Cross-Sector Homeless Service Collaboration: Perspectives from Social Service Providers
Bibliographic record
Abstract
Coordinated and comprehensive services are needed for individuals experiencing homelessness or those at risk for homelessness. Various organizations working in collaboration and partnerships to address social issues face several barriers. This study aims to examine the efforts of a cross-sector collaboration of social service providers supporting individuals experiencing homelessness in the United States through the Collective Impact framework. Organizations specializing in behavioral health, medical, housing, and HIV/AIDS services encompass these providers. To measure how well the conditions of collective impact were being met, an online survey was delivered to the service providers from the organizations. Follow-up focus groups aimed to explain and enhance the survey results. ANCOVA evaluated the differences in meeting collective impact conditions across organizations. While no significant differences were found, the highest mean scores were for common agenda and continuous communication, indicating strong alignment and open dialogue across agencies. The lowest scores were for mutually reinforcing activities and backbone infrastructure. Thematic analysis of the focus groups supported these findings and revealed four key challenges: concerns with safety and security, role confusion, inconsistent communication, and organizational culture differences. These results suggest a need for clearer protocols, shared leadership structures, and strategies to align organizational roles and expectations. Findings highlight the importance of continuous relationship-building and structural coordination to strengthen collective impact in cross-sector collaborations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".