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Understanding the behaviour of adopted northern Canadian community dogs through a mixed-methods approach

2025· article· en· W4408734437 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueApplied Animal Behaviour Science · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPet therapyAnimal-assisted therapyHUBzeroPsychologyAnimal welfareVeterinary medicineGeographyMedicineBiologyEcology

Abstract

fetched live from OpenAlex

Northern dogs, including pet, community, and free-roaming dogs (FRDs) from remote northern Canadian communities, are often rehomed to less remote areas as part of population control efforts. This change in environment may restrict dogs’ autonomy and freedom compared to the environment they originated from. This study aimed to investigate the post-adoption behaviour and adjustment of northern dogs using a mixed-methods approach. Data were collected from 357 participants through an 89-item survey distributed via social media and author networks. The survey addressed owner and dog demographics, lifestyle factors, and dog behaviour using a shortened version of the Canine Behaviour and Research Questionnaire (C-BARQ). Additionally, an open-ended question explored owners’ perspectives of their dog’s adjustment to the home. An exploratory factor analysis (EFA) was conducted on the shortened C-BARQ to examine the factor structure. Multiple logistic regressions were used to analyse the influence of lifestyle and demographic parameters on C-BARQ subscale scores. Qualitative content analysis was used to process open-ended responses. The EFA revealed a 13-factor structure, including Stranger-directed aggression, Owner-directed aggression, Dog-directed aggression and fear, Stranger-directed fear, Non-social fear, Touch sensitivity, Separation-related behaviour, Chasing, Escape, Attachment, Excitability, Energy, Trainability and Dog rivalry. Adopted Northern dogs demonstrated high scores for Chasing, Energy, and Attachment, with influencing factors including age at adoption, access to other dogs, and household size. Content analysis identified key themes related to the adjustment process and factors influencing it. Overall, a substantial portion of owners reported that Northern dogs displayed behaviour problems post-adoption, which may stem from dogs experiencing frustration, related to a lack of control over their new environments and a misalignment with their previous reality. This study highlights the importance of understanding and fulfilling the unique social, physical and cognitive needs of Northern dogs to ensure a smoother adjustment process post-adoption. • 357 owners were surveyed to understand the adjustment and behaviour of Northern dogs’ post-adoption. • High prevalence of behaviour problems: 93.84 % of northern dog owners reported at least one behaviour problem post-adoption. • Key behaviours noted: Northern dogs had high C-BARQ scores for chasing, energy and attachment. • Factors influencing behaviour: Dog age at adoption, access to other dogs and household size impacted behaviour. • Role of frustration: Frustration may be playing a role in Northern dogs’ transition from free roaming to a more restricted lifestyle due to a loss of autonomy, highlighting the importance of fulfilling the social, physical, and cognitive needs of Northern dogs.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.315
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.075
GPT teacher head0.385
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it