The need for a social revolution in residential care
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Loneliness and depression are serious mental health concerns across the spectrum of residential care, from nursing homes to assisted and retirement living. Psychosocial care provided to residents to address these concerns is typically based on a long-standing tradition of 'light' social events, such as games, trips, and social gatherings, planned and implemented by staff. Although these activities provide enjoyment for some, loneliness and depression persist and the lack of resident input perpetuates the stereotype of residents as passive recipients of care. Residents continue to report lack of meaning in their lives, limited opportunities for contribution and frustration with paternalistic communication with staff. Those living with dementia face additional discrimination resulting in a range of unmet needs including lack of autonomy and belonging-both of which are linked with interpersonal violence. Research suggests, however, that programs fostering engagement and peer support provide opportunities for residents to be socially productive and to develop a valued social identity. The purpose of this paper is to offer a re-conceptualization of current practices. We argue that residents represent a largely untapped resource in our attempts to advance the quality of psychosocial care. We propose overturning practices that focus on entertainment and distraction by introducing a new approach that centers on resident contributions and peer support. We offer a model-Resident Engagement and Peer Support (REAP)-for designing interventions that advance residents' social identity, enhance reciprocal relationships and increase social productivity. This model has the potential to revolutionize current psychosocial practice by moving from resident care to resident engagement.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it