Training the Veterinary Public Health Workforce: A Review of Educational Opportunities in US Veterinary Schools
Bibliographic record
Abstract
This article presents the results of an Internet-based review conducted in January and February 2003 to assess the educational opportunities available in veterinary public health, epidemiology, and preventive medicine at the 27 veterinary schools in the United States. Most professional veterinary curricula are designed to train students for careers as highly qualified private practitioners, although there is an increased need for veterinary perspectives and contributions in the public health sector. The future of veterinary public health relies on the opportunities available in education to teach and encourage students to pursue a career of public service. The results of this review indicate the availability of a wide variety of required courses, electives, and post-graduate training programs to veterinary students in the United States. Veterinary students are exposed to a median of 60 hours of public health, epidemiology, and preventive medicine in required stand-alone courses in these areas. Four veterinary schools also have required rotations for senior students in public health, preventive medicine, or population medicine. Contact time for required public health, epidemiology, and preventive medicine courses ranges from 30 to 150 contact hours. Advanced training was available in these subjects at 79% of the 27 schools. Greater collaboration between veterinary schools, schools of public health, and the professional public health community will increase exposure to and opportunities in public health to all future 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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".