Co-Designing the “Peer to Community (P2C) Model”: An Intervention for Promoting Community Integration Following Homelessness
Bibliographic record
Abstract
Background: Community integration is an important outcome for homelessness prevention that has been challenging to effectively target using existing approaches. We conducted this study to design an intervention aimed at improving community integration following homelessness to fill this gap in existing research and practice. Method: We conducted a community-based participatory research (CBPR) study to identify what is needed to thrive following homelessness in one large and one mid-sized urban centre in Ontario, Canada. This CBPR study involved a collaboration among persons with lived experiences of homelessness, service providers, organizational leaders, and researchers. It comprised a stakeholder consultation followed by a co-design process that responded to our consultation findings. This paper presents a case study of a co-design process used to develop a novel intervention. Findings: Our stakeholder consultation emphasized a need for implementing approaches targeting community integration following homelessness. We responded by collaborating on the co-design of an intervention called the Peer to Community (P2C) Model. This intervention utilizes the expertise of peer support specialists, occupational therapists, and social workers to support meaningful activity participation and relationship building as pathways to community integration following homelessness. The (P2C) model is informed by five philosophies: 1) Housing First; 2) harm reduction; 3) trauma and violence-informed care; 4) person-centred care; and 5) the mental health recovery model. Our co-design process involved the development of the P2C model, educational modules for training individuals to deliver this approach, and a fidelity measure. Implications: The P2C model is a novel approach designed to support community integration following homelessness and needs to be piloted and evaluated in future research. A pilot study is currently underway in a mid-sized city in Ontario, Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".