“My Horse Has a Voice; I’m Just Trying to Figure Out What to Do With It”: Communication Between Canadian Dressage Coaches, Riders, and Horses
Bibliographic record
Abstract
Evidence suggests that competitive dressage may compromise horses’ physical and emotional welfare. The coach–rider–horse relationship is paramount to the wellbeing of dressage horses. Therefore, this study sought to explore the relationship between equestrian coaches, riders, and horses during dressage lessons. Specifically, the objectives of this study were to explore (1) the way dressage coaches and riders interpret, respond to, and elicit specific horse behaviors, and (2) the way these interactions influence horse behavior and the learning process between coaches and riders. Using an ethnographic case study design, the first author spent 2–6 weeks with each of the four participating Equestrian Canada certified dressage coaches, conducting interviews with each coach (n = 4) and rider (n = 19), recording field notes and video recording 30 dressage lessons with a Pivo device and a GoPro camera strapped to the rider’s chest. Multimodal interaction analysis was employed to transcribe and analyze rider and horse behavior and coach–rider dialogue during dressage lessons. Reflexive thematic analysis was applied to field notes, interviews, and video transcripts to develop codes and themes to represent the data. Three themes were developed. The first theme portrayed that equestrian coaches believed they listened to horse behavior to guide their application of horse training methods. The second theme highlighted that horses’ behavior may instill emotions (e.g., fear) in riders, which in turn affects their ability to implement instruction from the coach. The last theme underscored the lack of clear, actionable language used during dressage lessons that may hinder communication between coach and rider, contributing to negative affective states for the horse. Overall, the findings suggest a need to evaluate training approaches, emphasizing that equestrians’ emotions may be a barrier to understanding coach instructions and implementing training methods that promote horse welfare.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".