Veterinary and Pharmacy Students’ Expectations Before and Experiences After Participating in an Interdisciplinary Access to Care Veterinary Clinic, WisCARES
Bibliographic record
Abstract
This pilot survey study describes student expectations and experiences at WisCARES, a low-cost veterinary medical teaching clinic where students from multiple disciplines collaborate. We hypothesized that prior to the workday, students would describe different expectations of working in an interdisciplinary access to care clinic than what they ultimately experienced. We surveyed 62 students from the School of Veterinary Medicine (46) and pharmacy (16) who spent a clinic day at WisCARES. Before introductory rounds, students completed a short survey consisting of four open-ended questions about their learning expectations; at the end of the day, they reviewed their initial responses and added what they actually learned. Qualitative information was categorized and analyzed using descriptive statistics. Thirteen major themes emerged: diversity, confidence, communication, case lead/case management, financial experience, helping people, teamwork, technical skills, inter-professional experience, mentoring, non-specific positive regard, appreciation for resources, and rounds. Students reported improved confidence in managing and leading cases with specific positive outcomes in communicating with clients, particularly regarding leading financial conversations. Developing greater insight into diversity was a common theme expressed in students' expectations but was less frequently noted as an end-of-day outcome. Veterinary students less frequently described the value of the inter-professional environment and collaboration, but this was a major theme noted among pharmacy students. Student feedback was positive overall. The current study is useful in identifying areas for improving collaborative instruction and access to care professional student learning opportunities.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".