Veterinary Forensics, Animal Welfare and Animal Abuse: Perceptions and Knowledge of Brazilian and Colombian Veterinary Students
Bibliographic record
Abstract
Veterinarians have a fundamental role to play in the detection of animal abuse and domestic violence cases. Therefore, it is essential that veterinary colleges provide appropriate training in animal welfare and veterinary forensics. The aim of this article is to characterize the perception and knowledge of veterinary students about training in veterinary forensics, animal welfare and the association between animal abuse and human violence. An online survey was made available to veterinary students at 227 veterinary colleges in Brazil and 22 in Colombia. The Chi-square test of independence was performed to compare responses of Brazilian and Colombian students for categorical survey items. Most of the surveyed students indicated that their college offered animal welfare training. However, only 21.8% (47/216) of the Colombian and 43.1% (216/523) of the Brazilian students mentioned that their veterinary colleges offered veterinary forensics training. Deficits in training in identification of non-accidental traumas, reporting of animal abuse and awareness of the association between interpersonal violence and animal abuse were identified in both countries. Despite this, more than 90% of students were aware of the relationship between these two crimes and in the importance of receiving compulsory training in animal abuse and veterinary forensics. Likewise, most of the respondents recognized that animal abuse includes both physical and mental abuse. The results highlight the need to improve education in animal welfare, animal abuse, human violence and veterinary forensics in veterinary colleges in Brazil and Colombia.
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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 | 0.000 | 0.000 |
| 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".