Voice in The “Long 20th Century”: From Mechanical to Electrical Aurality1
Bibliographic record
Abstract
The use of microphones in theatre today is so common that it is hard to believe how recent this practice is and, more importantly, that it has provoked such long standing and fierce resistance. The fact is that the theatre, which very quickly integrated the electric lamp (at the end of the 19th century) into its technical arsenal, waited more than a century before resorting to microphones to relay the voices of the actors. Technological imperfections alone are not sufficient to explain this deferment since, between the emergence of the first sound reproduction technologies in the late 1870s (microphone, phonograph, telephone) and the 21st century, four distinct media have enjoyed considerable success on account of these technologies : records, radio, cinema and television. This article argues is that such delay was due to an ideological positioning by which the theatre tried to affirm its ontological superiority over the other media practices by establishing itself as the ultimate refuge of “authenticity” by virtue of the simultaneous – and non-technologically mediated – presence of the actor and the spectator in a single space. In this context, the human voice of theatre took on a highly symbolic value, that of unadulterated authenticity, a value which seemed perverted everywhere else.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.031 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".