Factors Affecting Behavior and Welfare of Service Dogs for Children With Autism Spectrum Disorder
Bibliographic record
Abstract
The use of service dogs for children with autism spectrum disorder is a relatively new and growing assistance-dog application. The objectives of this article were to identify and describe the factors influencing an autism service dog's performance and the impact of this type of placement on the dog's welfare. A qualitative approach uses interview and observational data to characterize the dogs' behaviors and welfare with relevancy to the dogs' home environments. Identification of potential physical stressors included lack of rest or recovery time after working, unintentional maltreatment and prodding by children with autism, lack of predictability in daily routines, and insufficient opportunities for recreational activities. Results revealed that these dogs formed social relationships primarily with the parents and second with the children with autism. Failure to recognize and respond to the identified physical, emotional, and social needs can have serious impacts on the behavior, welfare, and performance of these autism service dogs, as well as parental satisfaction. As applications of service dogs expand to new domains, there is a need to assess and understand factors and variables affecting the relationship between family and service dog to ensure continued success of these programs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".