A Scoping Review of Social Housing Models for Older Adults
Bibliographic record
Abstract
Abstract Access to affordable housing is a rising concern for many older adults, and government-sponsored social housing programs are one approach to support low-income older adult renters; however, these housing models are limited in availability and may not all be well-suited to support aging in place. To better understand how to promote the physical, mental and social wellbeing of older tenants in social housing, this scoping review mapped relevant literature to examine: 1) the characteristics of older adults in social housing; and 2) social housing service models and policies. Seven peer reviewed databases were searched for relevant articles, which were screened by two independent reviewers. A total of 140 articles met the inclusion criteria. Studies were predominately from the US and Canada; spanning over five decades of research, with publications surging in the 1980’s and in the 2010’s. Almost all studies reported on the sociodemographic and health characteristics of older tenants, and two thirds presented findings on social housing service models, including policies, staff positions and training, and access to on-site support services. This review points to a high level of vulnerability among older adult tenants living in social housing and highlights the importance of co-locating support services in social housing buildings, with dedicated tenant-support staff to identify vulnerable tenants and link them to these services. There is an acute need for more research on key issues related to housing retention, such as eviction prevention, in order to identify opportunities for social housing landlords to help older tenants age in place.
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.
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 | 0.010 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".