The effect of benchmarking on management practices and equid welfare on Prince Edward Island, Canada
Bibliographic record
Abstract
There are challenges with assessing the welfare of equines due to their diverse uses and management practices. The objectives of this study were to (1) describe the prevalence of animal-based welfare outcomes and compliance with Canada’s National Farm Animal Care Council Code of Practice for the Care and Handling of Equines on equine farms in Prince Edward Island, Canada, and (2) determine the effect of benchmarking on compliance and awareness of the Code of Practice, as well as any changes in practices and animal-based welfare outcomes on these farms. Sixty farms were enrolled and were visited for an initial equine welfare assessment; all farms were then provided a benchmarking report that compared data collected from their equids to the other farms and the Code of Practice. Of these, 50 farms were re-visited the following year for a second assessment. The prevalence of animal-based outcomes in both years is presented descriptively, and differences between years were analyzed using paired t-tests and Chi-squared tests. On the second visit, 54% (n = 27) of farms showed more awareness of the Code of Practice and 48% (n = 24) of farms showed an improvement in at least one category of Code of Practice requirements. Of the animal-based measures, there was a significant reduction in the prevalence of unhealthy body condition score (−17.72, P < 0.001), integument lesions (−6.22, P = 0.020), and hoof abnormalities (−4.541, P = 0.026) from the first to the second visit. Although it is not clear if these changes occurred solely due to the benchmarking report, the results suggest that horse and donkey owners may be motivated to improve equid care and management using this approach. This study adds to the existing knowledge of equid welfare by providing a practical framework for the development of animal welfare assessments and the potential role of benchmarking in improving the welfare of horses and donkeys on Prince Edward Island and abroad.
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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 | 0.001 |
| 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 | 0.001 | 0.002 |
| 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".