Animal Maltreatment as a Risk Marker of More Frequent and Severe Forms of Intimate Partner Violence
Why this work is in the frame
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Bibliographic record
Abstract
Although there is a growing body of literature documenting the co-occurrence of animal abuse and intimate partner violence (IPV), only a few studies have examined the relationship between animal maltreatment, types of IPV, and abuse severity. The results of those studies have been inconclusive and in some cases even contradictory. The current study contributes new findings to that specific segment of the literature and sheds some light on the inconsistent findings in previous studies. Data were gathered from 86 abused women receiving services from domestic violence shelters across Canada via a structured survey about pet abuse and the level and types of IPV perpetrated by abusive partners. Type and severity of IPV was measured using subscales of the Revised Conflict Tactics Scale (CTS2) and the Checklist of Controlling Behaviors (CCB). Animal maltreatment was measured using the Partner’s Treatment of Animals Scale (PTAS). Participants were divided into three groups: women who did not have pets during their abusive relationship ( n = 31), women who had pets and reported little or no animal maltreatment ( n = 21), and women who had pets and reported frequent or severe animal maltreatment ( n = 34). Examining within-group variations in experiences of IPV and pet abuse using a series of one-way between-groups ANOVA tests, this study provides evidence to support the conclusion that women who report that their partner mistreated their pets are themselves at significantly greater risk of more frequent and severe forms of IPV, most specifically psychological, physical, and sexual abuse. The findings point to the urgency of better understanding and mitigating the unique barriers to leaving an abusive relationship faced by women with companion animals.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it