Social Effects of a Dog's Presence on Children with Disabilities
Bibliographic record
Abstract
Productive and positive interactions between dogs and humans have been documented in studies using dogs trained as companion animals and as assistants for people with disabilities. In this study, the effects of the presence of a dog on social interactions between three 5–9-year-old children with developmental disabilities and their teacher at an elementary school were analyzed. A single-case experimental design with repeated measures and with replicated effects across participants was employed to assess changes in interactions from baseline to an intervention condition. During baseline, interactions were assessed in the social environment of a room adjacent to the classroom, which had a toy dog and other play materials, during time with the teacher. The experimental change introduced sequentially and systematically across the participants was the additional presence of an obedience-trained dog, a German Shepherd/Labrador Retriever cross. Interactions between the children and their teacher were examined during morning sessions using reliable direct observation interval recording procedures. All participants demonstrated an increase in overall positive initiated behaviors (verbal and non-verbal) toward both the teacher and the dog. The children also showed an overall decrease in negative initiated behaviors. In addition, observational ratings showed positive generalization of improved social responsiveness by the children in their classroom following the completion of the experimental sessions. This study supports the position that children with developmental disabilities benefit from the use of skilled dogs as teaching assistants and therapeutic adjuncts.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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".