Everyone Deserves a Sanctuary: Alienation as a Barrier to the Health and Healing of Older Women Who Experienced Homelessness
Bibliographic record
Abstract
Experiences of homelessness can result in social exclusion through stigmatization, discrimination, and displacement. Stress from lack of community integration for people who have been homeless can result in poorer health outcomes, including: higher rates of mental illness and chronic physical health conditions, substance dependence, loneliness, and suicide. This may be particularly true for older women who experience multiple intersections of marginalization. However, there is a lack of research that addresses how to facilitate a sense of belonging for and promote the health and healing of older women who have been homeless, and it is unclear what environmental conditions would help these women to transition out of homelessness and into a place of home that is stable, secure, and safe. This thesis stems from a larger community-based qualitative study that explores the experiences of older women who have been homeless and service providers in the homeless-serving sector, with the goal of building priority recommendations for system improvements. My research aims to address two research questions: 1) how have older women been marginalized and rendered invisible within homeless environments; and 2) how do homelessness experiences and environments shape older women’s behaviour? The theoretical frameworks of intersectionality and alienation guided this thesis, focusing on and developing insights into older women’s experiences of stigma and social exclusion and the impacts this marginalization has on their health. My findings derived from a secondary analysis of 11 out of 20 existing qualitative interviews with older women who have been homeless in Victoria, British Columbia, which revealed that older women were marginalized in homeless environments through a lack of safety and autonomy that contributed to high levels of alienation. Alienation prevented the development of a sense of home and belonging after homelessness that in turn impacted older women’s health and wellbeing. The recommendations from this analysis suggest that greater consideration to the concept of therapeutic landscapes for older women after homelessness would offer more opportunity for them to develop a sense of home and belonging. Overall, this project aims to fill a current gap in the literature on the social exclusion and subsequent health outcomes of older women who have experienced homelessness in Canada.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".