Animal Safekeeping in Situations of Intimate Partner Violence: Experiences of Human Service and Animal Welfare Professionals
Bibliographic record
Abstract
Although knowledge of the link between intimate partner violence (IPV) and animal maltreatment has increased significantly in recent years, few studies have examined service providers’ experiences with IPV and concurrent animal abuse, as well as animal safekeeping in situations of IPV. The present study documented human service and animal welfare service providers’ experiences supporting victims/survivors of IPV, who owned pets and livestock, and included service providers in rural and northern communities in Saskatchewan. Online surveys were completed by 128 human service professionals (including domestic violence shelter workers, domestic violence counsellors, victim services workers, police, and legal professionals) and 43 animal welfare professionals (including workers from animal rescues, humane societies, Societies for the Prevention of Cruelty to Animals [SPCAs], and veterinary clinics) ( n = 171). Respondents shared information relating to their awareness of the link; their experiences responding in situations of IPV and concurrent animal abuse, including arranging animal safekeeping in situations of IPV; and successes and challenges related to effective service provision. Results include descriptions of intersecting risks to people and animals. Service providers shared ways that they have assisted victims/survivors who own animals, such as through animal safekeeping programs. Both human service and animal welfare professionals expressed the need for pet-friendly domestic violence shelters and pet-friendly long-term housing options. Service providers offered recommendations for improving education and training; improving provision of services of victims/survivors of IPV and their animals, including improving access to Emergency Intervention Orders and establishing funding for animal safekeeping in situations of IPV; and strengthening existing and building new partnerships.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".