Sound medicine: studying the acoustic environment of the modern hospital, 1870–1970
Bibliographic record
Abstract
The twentieth-century hospital encountered two categories of sound that appeared troublesome. First was a kind of noise generated by city life, and second was a kind of soundscape generated by hospital life. In both cases, the acoustic environment was described and notated as an effect on patients, who, ill and immobile, were subject to sounds in a way that put their health and recovery at risk. In both cases, the solution to sound problems in the hospital was seen to be cultural and material, not medical. The difficulty was that physicians had no especial training to address the effect of sound on patients’ bodies. Sound and noise escaped the remit of medical expertise, and hospitals instead relied on a weak disciplinary injunction to silent comportment. This left sound as a matter for the medical environment rather than for medical intervention. In short, sound medicine was architectural.This paper looks at the twentieth-century modern hospital as an institution with particular acoustic environments, modified and shaped by architectural responses to the perceived problem of sound. I explore the emergence of noise on the inpatient ward as an architectural research topic, especially in the ground-breaking studies of the Nuffield Provincial Hospitals Trust (ca. 1955), and the identification of the emergency ward as the hospital’s signature acoustic environment. Using published studies of architectural acoustics, prescriptive advice from hospital specialist architects, and evidence from documentary films, I argue that the engagement with sound is an underemphasised yet key architectural characteristic of the modern hospital.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".