‘Where to now?’ Understanding the landscape of health and social services for homeless women in London, Ontario, Canada
Bibliographic record
Abstract
Homelessness is an ongoing social challenge effecting women in unique ways. The purpose of this research study was to understand a network of health and social services accessed by women experiencing homelessness, and how individuals successfully or unsuccessfully navigated these services. Data were collected utilizing a participatory application of the PhotoVoice method, grounded in a critical feminist intersectional perspective. Six women with lived experience of homelessness were recruited from a drop-in centre to participate in the six-week project. Through photo-taking, group discussions, arts-based dialogue, and individual interviews, themes were developed around women’s navigation of services and experiences of homelessness. A constant comparative method of thematic analysis was utilized so that themes could evolve iteratively and collaboratively with both the research team reflecting independently on qualitative data, and the women reflecting collaboratively on the data. Themes generated included: On the Margins; Feeling at Home; Mighty Women; Safety; Creating Home; and Whenever, Wherever. It is recommended that: 1) Communities keep developing more safe and affordable housing; 2) Government investments in homelessness include a general gender lens; 3) Women have access to 24-hour safe spaces; 4) Participatory research methodologies add valuable knowledge for women experiencing homelessness; and 5) Service providers be trained in trauma and violenceinformed care.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.024 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".