Using design thinking to assess needs and develop faith-based and leisure programming for women of lived experience with homelessness
Bibliographic record
Abstract
Homelessness is a critical issue across Canada. Providing housing and other basic services to individuals of lived experience with homelessness is a priority for agencies interested in addressing this issue. However, once basic needs have been met, provision of leisure and faith-based programming could contribute to holistic improvements in health and well-being for this homeless population. The purpose of this research is to empathize with and identify the needs of women of lived experience with homelessness living in Nanaimo’s Samaritan House (inclusive of Martha’s Place). Guided by design thinking and participatory action approaches (i.e., user-centered, empathetic, co-created design), qualitative data was collected from residents of the Samaritan House and Martha’s Place during the summer of 2019. The findings of the research will be used by Island Crisis Care Society (the non-profit that owns and operates the Samaritan House) to improve resident wellbeing by co-addressing their leisure and faith-based needs through their own efforts and via community partnerships. Our findings indicate that supporting leisure and recreational participation as well as opportunities to engage in faith-based activities is both desired and seen as key to supporting overall health and wellbeing.
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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 | 0.034 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.006 |
| 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".