Caring for patients with lived experience of homelessness.
Bibliographic record
Abstract
OBJECTIVE: To guide family physicians working in a range of primary care clinical settings on how to provide care and support for patients who are vulnerably housed or experiencing homelessness. SOURCES OF INFORMATION: The approach integrates recommendations from evidence-based clinical guidelines, the views of persons with lived experience of homelessness, the theoretical tenets of the Patient's Medical Home framework, and practical lessons learned from family physicians working in a variety of clinical practice settings. MAIN MESSAGE: Family physicians can use simple and effective approaches to identify patients who are homeless or vulnerably housed; take initial steps to initiate access to housing, income assistance, case management, and treatment for substance use; and work collaboratively using trauma-informed and anti-oppressive approaches to better assist individuals with health and social needs. Family physicians also have a powerful advocacy voice and can partner with local community organizations and people with lived experience of homelessness to advocate for policy changes to address social inequities. CONCLUSION: Family physicians can directly address the physical health, mental health, and social needs of patients who are homeless or vulnerably housed. Moreover, they can champion outreach and onboarding programs that assist individuals who have experienced homelessness in accessing patient medical homes and can advocate for broader action on the underlying structural causes of homelessness.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".