Being a member of a novel transitional case management team for patients with unstable housing: an ethnographic study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Background Homeless and unstably housed individuals face barriers in accessing healthcare despite experiencing greater health needs than the general population. Case management programs are effectively used to provide care for this population. However, little is known about the experiences of providers, their needs, and the ways they can be supported in their roles. Connect 2 Care (C2C) is a mobile outreach team that provides transitional case management for vulnerable individuals in a major Canadian city. Using an ethnographic approach, we aimed to describe the experiences of C2C team members and explore their perceptions and challenges. Methods We conducted participant observations and semi-structured interviews with C2C team members. Data analysis consisted of inductive thematic analysis to identify themes that were iteratively discussed. Results From 36 h of field observations with eight team members and 15 semi-structured interviews with 12 team members, we identified five overarching themes: 1) Hiring the right people & onboarding: becoming part of C2C; 2) Working as a team member: from experience to expertise; 3) Proud but unsupported: adding value but undervalued; 4) Team-initiated coping: satisfaction in the face of emotional strain, and; 5) Likes and dislikes: committed to challenges. Conclusions A cohesive team of providers with suitable personal and professional characteristics is essential to care for this complex population. Emotional support and inclusion of frontline workers in operational decisions are important considerations for optimal care and program sustainability.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it