Deteriorating care home residents as ‘matter out of place’ in both care homes and hospitals: An ethnographic study
Bibliographic record
Abstract
Older people living in care homes are susceptible to deteriorations in their health. At times of deterioration, care home staff play a crucial role in considering the potential benefits and burdens associated with either caring for the resident in the home or transferring them to hospital. Using data collected through interviews with 30 care home staff and 113 h of ethnographic fieldwork in care homes in England, we consider the ways that care home staff can perceive deteriorating care home residents to be, often simultaneously, vulnerable (or ‘at risk’) and dangerous (or ‘a risk’) in both the hospital and the care home. Drawing on the work of Mary Douglas, we suggest deteriorating care home residents can be considered to be ‘matter out of place’ and can therefore be considered as ‘placeless’ in whichever setting they receive care. Instead of asking whether deteriorating residents are in the ‘right place’ to receive care, we might instead ask whether healthcare services are the ‘right shape’ to support to deteriorating care home residents and their complex needs. • Care home residents often experience deteriorations in their health. • Care staff play a crucial role in deciding whether to transfer residents to hospital. • Staff perceive residents as vulnerable and dangerous in hospitals and care homes. • Deteriorating residents are viewed as matter out of place in both settings.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 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".