Are safer, welcoming care homes possible? Considering physical environments
Bibliographic record
Abstract
As the pandemic rolled through care homes, did overcrowding, close quarters, large facilities, and shared spaces create the conditions for high rates of resident infection and death? Taking up the perspectives of residents and workers, this chapter draws on a physical design analysis of photo diaries and interviews at eight care homes in Canada to describe how residents, staff, and families experienced care home environments since the onset of the pandemic, including during lockdowns, restrictions, and physical distancing measures. Then, drawing on over a decade of international research, we outline six principles for planning and organizing the future of care home physical environments. We argue that there is no single “best” way to organize care home physical environments for all those who need 24/7 medical and social care, but there are principles that can guide care homes to achieve safer, welcoming physical environments for current and prospective residents and staff, including in disease-outbreak conditions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".