Conceptualizing the Shelter and Housing Needs and Solutions of Older People Experiencing Homelessness
Bibliographic record
Abstract
Abstract Newly and chronically homeless older adults have unique pathways into homelessness and distinct physical, mental, and social needs. Using a five-step process, we conducted a scoping review of primary research to investigate the needs and solutions for sheltering/housing older people experiencing homelessness (OPEH). Thematic analysis of data from 19 sources revealed 1) shelter/housing needs and challenges of newly vs. chronically homeless older adults; 2) existing shelter/housing solutions addressing the needs of OPEH, including Housing First, permanent supportive housing, and multiservice homelessness intervention programs; and 3) outcomes of rehousing OPEH. Following, we developed a conceptual model which outlines how unique health and psychosocial needs of newly and chronically homeless older adults can be met through appropriately-designed shelter/housing solutions with individualized levels of senior-specific support. Future shelter/housing initiatives and strategies should use a rights-based approach and prioritize matching diverse OPEH needs to appropriate shelter/housing options that will support their ability to age-in-the-right-place. Part of a symposium sponsored by the Environmental Gerontology Interest Group.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".