How Can the Ethological Study of Dog-Human Companionship Inform Social Robotics?
Bibliographic record
Abstract
This chapter utilises the human-dog relationship as an example of the possible ways to examine human-animal relationships in general and as a model of a possible future human-robot relationship, assuming some functional convergence between social robots and dogs in relation to humans. The behavioural interaction between humans and dogs may provide important insights for ethological research on heterospecific social behaviour. The studies on dog-human relationships suggest that dogs are better at adjusting their interactions to the owners' demands than other companion animals, and on the basis of questionnaire studies, dogs interact with their owners in ways, which result in higher levels of attachment. In recent years several so called companion robots have been developed, many of which capitalize on the human-pet relationship. Recently different comparative studies were conducted investigating the dog-human and robot-human interactions using AIBO and PLEO as robotic companions. Keywords:AIBO; dog-human relationships; ethological research; PLEO; social robots
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".