Behaviour problems in racing standardbred horses in Ontario
Bibliographic record
Abstract
This thesis is an investigation into the welfare of racing Standardbred horses, using behaviour problems as indicators. A questionnaire, administered at 14 racetracks across Ontario, was used to collect data on the prevalence, solutions and risk factors of 16 behaviour problems. Performance variables were also compared to behaviour problems and management factors. From 1295 questionnaires, the most prevalent behaviour problems were wood-chewing and pawing, reported at above 40%. Bites and kicks directed at handlers, unmeasured elsewhere were reported at approximately 10% each. Choices of solutions to problems indicate that education and years of racetrack experience did not improve handling and suggest that grooms may lack knowledge of learning theory and equine motivation. Aggression and daily access to paddock/pasture were most strongly associated with performance. Daily access to paddock/pasture for horses and specialised training for grooms have potential for improving racing Standardbred welfare.
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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 | 0.000 | 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 | 0.001 |
| 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".