Motivation and Prior Animal Experience of Newly Enrolled Veterinary Nursing Students at two Irish Third-Level Institutions
Bibliographic record
Abstract
Veterinary nurses report an intrinsic desire to work with animals. However, this motivation may be eroded by poor working conditions and low pay, resulting in the exit of experienced veterinary nurses from clinical practice. This study sought to quantify the level of animal-handling experience students possessed at the start of their training and to explore the factors motivating them to enter veterinary nurse training in two Irish third-level institutions. The authors had noted a tendency for veterinary nursing students to possess limited animal-handling skills, despite their obvious motivation to work with animals. The study explores possible reasons for this, as it mirrors previous reports in relation to students of veterinary medicine. First-year veterinary nursing students at Dundalk Institute of Technology and University College Dublin were surveyed and a focus group was held in each institution to explore student motivations for choosing this career and their prior animal-handling experience and workplace exposure. The results show that veterinary nursing students are highly intrinsically motivated to work with and care for animals. The majority had spent time in the veterinary workplace before starting their studies but they had limited animal-handling experience beyond that of family pets, primarily dogs. The study also revealed potential tensions between the veterinary nursing and veterinary medical students at University College Dublin: a hitherto unexposed aspect of the hidden curriculum in this institution. The results of this study highlight the need for ongoing investment in practical animal-handling training for veterinary nursing students.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".