Animals Used in Research and Education, 1966–2016: Evolving Attitudes, Policies, and Relationships
Bibliographic record
Abstract
Since the inception of the Association of American Veterinary Medical Colleges (AAVMC), the use of animals in research and education has been a central element of the programs of member institutions. As veterinary education and research programs have evolved over the past 50 years, so too have societal views and regulatory policies. AAVMC member institutions have continually responded to these events by exchanging best practices in training their students in the framework of comparative medicine and the needs of society. Animals provide students and faculty with the tools to learn the fundamental knowledge and skills of veterinary medicine and scientific discovery. The study of animal models has contributed extensively to medicine, veterinary medicine, and basic sciences as these disciplines seek to understand life processes. Changing societal views over the past 50 years have provided active examination and continued refinement of the use of animals in veterinary medical education and research. The future use of animals to educate and train veterinarians will likely continue to evolve as technological advances are applied to experimental design and educational systems. Natural animal models of both human and animal health will undoubtedly continue to serve a significant role in the education of veterinarians and in the development of new treatments of animal and human disease. As it looks to the future, the AAVMC as an organization will need to continue to support and promote best practices in the humane care and appropriate use of animals in both education and research.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".