Review of Brian Kane,<i>Sound Unseen: Acousmatic Sound in Theory and Practice</i>(Oxford, 2014)
Bibliographic record
Abstract
Sometimes I fancy that the noise has stopped, for it makes long pauses . . . it is as if the fountains from which flows the silence of the burrow were unsealed . . . but the most perfunctory listening shows at once that I was shamefully deceived: away there in the distance the whistling still remains unshaken. (Kafka, [1] The subterranean mole-like animal in Franz Kafka's unfinished short story "The Burrow" is perpetually dogged by a high-pitched whistling noise. Instinctively engaged in a territorial mode of listening, the paranoid mole posits a series of hypotheses about the nature of the intrusive sound. The mole is unable to appreciate unseen sounds as an abstract, aestheticized experience; instead, it harbors intense curiosity about the source and cause of the auditory effects. For this reason, Brian Kane's new book Sound Unseen adopts the mole's perspective and projects the conditions in Kafka's burrow as an apt metaphor for building a theory of acousmatic sound.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".