Understanding Place Histories to Inform Positive Ageing-in-Place Transitions: An Intersectional Place Perspective of Forced Relocation Experiences
Bibliographic record
Abstract
Background: Forced relocation is not always experienced as a single occurrence or event in time. Currently, there is a limited knowledge on how several substantial relocations across a lifetime impacts the health and wellbeing of older people. Aim: This study explores forced relocation experiences of older, low-income migrant Canadians through inquiries into their past place histories and examines how these have shaped opportunities and oppressions leading up to transitions into affordable housing in Richmond, BC, Canada. Methods: Informed by an intersectional place perspective model developed specifically for this research, a multi-method, qualitative community-based approach was undertaken involving in-depth interviews (N = 15), storytelling sessions (N = 10), and photo-tours (N = 8), with 28 participants. Narrative and visual data were co-analysed with participants, using a framework thematic analysis approach. Results: The analysis revealed oppressive structures that influenced the everyday lives of older people, which generated feelings of distress, fear, exclusion, feeling unsettled, and being ‘othered’. However, within oppressive structures of enforcement emerged experiences of empowerment engendered through gaining a sense of community, realising social belonging and family, maintaining pride and personal integrity as well as capturing community, social, psychological, physical and health transitions. Discussion: Unique insights acquired from an intersectional place analysis highlight how past experiences of place shape current perceptions of home and provide important implications for supporting and maintaining the health and wellbeing of older people during this type of relocation. The theoretical resource developed for this study, offers researchers, planners and developers an important tool for procuring a more critical perspective when creating homes for marginalised 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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.015 | 0.026 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".