Reasons for Guardian-Relinquishment of Dogs to Shelters: Animal and Regional Predictors in British Columbia, Canada
Bibliographic record
Abstract
Dogs are relinquished to animal shelters for animal-related or guardian-related reasons. Understanding what drives relinquishment patterns is essential for informing intervention opportunities to keep animals with their guardians. Whereas, overall reasons for relinquishment in a given shelter system have been well explored, analysis of human and animal predictors of relinquishing for a specific reason has not been previously attempted. We used characteristics of relinquishment including year, population of the relinquishing guardian's region, health status of the dog, breed, age group, weight, and sex to predict reasons for dog relinquishment to British Columbia (BC) Society for the Prevention of Cruelty to Animals (SPCA) shelters across BC between 2008 and 2019 ( n = 32,081). Relinquishment trends for puppies and adult dogs were also viewed and described. From 2008–2019, the proportion of dogs relinquished relative to total intake remained consistent (range: 31–35%). Primary reasons reported by guardians were having too many dogs (19%), housing issues (17%), personal issues (15%), financial issues (10%), dog behavior (10%), and guardian health (8%). Over years, an increasing proportion of dogs were relinquished for the reason “too many” (OR = 1.16, 95% CI, 1.10–1.23, p < 0.001) and “behavior” (OR = 1.34, 95% CI, 1.26–1.43, p < 0.001), while a decreasing proportion were relinquished due to financial problems (OR = 0.94, 95% CI, 0.88–1.00, p = 0.047). Being a puppy, mixed breed, small, and from a small or medium population center predicted the reason “too many.” Being a senior, Healthy, or from a medium or large population center predicted the reason “housing issues.” Being a non-puppy, Healthy dog in a large population center predicted the reason “personal issues.” Being a puppy, non-Healthy, female, and from a large population center predicted the reason “financial issues.” Being a larger young adult or adult and Healthy predicted the reason “dog behavior.” Being an adult or senior small dog from a small population center predicted the reason “guardian health.” Particularly promising region-specific intervention opportunities include efforts to prevent too many animals in small population centers, improvement of pet-inclusive housing in large population centers, and providing animal care support in large population centers. Accessible veterinary services, including low-cost or subsidized care, likely benefit dog retention across BC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".