on the Acoustic and Spatial ‘Turns’
Bibliographic record
Abstract
This review critically engages with Susan Bennett’s Sound and Kim Solga’s Space—inaugural books in the authors’ co-edited series, Theory for Theatre Studies. It outlines key aspects of both books, evaluating their contribution to the fields of theatre and performance studies in terms of pedagogy and research. Sound and Space effectively foreground diverse theories specific to their topics. Working across disciplines and in relation to theatre and performance, both offer a number of case studies to elucidate theoretical approaches. As rigorous and foundational texts that illuminate discourses and practices around the ‘auditory turn’ and the ‘spatial turn,’ Sound and Space prompt readers to extend their thinking across theories, genres, disciplines, and time periods. Written accessibly for a wide readership—students, practitioners, researchers, teachers—these books inspire innovative thinking about sound and space in the theatre and in everyday life. Readers are directed to additional resources, including digital materials, encouraging further exploration and engagement with these topics.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".