Spanish for Veterinarians Part 1: An Approach to Weaving Spanish Language Education into DVM Curricula
Bibliographic record
Abstract
The authors describe the need for discipline-specific Spanish language training in veterinary programs and elaborate on student interest in veterinary Spanish offerings. They outline their interdisciplinary approach to field-specific Spanish curriculum development that evolved from a single third-year practicum offering into a 7-credit Spanish language program while summarizing curriculum content, assessments, and student feedback. The challenges and approaches to weaving the language program into a demanding veterinary curriculum are addressed and program limitations are discussed. The paper ends with an outline of exciting future directions currently underway that hold achieving the necessary level of Spanish language proficiency for successful communication about animal health and well-being as a primary goal. The intent of this publication is to shed light on unique aspects associated with designing and delivering a Spanish language program within veterinary education, including the importance of interdisciplinary collaboration with language teaching professionals for curriculum development and delivery.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".