The role of a student-run clinic in providing primary care for Calgary’s homeless populations: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Despite the increasing popularity of Student-Run Clinics (SRCs) in Canada, there is little existing literature exploring their role within the Canadian healthcare system. Generalizing American literature to Canadian SRCs is inappropriate, given significant differences in healthcare delivery between the two countries. Medical students at the University of Calgary started a SRC serving Calgary's homeless population at the Calgary Drop-In and Rehabilitation Centre (CDIRC). This study explored stakeholders' desired role for a SRC within Calgary's primary healthcare system and potential barriers it may face. METHODS: Individual and group semi-structured interviews were undertaken with key stakeholders in the SRC project: clients (potential patients), CDIRC staff, staff from other stakeholder organizations, medical students, and faculty members. Convenience sampling was used in the recruitment of client participants. Interview transcripts were analyzed using a coding template which was derived from the literature. RESULTS: Participants identified factors related to the clinic and to medical students that suggest there is an important role for a SRC in Calgary. The clinic was cited as improving access to primary healthcare for individuals experiencing homelessness. It was suggested that students may be ideally suited to provide empathetic healthcare to this population. Barriers to success were identified, including continuity of care and the exclusion of some subsets of the homeless population due to location. CONCLUSIONS: SRCs possess several unique features that may make them a potentially important primary healthcare resource for the homeless. Participants identified numerous benefits of the SRC to providing primary care for homeless individuals, as well as several important limitations that need to be accounted for when designing and implementing such a program.
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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 | 0.009 | 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 | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".