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Record W2030120930 · doi:10.3138/jvme.35.2.177

The Dual DVM/MPH Degree at the University of Wisconsin—Madison: A Uniquely Interdisciplinary Collaboration

2008· article· en· W2030120930 on OpenAlexvenueno aff
Christopher W. Olsen, Patrick Remington

Bibliographic record

VenueJournal of Veterinary Medical Education · 2008
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationMedical educationPublic healthDegree programPharmacyMedicineHealth careFamily medicinePsychologyNursingPolitical science

Abstract

fetched live from OpenAlex

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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.369
GPT teacher head0.513
Teacher spread0.144 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2008
Admission routes1
Has abstractyes

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