The Dual DVM/MPH Degree at the University of Wisconsin—Madison: A Uniquely Interdisciplinary Collaboration
Bibliographic record
Abstract
The University of Wisconsin-Madison (UWM) launched a new Master of Public Health (MPH) degree program in 2005. This 42-credit MPH degree consists of 18 core and 14 elective course credits, two seminar credits, and eight field project/culminating experience credits. Unique strengths of the program include its strongly interdisciplinary philosophy, encompassing both health science (human medicine, veterinary medicine, pharmacy, nursing) and social science units on campus, and its emphasis on service learning through instructional and field project ties to the public-health community of the state and beyond. To date, the program has admitted 87 students, including full-time students as well as part-time students who continue to work in the health care and/or public-health sectors. The program is currently proceeding with the process for accreditation through the Council for Education in Public Health. In 2007, a formal dual DVM/MPH program was approved to allow students to integrate DVM and MPH training and complete both degrees in a total of five years. Nine MPH students over the first three years of admissions have been individuals affiliated with veterinary medicine (five DVM students and four post-graduate veterinarians).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.008 |
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".