Investigating the relationship between canine training classes and post-adoption return rates in North American shelters
Bibliographic record
Abstract
Although millions of pets are adopted from shelters each year, a significant portion are returned after adoption which can have negative implications for pets and animal shelters. Previous studies indicate a strong correlation between behavioral issues and returned shelter dogs. The aim of this study was to investigate the relationship between attending post-adoption training classes and return rates. The study also looked at the distribution of return reasons between dogs who attended training and dogs who did not. Retrospective data between April 1st 2023 and March 31st 2024 was collected from three different shelters in North America (Seattle, WA; DeKalb, IL; Edmonton, AB). Of all the adopted dogs (n = 3325), we looked at which dogs attended training (n = 204) and used propensity score matching to generate a matched control group of dogs who did not attend training. The control group was matched based on age, sex, breed, shelter and intake type. The results showed no significant difference in return rates between dogs who attended training (8.3 %) and dogs who did not attend training (9.3 %) as analyzed by Pearson Chi Squared test ( X 2 (1) = 0.122, p = 0.727). However, of all the returned dogs, those who attended training were more likely to be returned for owner-related reasons (58.8 %), whereas dogs who did not attend training were more likely to be returned for animal-related reasons (78.9 %, X 2 (1) = 5.386, p = 0.020). While attending training classes at animal shelters may help to reduce behavioral returns, as shown by the shift in return reasons, they do not appear to reduce return rates significantly for the general shelter population. This finding provides valuable insight for shelters to improve their resource allocation. Shelters can have a more targeted approach by providing behavioral support for dogs that are at high-risk of return, thus setting those dogs up for a greater likelihood of permanent adoption. • Training classes were not associated with return rates among adopted shelter dogs. • The reasons for returned adoptions differed following training classes. • Attending training classes at animal shelters may help to reduce behavioral returns.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".