Session 3: Preserving the critical bond between domestic violence survivors and pets: breaking the barriers
Bibliographic record
Abstract
Human abuse and animal abuse are clearly linked. When it comes to domestic violence, as many as 70% of survivors report having a pet and that a pet was injured, maimed, killed or threatened in the last year. In addition, 48% of victims report delaying leaving out of concern for their pet. Despite the barrier pets pose in a victim's ability to leave, few domestic violence shelters house pets. RedRover helps survivors overcome this barrier through various grant programs, an online directory and outreach efforts that help victims and advocates find solutions.\nThis presentation will review examples of the types of co-sheltering, community partnerships and other programs domestic violence shelters have developed to ensure survivors can escape their abusive situations with their pets, as well as the resources and assistance RedRover provides, including the safeplaceforpets.org website, which contains a searchable database of over 600 programs and shelters throughout the United States and Canada that offer survivors assistance with finding temporary housing for their pets. Since 2012 we have helped over 60 shelters start or expand facilities for pets and provided over 500 grants for domestic violence survivors to board their pets while they stay at a domestic violence shelter. In October of this year, we are launching a campaign to increase awareness of safeplaceforpets.org among domestic violence victims, and I will provide a campaign update and have resources available to share.\nThrough our outreach work, surveys and conversations with advocates, we have also learned about the major obstacles that have historically prevented domestic violence shelters from housing pets. We will share these key obstacles and a few of the solutions created using strong community partnerships, along with an overview of what is offered in Allie Phillips' SAF-T Start-Up Manual, which is the guide we encourage people to follow to help answer questions regarding the various co-sheltering models and how to set them up.\nCurrently nine states in the United States do not have even one shelter that allows pets. RedRover's current outreach efforts have focused on these nine states, with the goal of having every U.S. state include at least one pet-friendly domestic violence shelter by 2022. In our most recent round of grant applications, we are happy to report that three of these nine states have applied! This presentation will touch on outreach strategies that have been effective, as well as open up a large or small-group discussions within the audience for ideas, connections and possible partnerships to address specific obstacles identified.\nRedRover is a 501(c)3 animal welfare nonprofit organization based in Sacramento, CA that works in the United States and Canada. RedRover believes pets are family, and we keep families together by helping animals and people in immediate crisis through our RedRover Relief and RedRover Responders programs, crises such as: natural disasters, veterinary emergencies or domestic violence. We also work to prevent animal cruelty and neglect by increasing empathy and understanding about animals through our RedRover Readers program.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.169 | 0.060 |
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".