The State of Veterinary Dental Education in North America, Canada, and the Caribbean: A Descriptive Study
Bibliographic record
Abstract
Dental disease is important in the population of pets seen by veterinarians. Knowledge and skills related to oral disease and dentistry are critical entry-level skills expected of graduating veterinarians. A descriptive survey on the state of veterinary dental education was sent to respondents from 35 veterinary schools in the United States, Canada, and the Caribbean. Using the online SurveyMonkey application, respondents answered up to 26 questions. Questions were primarily designed to determine the breadth and depth of veterinary dental education from didactic instruction in years 1-3 to the clinical year programs. There was an excellent response to the survey with 86% compliance. Learning opportunities for veterinary students in years 1-3 in both the lecture and laboratory environments were limited, as were the experiences in the clinical year 4, which were divided between community-type practices and veterinary dentistry and oral surgery services. The former provided more hands-on clinical experience, including tooth extraction, while the latter focused on dental charting and periodontal debridement. Data on degrees and certifications of faculty revealed only 12 programs with board-certified veterinary dentists. Of these, seven veterinary schools had residency programs in veterinary dentistry at the time of the survey. Data from this study demonstrate the lack of curricular time dedicated to dental content in the veterinary schools participating in the survey, thereby suggesting the need for veterinary schools to address the issue of veterinary dental education. By graduation, new veterinarians should have acquired the needed knowledge and skills to meet both societal demands and professional expectations.
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 | 0.003 |
| 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".