Exploring Veterinary Students’ Perceptions of Teamwork and Learning from an Interprofessional Community-Based Experience
Bibliographic record
Abstract
The COVID-19 pandemic provided insight into the gaps provided by health care systems that could benefit from collaborative practice across the nexus of the animal and human health professions. The platform of interprofessional education, recognized as a pedagogical platform for delivering the principles of One Health, embodies the benefits of collaboration to address critical emerging public health issues, including the emergence of vector-borne zoonoses, antimicrobial resistance, food security and defense, and the impacts of climatic change. A phenomenological methodology, which is used to understand individuals lived experience, elicited veterinary students' perceptions of the benefits of interprofessional learning. Veterinary students indicated that the interprofessional learning experience facilitated their development of critical skills, including adaptability, communication, mutual support, and an awareness of the social determinants of health, which are critical for readying them for practice in a postpandemic world.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| 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".