Inclusive Approaches by VAW Shelters: Respecting Women's Choice to be Together With Companion Animals
Bibliographic record
Abstract
Women often delay moving to VAW shelters if their companion animals’ safety is not ensured. Yet, few shelters accommodate them together. The purpose of this study is to explore what may help to promote services for women with companion animals facing violence, through learning from professionals who already provide support. Our email survey with VAW shelters in Ontario, Canada identified services and potential interviewees. Nine semi-structured telephone interviews with professionals were conducted to explore their experiences and views on human–animal relationships. All agencies that provided onsite programs, plus one about to start, participated. We utilized Critical Animal Studies as a theory to understand human–animal relationships through concepts such as intersectionality, anthropocentrism, speciesism, and feminist ethics of responsibility. The study found: (1) seven approaches shelters used to help women with companion animals; (2) programs that accept companion animals helped women move to shelters quickly but also affirmed women’s mutually respectful relationships with companion animals; (3) shelters also benefited, including expanding support from local communities and opportunities to educate them. The study suggests that by shifting ontological and theoretical approaches and including a critical examination of human–animal relationships at interpersonal and social structural levels, professional education promotes mobilizing resources for women with companion animals.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.015 | 0.020 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".