Factors That Attract Veterinarians to or Discourage Them from Research Careers: A Program Director's Perspective
Bibliographic record
Abstract
There is a nationwide shortage of veterinarian-scientists in the United States. Barriers to recruiting veterinary students into research careers need to be identified, and mechanisms devised to reduce these barriers. Barriers to attracting veterinary students into research careers include ignorance of available research careers and of the training opportunities. Once admitted, students in research training programs often feel isolated, fitting into neither the veterinary environment nor the research environment. To address the above issues, it is necessary to advertise and educate the public about opportunities for veterinarian-scientists. Schools need to develop high-quality training programs that are well structured but retain appropriate flexibility. Sufficient resources are needed to operate these programs so that students do not graduate with significant debt. A community of veterinarian-scientists needs to be developed so that students do not feel isolated but, rather, are part of a large community of like-minded individuals. Because of the complexities of programs that train veterinarian-scientists, it is necessary to provide extensive advising and for faculty to develop a proactive, servant-leadership attitude. Finally, students must be made aware of career options after graduation.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".