A Museum Medicine Internship: Program Outline and Participants’ Reflections of Its Impact on Their Veterinary Careers
Bibliographic record
Abstract
The Window on Animal Health at the North Carolina Museum of Natural Sciences hosts the VetPAC Museum Medicine Internship, an undergraduate student internship program founded in collaboration with the Veterinary Professions Advising Center at North Carolina State University. It is designed to train pre-veterinary track students for wildlife and exotic animal husbandry and medicine in a unique museum clinical facility surrounded by large windows and a two-way audio system to facilitate public interaction during veterinary casework. The development of veterinary skills for interns is achieved via four competency-based stages: stage 1, veterinary assisting; stage 2, veterinary diagnostics; stage 3, medical case management and presentation; and stage 4, biosecurity and animal welfare. The goal of the internship is to provide students a hands-on opportunity to work alongside veterinarians on wildlife and exotic animal cases while simultaneously interacting with and educating museum visitors. A participant experience evaluation assessing the impact of this program on past participants' veterinary education and careers was performed via online survey upon completion of 10 years since its inception. The results show that participants reported a higher comfort level working with wildlife and exotic animals in all the proposed taxa categories after participating in the internship program. Of the 42 (98%) participants who indicated their career paths, 27 (64%) were accepted into a veterinary college following the internship program. Additionally, 42 (98%) participants stated they would strongly recommend this program to students interested in a veterinary sciences career. Through this article we present a practical model for a Museum Medicine Internship program and describe the value for establishing similar programs at peer institutions through the reflective feedback of past internship participants.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".