Exploring the role of our contacts with pets in broadening concerns for animals, nature, and fellow humans: a representative study
Bibliographic record
Abstract
While pet ownership is normative in many occidental countries, whether humans' proximal contacts with pets have implications for attitudes and behaviors toward other (non pet) animals, nature, and fellow humans, has received limited empirical attention. In a large representative sample, we investigate whether pet ownership and positive contact with pets are associated with more positive attitudes and heightened concerns for non-pet animals, nature, and human outgroups. A cross-sectional questionnaire survey was conducted among Canadian adults (619 pet owners, 450 non-pet owners). Pet owners reported more positive attitudes toward non-pet animals (e.g., wild, farm animals), higher identification with animals, more positive attitudes toward human outgroups, higher biospheric environmental concerns, higher human-environment interdependence beliefs, and lower usual meat consumption. Positive contact with pets was also associated with most of these outcomes. Solidarity with animals, a dimension of identification with animals, emerged as a particularly clear predictor of these outcomes and mediated the associations between positive contact with pets and positive attitudes toward non-pet animals, biospheric, egoistic, and altruistic environmental concerns, human-environment interdependence beliefs, and diet. Our results provide support for the capacity of pets to shape human consideration for a broad range of social issues, beyond the specific context of human-pet relations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".