Practical Animal-Handling Classes at University College Dublin
Bibliographic record
Abstract
The first two years of the veterinary program at University College Dublin (UCD) include two modules whereby students gain experience in basic animal handling. Practical Animal Husbandry uses both lectures and animal handling classes aimed at teaching students to approach, restrain, and carry out routine husbandry procedures on food-producing and companion animals humanely and competently and to be aware of the risks to human health of inappropriate animal approach and handling. Staff and students are given lists of animal-handling competencies designed to ensure that students attain relevant handling skills for beef and dairy cattle, pigs, horses, sheep, cats, dogs, and exotics (e.g., rabbits, guinea pigs). Students are allotted up to 12 weeks of Farm and Companion Animal Experience, an extramural (EMS) activity, according to their prior experience; the objectives are to become proficient in the handling and management of animals and to develop an understanding of the key husbandry factors in food-production systems (milk, beef, lamb, pork) at the farm level. Students are assessed in practical examinations at the end of the second year and cannot progress until they have achieved the required competence. In addition to the pedagogic strategies, special consideration is given to the welfare of the animals used in teaching practicals and to the health and safety of teaching staff and students.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.210 | 0.037 |
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 source (direct Gemma or distilled Codex), 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".