Intimate Partner Violence, Animal Maltreatment, and Animal Safekeeping: Findings From a Public Survey
Bibliographic record
Abstract
While research on the link between intimate partner violence (IPV), animal maltreatment, and the need for animal safekeeping has increased significantly in recent years, previous research has included samples of victims/survivors and service providers. The present study examined public awareness of the link between IPV, animal abuse, and the need for animal safekeeping. The study also examined awareness of services and supports and inquired about respondents' experiences with animal safekeeping in situations of IPV through an online survey that was open to the public. The survey included quantitative and qualitative questions and asked about three types of animals: pets, livestock, and service animals. Respondents were 176 residents of Saskatchewan who live in urban, rural, and northern areas of the province. Findings indicate that many respondents knew people who experienced IPV where their animals were also abused. Several respondents had assisted someone in planning for temporary animal safekeeping as part of their plan to exit a relationship when they were experiencing IPV. These results demonstrate the importance of "natural supports," including family, friends, and neighbors, for providing information, support, and assistance with animal safekeeping in situations of IPV, especially in rural and northern communities that do not have domestic violence and animal welfare agencies nearby. Findings also indicate public support for increasing services and supports for people who experience IPV and own animals, including pet-friendly domestic violence shelters and rental housing, to allow people and animals escaping IPV to remain together.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".