The health challenges of families experiencing homelessness
Bibliographic record
Abstract
Purpose The purpose of this paper is to report the findings of a scoping review on the health challenges of families experiencing homelessness. There is a bi-directional relationship between health and homelessness in that poor health can increase the risk of housing loss, and experiencing homelessness is bad for one’s health. The experience of homelessness differs between populations and this review focuses on families as one of the fastest growing segments of the homeless population. While research has been integrated on the causes of homelessness for families, this same integration has not been conducted looking at health challenges of families experiencing homelessness. Design/methodology/approach A scoping review methodology is utilized in the paper. As the goal of this work is to ultimately develop interventions for a Canadian context, primacy is given to Canadian sources, but other relevant literature is also included. Findings A clear distinction is seen in the literature between health challenges of children of homeless families and health challenges of parents. These themes are explored separately, and preliminary recommendations are made for potential points of intervention as personal, program and policy levels. Originality/value This review of current evidence is an important first step in building a foundation for interventions to improve health outcomes for those experiencing housing loss.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".