Housing and Life Course Transitions in Later Life: The Role of Housing, Place, and Sense of Home in Periods of Uncertainty
Bibliographic record
Abstract
Abstract Housing is central factor for health and well-being in later life. Many countries have implemented ageing in place policies, but they tend to neglect the dynamic nature and heterogeneity of the ageing process. Housing needs change as people grow older, and experience different transitions across their life courses. Studies have demonstrated relationships between housing and health and wellbeing in later life on the one hand and life transitions and health and wellbeing in later life on the other hand. However, research on life transitions in combination with objective and perceived housing in relation to indicators of good ageing is scarce. Hence, the symposium aims to explore the dynamic relationship between housing and life transitions and how this relationship impacts health, well-being, functioning, and social/neighborhood participation along the process of ageing. First, Anna Wanka and Frank Oswald investigate how older adults’ relationship to their home is interlinked with life-course transitions and social exclusion, presenting case studies from three countries. Maya Kylén explores the meaning of home and health dynamics throughout the retirement transition among the ‘younger old’ in Sweden. Kieran Walsh asks how ‘sense of home’ interrelates with risks entailed in the transitions of bereavement, dementia on-set and forced migration. Finally, Helen Barrie discusses the transition to homelessness based on the HILDA survey to identify the profile(s) of older people at risk of homelessness in Australia. Finally, Richard A. Settersten will discuss the four contributions.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".