A narrative-based exploration of aging, precariousness and housing instability among low-income older adults in Canada
Bibliographic record
Abstract
In this article we focus upon low-income older adults’ lived experiences of aging, precariousness and housing instability/homelessness in Hamilton, Canada. Precariousness includes involuntary or incentivized displacement, as well as ‘health discounting’ in the face of rising shelter costs, inappropriate housing, periods of homelessness and involuntary housing immobility. The lived experiences of aging, precariousness and housing instability were collected through arts-based methodologies, whereby participants were given tablets to record their photos, videos and written diaries of their housing-related experiences. Additionally, participants took part in individual semi-structured interviews and participant observation in community-based settings. The recounting of participant experiences through a sensemaking frame allows for an exploration of the question of what it means to be ‘devalued’ as one ages to the extent that securing shelter is an overwhelming and stressful journey. Participant narratives provide compelling counter stories contesting popular notions that older adults will be taken care of as they age by the state or private savings. In sharing these stories, we are attempting to bring ‘recognizability’ to the experiences of aging, precariousness and housing/homelessness in order to contribute to the conditions through which low-income older adults’ experiences can be folded into policy co-design geared towards affordable housing.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.024 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| 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".