An investigation of human-animal interactions and empathy as related to pet preference, ownership, attachment, and attitudes in children
Bibliographic record
Abstract
A group of elementary students (n = 155) were surveyed with respect to four aspects of relationships with pets—preference, ownership, attachment, and attitude—in order to further explore the connection that appears to exist between human–animal interactions and empathy. The investigation was initiated, in part, in order to elaborate upon findings from an earlier study (Daly and Morton 2003) and focused mainly on the relationships between children and dogs and cats, although horses, birds, and fish were also included. Some of the general findings related to dogs and cats are: (1) children who preferred (Pet Preference Inventory) both dogs and cats were more empathic than those who preferred cats or dogs only; (2) those who owned both dogs and cats were more empathic than those who owned only a dog, owned only a cat, or who owned neither; (3) those who were highly attached to their pets (Lexington Attachment to Pets Scale) were more empathic than those who were less attached; and (4) empathy and positive attitude (Pet Attitude Scale) revealed a significant positive correlation. As expected, girls were significantly more empathic than boys. Moreover, while cell sizes were low with respect to pet preference and ownership, empathy was also higher for individuals who expressed a preference for birds and horses. While the earlier study (Daly and Morton 2003) indicated that higher empathy was associated with dog ownership more so than other pets, including cats, a notable finding of the present study is that empathy appears to be positively associated with individuals who prefer, and/or who own, both a dog and a cat. The implications extend to the need: (1) for continued empirical research investigating the relationship between human–animal interactions and empathy; and (2) to refine the questions that lead to a clearer explanation of this relationship.
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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) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".