AGING IN THE RIGHT PLACE: HOUSING AND SOCIAL SUPPORTS FOR OLDER ADULTS EXPERIENCING HOMELESSNESS
Bibliographic record
Abstract
Abstract The Aging in the Right Place (AIRP) framework recognizes that secure housing for older adults should support one’s unique vulnerabilities and lifestyles. Applying the AIRP framework to older people experiencing homelessness (OPEH) reveals limited access to the types of living environments and supportive services that promote dignity, health, and inclusion in later life. This symposium aims to use the AIRP framework to examine the places, meanings, and opportunities experienced by diverse groups of OPEH striving to secure housing and promote their well-being. The first paper uses photovoice interviews and thematic analysis to broaden the current conceptualization of AIRP by exploring how feelings, actions, and place inform the meaning of AIRP for older adult residents of one temporary housing program in Vancouver, CA. The second examines the housing and support needs of older adult veterans in Calgary, CA residing in temporary congregate housing through a multi-methods approach involving document reviews, environmental audits, and in-depth interviews. The third paper uses interviews with OPEH and service providers in Columbus, OH to look across the continuum of housing occupied by older adults before, during, and after an episode of late-life homelessness and to investigate the mechanisms that allow OPEH to identify and access the housing they consider optimal. Finally, the discussion positions AIRP for OPEH within the broad context of Age-Friendly ecosystems to highlight the role of coordination between housing providers, government leaders, health services, university researchers, and residents to ensure that AIRP is achievable for precariously housed older persons.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".