Advancing the Concept of Resilience for Older People Who Are Experiencing Homelessness
Bibliographic record
Abstract
Abstract Current conceptualizations of resilience have overlooked the lived expertise of older people experiencing homelessness (OPEH) – individuals who have much insight to offer in terms of progressing notions on how people ‘stand up’ to adversity and ‘bounce back’ to a state of physical and psychological homeostasis across the life course. Drawing from extant literature and data from a community-engaged research project, which interviewed 40 participants and examined the health supports needed for individuals experiencing homelessness upon hospital discharge, we provide a comparison of resilience among homeless individuals generally and resilience among OPEH. Based on narratives of significant adversity experienced by OPEH in Vancouver, Canada, we offer a critical analysis of ‘resilience in ecological context’ that identifies unique characteristics of resilience at micro, meso, exo, and macro system levels. We discuss how our conceptual model of resilience pertinent to OPEH can be used to shape research, policy, and practice. 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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.032 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| 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".