Tail Docking and Ear Cropping Dogs: Public Awareness and Perceptions
Bibliographic record
Abstract
Tail docking and ear cropping are two surgical procedures commonly performed on many dog breeds. These procedures are classified as medically unnecessary surgeries whose purpose is primarily cosmetic. Available attitude research surrounding these controversial practices has been limited to surveys of veterinarians and dog breeders familiar with both practices. The aim of this project was to: 1) assess public awareness of tail docking and ear cropping, 2) determine whether physical alteration of a dog affects how the dog, and 3) owner are perceived. In Experiment 1 awareness was measured using a combination of both explicit and implicit measures. We found that 42% of participants (n = 810) were unable to correctly explain the reason why tail docked and ear cropped dogs had short ears and tails. Similarly, an implicit measure of awareness ('nature vs nurture task'), found that the majority of participants believed short tails and erect ears were a consequence of genetics rather than something the owner or breeder had done. The results obtained in Experiment 2 (n = 392) provide evidence that ear cropped and tail docked dogs are perceived differently than an identical dog in its 'natural' state. Modified dogs were perceived as being more aggressive, more dominant, less playful and less attractive than natural dogs. Experiment 3 (n = 410) is the first evidence that owners of modified dogs are perceived as being more aggressive, more narcissistic, less playful, less talkative and less warm compared to owners of natural dogs. Taken together, these results suggest that although a significant proportion of subjects appear unaware of the practices of tail docking and ear cropping in dogs, these procedures have significant impacts on how modified dogs and their owners are perceived by others.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".