Effects of jockey position and surfaces on horse movement asymmetry and horse-jockey synchronisation during trotting exercise
Bibliographic record
Abstract
Racehorses and jockeys can incur injuries, not only during gallops, but also during routine trotting exercise to access gallop tracks or warm-up. Understanding how jockey position affects racehorse movement may influence safety, and this may vary across different surface conditions. This study used inertial sensing technology (XSens MTw sensors) and linear mixed models to quantify and determine the significance (p ≤ 0.05) of jockey riding position ('rising' versus 'two-point seat') and surface type (artificial, grass and tarmac) on: 1) time offsets between stance and flight phases; 2) horses' vertical upper body movement asymmetry and 3) time lags (in % of stride time) between horse and jockey maximum and minimum vertical displacements. Six ex-racehorses were recruited on a convenience basis from the British Racing School and were ridden by one jockey. Surface type did not significantly influence timings between the stance and flight phases or horse asymmetry. Jockey riding position was linked to a 1.8% difference in stance phase offsets (p < 0.001) and 0.9% difference in flight phases (p = 0.015) for two-point seat versus rising trot. Jockey riding position also affected horse movement asymmetry at the poll across stance phases (weight bearing asymmetry, p = 0.005) and symmetry at the withers and sacrum across flight phases (push-off asymmetry, p < 0.001). In rising trot, the jockey reduced poll asymmetry around the seated stance phase, but increased withers and sacrum push-off asymmetries after the seated stance phase. Time-offsets between the horse and jockey minimum and maximum displacements around stance and flight phases, respectively, were also significantly affected by jockey riding position (all p < 0.001). As the jockey stood up in their stirrups at stance, in either the rising component of rising trot or in the two-point seat, their delay in following the horse's movements increased by 2.8-4.5%, compared to when they were seated (p < 0.001). There was also an increased delay of the jockey by 0.6-0.8% around stance on tarmac compared to on the artificial surface (p ≤ 0.019). During flight phases, jockey displacement maximums were reached 5.5-7.0% and 9.3-11% after the horse following the seated stance in rising trot and during two-point seat, respectively, but jockey movements preceded horse movements around the post-standing flight phases by 4.9-7.3% in rising trot. In summary, jockey position had a greater impact on horse movement asymmetry and horse-jockey synchronisation than surface type. However, further work is required to relate study outcomes to injury risk.
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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 | 0.000 |
| 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".