Long-term care as contested acoustical space: Exploring resident relationships and identities <i>in</i> sound
Bibliographic record
Abstract
As the global population ages, residential care facilities are challenged to create positive living environments for people in later life. Health care acoustics are increasingly recognized as a key design factor in the experience of well-being for long-term care residents; however, acoustics are being conceptualized predominantly within the medical model. Just as the modern hospital battles disease with technology, sterility and efficiency, health care acoustics are receiving similar treatment. Materialist efforts towards acoustical separation evoke images of containment, quarantine and control, as if sound was something to be isolated. Sound becomes part of the contested space of long-term care that exists in tension between hospital and home. The move towards acoustical separation denies the social significance of sound in residents’ lives. Sound does not displace care; it emplaces care and the social relationships therein. Drawing upon ethnographic fieldwork in a Canadian long-term care facility, this article will use a phenomenological lens to explore how relationships are shaped in sound among residents living in long-term care. Ethnographic vignettes illustrate how the free flow of music through the care unit incited collective engagement among residents, reduced barriers to sharing social space and constructed new social identity. The article concludes that residents’ relationships are shaped within the acoustical milieu of the care unit and that to impose acoustical separation between residents’ living spaces may further isolate residents who are already at risk of loneliness.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.017 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".