Horse Housing on Prince Edward Island, Canada: Attitudes and Experiences Related to Keeping Horses Outdoors and in Groups
Bibliographic record
Abstract
Limited research has assessed the "human dimension" of horse care. The aims of this study were to (1) understand horse owner attitudes toward horse welfare when kept outdoors versus indoors and in groups versus individually, (2) compare horse owner attitudes toward horse welfare with the ways in which they house their horses, and (3) explore horse owner reasons for and challenges with their horses' housing. Seventy-six horse owners in Prince Edward Island, Canada completed a questionnaire. Non-parametric tests and quantitative content analysis were used for data analysis. Consistent with the way horses were kept, most (82-96%) owners agreed that horses' physical health, mental well-being, and natural living were better when kept outdoors and in groups. Fewer (64-68%) participants agreed that the horses' standard of care was better when kept outdoors or in groups. Results show associations between owners whose attitudes suggest indoor and/or individual housing is better for horse welfare and keeping their horses indoors part-time and/or individually. Two overarching themes were developed from owners' responses regarding their reasons and challenges related to the ways in which horses were housed: horse-centered and owner-centered care. The results indicate that horse owners' choices about their horses' housing correspond to beliefs about 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".