Enhancing Human–Animal Relationships through Veterinary Medical Instruction in Animal-Assisted Therapy and Animal-Assisted Activities
Bibliographic record
Abstract
Instruction in animal-assisted therapy (AAT) and animal-assisted activities (AAAs) teaches veterinary medical students to confidently and assertively maximize the benefits and minimize the risks of this union of animals and people. Instruction in AAT/AAA also addresses requirements by the American Veterinary Medical Association Council on Education that accredited schools/colleges of veterinary medicine include in their standard curriculum the topics of the human-animal bond, behavior, and the contributions of the veterinarian to the overall public and professional health care teams. Entry-level veterinarians should be prepared to: (1) assure that animals who provide AAT/AAA are healthy enough to visit nursing homes, hospitals, or other institutions; (2) promote behavior testing that selects animals who will feel safe, comfortable, and connected; (3) advise facilities regarding infection control and ways to provide a safe environment where the animals, their handlers, and the people being visited will not be injured or become ill; and (4) advocate for their patients and show compassion for their clients when animals are determined to be inappropriate participants in AAT/AAA programs. This article presents AAT/AAA terminology, ways in which veterinarians can advocate for AAT/AAA, the advantages of being involved in AAT/AAA, a model AAT/AAA practicum from Tuskegee University's School of Veterinary Medicine (TUSVM), and examples of co-curricular activities in AAT/AAA by TUSVM's student volunteers.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".