Do the Owner-horse Pairs Have Similar Personality Traits According to the Short Inventory of the Horse Personality?
Bibliographic record
Abstract
Abstract The personality of a horse is thought to influence the quality of horse-human relationship. In this study, we developed a questionnaire to assess horse’s personality. For validation, 2431 horse-owners filled it out for their horse along with an existing questionnaire to determine their personality. Out of this sample, 39 horses were tested in personality tests, to monitor the owners' responses to the questionnaires. We then compared the results of the equine questionnaire to the results of the personality tests and then investigated which components of the equine personality and of the owner, were similar. Personality scores obtained from the questionnaire showed, first, that owners with a higher Emotional stability score perceived their horses to be also easily stressed (r = 0.26, N = 2431, p < 0.05) and secondly that Conscientious owners described their horses as Conscientious as well (r = 0.26, N = 2431, p < 0.05). The personality tests confirmed the scores for the Emotional stability trait, i.e. easily stressed horses were more active during personality tests (r = 0.56, N = 39, p < 0.05). These results do not allow us to exclude the effect of the owner's personality on his horse in the long term.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".