Factors associated with hare mortality during coursing
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Hare coursing is a widespread but controversial activity. In an attempt to reduce hare mortality and mitigate the activity's impact on hare welfare, the Irish Coursing Club introduced measures including the compulsory muzzling of dogs in 1993. However, the efficacy of these measures remained the subject of heated debate. Official records, corroborated by independent video evidence, were used to assess the fate of individual Irish hares (Lepus timidus hibernicus) during coursing events from 1988-2004. Muzzling dogs significantly reduced levels of hare mortality. In courses using unmuzzled dogs from 1988/89-1992/93 mean hare mortality was 15.8%, compared to 4.1% in courses using muzzled dogs from 1993/94-2003/04. Further reductions in mortality could not be accounted for by muzzling dogs, supporting the efficacy of other factors such as improved hare husbandry. The duration of the head start given to the hare prior to the release of the dogs significantly affected the outcome of the course. Hares that were killed had head starts of greater duration than those that were chased but survived, suggesting the former may have been slower. The selection of hares by assessment of their running ability may provide means to reduce hare mortality during courses further. Our findings support the efficacy of measures taken to mitigate the impact of coursing on individual hares. However, it is necessary to evaluate the impact of removing hares from the source population and of returning coursed hares to the wild before the wider impact of coursing on wild hare populations can be determined.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it