Research to Strengthen Policy, Practice, and Advocacy on Housing for Aging Societies
Bibliographic record
Abstract
Abstract Population aging alongside other global trends—such as urbanization, widening economic inequality, and climate change—accelerate the need for systematic efforts to improve housing for diverse individuals, families, and communities as they age. This symposium features gerontological research explicitly designed to advance policy, practice, and advocacy on aging and housing. The first presentation demonstrates the use of data from U.S. surveys to better characterize the nature of current and future challenges in access to affordable, accessible, and safe housing for older adults. The second paper presents findings from a mixed-methods action research project in Toronto involving tenants living in properties managed by the second largest senior housing provider in North America. The paper indicates how findings on facilitators and threats to aging in place directly inform policy implementation on integrated services in Toronto. The third paper presents findings from a longitudinal, in-depth interview study with leaders of age-friendly community initiatives in suburban New Jersey, demonstrating the simultaneous challenges and opportunities of embedding housing advocacy at the local level within broader age-friendly community change efforts. The fourth paper presents three case studies based on interviews with key stakeholders involved with anti-displacement housing preservation and public housing organizing in New York City, highlighting the often invisible work of older, lower income, African American women at the center of advocacy efforts to preserve affordable housing. Guided by interdisciplinary critical work on ethical responses to population aging, the discussant will integrate themes from the papers to propose a framework for research, policy, practice, and advocacy.
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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 | 0.118 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.035 |
| Scholarly communication | 0.022 | 0.023 |
| Open science | 0.005 | 0.023 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".