Family matters in Canada: understanding and addressing family homelessness in Ontario
Bibliographic record
Abstract
BACKGROUND: Homelessness is becoming an international public health issue in most developed countries, including Canada. Homelessness is regarded as both political and socioeconomic problems warranting broad and consistent result-oriented approaches. METHODS: This paper represents the qualitative findings of a project that explored risk factors associated with family homelessness and strategies that could mitigate and prevent homelessness among families using a focused ethnographic study guided by the principles of participatory action research (PAR). The sample includes 36 family members residing at a family shelter who participated in focus groups over two years (between April 2016 and December 2017). Most of the participants were single-parent women. RESULTS: The analysis yielded five major themes including, life challenges, lack of understanding of the system, existing power differentials, escaping from hardship, and a theme of proposed solutions for reducing family homelessness in the community. CONCLUSION: The findings illustrated the complex nature of family homelessness in Ontario; that the interaction of multiple systems can put families at risk of homelessness. Findings from this study underscore the need for urgent housing protocols aimed at educating homeless families on how to navigate and understand the system, enhance their conflict resolution skills, and develop strategies beyond relocation to help them to cope with difficulties with 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 | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".