Exploring the impact of a brief positive experience on dogs’ performance and stress resilience during a learning task
Bibliographic record
Abstract
Learning and stress resilience can be influenced by recent experiences. Research has traditionally focused on the effects of negative situations and stressors on subsequent learning and stress resilience, while knowledge is limited regarding the effects of positive experiences. We aimed to examine the impact of a pre-session brief positive experience on dogs' learning and stress resilience. Pet dogs were quasi-randomly assigned to the experimental (n = 20) or control (n = 20) group, counterbalanced for age, sex, and breed clade. Experimental dogs received a session intended to provide a positive experience, which included a 15 min walk on a long leash, human interaction, exploration, playing, and olfactory-based foraging. Control dogs were kept on leash in an office without being allowed to explore nor interact with their owner or the experimenters for 15 min. After 60 s of habituation to the testing room, all dogs were taught to nose-touch the experimenter's hand. After the Learning phase, there was a 2 min Disruption phase, in which a remote-controlled car moved inside of a tub at a distance. Measures included the number of hand touches in each phase, the latency to return to the task, and general stress and affiliative behaviours. No differences were observed in the Learning phase. Surprisingly, experimental dogs exhibited higher stress levels than control dogs during the Disruption phase. These dogs also spent a significantly higher proportion of time in proximity to their owners, which could be interpreted as reassurance-seeking behaviour. Contrary to our predictions, exposure to a brief positive experience did not impact learning and, surprisingly, seemed to have made dogs more susceptible to stress during the Disruption phase. Several possible explanations are discussed, including the possibility of an unintentional induction of a negative emotional state by the termination of the positive experience, as well as differences in arousal, or habituation to the indoor environment.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".