The Cooperative University of Iowa / Iowa State University MPH Program
Bibliographic record
Abstract
Public health is an important component of veterinary medicine. In the last 10 years, there has been growing recognition of the need to increase the number of veterinarians trained in public health. The Center for Food Security and Public Health (CFSPH) at Iowa State University (ISU), College of Veterinary Medicine, received a grant from the Centers for Disease Control and Prevention (CDC) to support veterinarians working at CFSPH while pursuing the Master of Public Health degree. CFSPH and ISU administrators worked with the University of Iowa (UI) College of Public Health to establish three cooperative programs for veterinarians to earn the MPH degree. This article describes how these programs were developed and how they operate. (1) Between 2002 and 2005, CFSPH used funds provided by the CDC to support 15 veterinarians as they worked for CFSPH and toward the MPH degree. As the program grew, distance-education methods such as the Internet, Polycom videoconferencing, and the Iowa Communications Network (ICN) were incorporated. (2) A concurrent DVM/MPH degree is now offered; students can complete both degrees in four years. As of January 2008, three students have received their DVM and MPH degrees and 16 students are enrolled in the program. (3) In June 2007, the UI and ISU launched a distance MPH program for veterinarians working in private practice, industry, and government. Eight veterinarians are participating in the program, which includes two two-week, in-person summer sessions, with the remainder of the coursework taken at a distance via the Internet.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.205 | 0.050 |
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".