“But my horse is well cared for”: A qualitative exploration of cognitive dissonance and enculturation in equestrian attitudes toward performance horses and their welfare
Bibliographic record
Abstract
Abstract There is concern amongst the public, equestrians, animal welfare organisations, and horse-sport governing bodies regarding the welfare of performance horses, but equestrian culture appears slow to change. The present study seeks to increase our understanding of human factors underlying the persistence of welfare-compromising management and training practices within the performance horse world. Individual, semi-structured interviews focused on equestrians’ attitudes were conducted with 22 equestrians from classical equestrian disciplines in the US, Canada, and the UK. Interview transcripts were analysed using reflexive thematic analysis. Five main themes were identified: perception of welfare issues; conflicting conceptions of a good life; objectification of the horse; instrumentalisation of horse care; and enculturation. Participants perceived and were concerned about horse welfare, but expressed dissonance-reducing strategies, including trivialisation, reframing and justification. Participants shared conflicting conceptions of a good life and described how equestrian activities may infringe upon horse welfare. Objectification of horses was among the attitudinal factors identified that may permit persistence of harmful practices, while the instrumentalisation of care theme showed how management practices often focused on performance and the horse’s job more than care about the horse. Finally, enculturation (the process of adopting attitudes and behaviours of a culture) in equestrianism may be fundamental to maintaining practices and attitudes that compromise horse welfare. These findings provide an enhanced understanding of why horse welfare issues persist in classical equestrian disciplines and may inform future human behaviour change strategies to promote improved 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 | 0.027 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.025 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| 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".