Teaching Slaughter: Mapping Changes in Emotions in Veterinary Students during Training in Humane Slaughter
Bibliographic record
Abstract
As part of their training, Dutch veterinary students learn how to carry out the humane slaughter of livestock, which many students consider emotionally challenging. The aims of this study were to plot changes in self-reported emotions in veterinary students at different time points during an educational program on humane slaughter using emotion cards and to assess the change in reported emotions after adding a video and a short period of self-reflection to the program. Emotions were mapped in five groups of students at the beginning, middle, and end of the program by asking them to select from 40 cards depicting emotions in photo and text. Then two changes were made to the course program: a video of an expert slaughterman stunning and bleeding a bovine was shown, and the students were requested to spend 2 minutes picturing themselves carrying out the same procedures. To evaluate the effect of these improvements to the course, the following five groups of students were asked in the same way to indicate their emotions at the same three time points. Adding the video and short period of self-reflection did not change the emotions reported by students. Our results indicate that instruction in humane slaughter techniques involves a significant mental challenge for students. The use of emotion cards by teachers could provide useful insights into emotional aspects of the more challenging programs for 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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".