Personality Traits and Owner-Dog Attachment in a Canadian Sample
Bibliographic record
Abstract
Abstract Much of the literature on owner-dog attachment and the influence of personality on the owner-dog relationship has originated in Europe, with few studies in North America. To address this imbalance, 29 owner-dog dyads from a Canadian population were tested in the Strange Situation Test (SST) and owners completed assessments of their own personalities (NEO-FFI-3), the personalities of their dogs (MCPQ-R), and their level of attachment to their dogs (DAQ). Attachment scores were comparable to those in previous research, and all owner-dog dyads were deemed to be securely attached. However, no predicted “matching” of seemingly analogous personality traits (e.g., human and dog Neuroticism) was found, and there was no relationship between dog personality and attachment behaviours during the SST. In contrast, owners with higher Extraversion scores initiated more contact with their dogs in the first reunion episode of the SST (following separation). Owners scoring low on Openness and/or Neuroticism had dogs with higher scores for Training Focus, suggesting that these dogs could more easily attend to a calm, stable owner. Owners who scored high in Openness had dogs with lower Amicability scores, possibly indicating more tolerance of a less desirable dog trait by such owners. Differences between the findings of this study and those conducted in Europe suggest that more emphasis should be given to the possible impact of cultural variation on the behaviours of and perceived relationships between owners and their dogs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".