The Connection Between Animal Abuse, Emotional Abuse, and Financial Abuse in Intimate Relationships: Evidence From a Nationally Representative Sample of the General Public
Bibliographic record
Abstract
This article empirically examines the extent to which the co-occurrence of the maltreatment of companion animals and intimate partner violence (IPV) previously documented in samples of women accessing services from domestic violence shelters extends to a nationally representative sample of the general Canadian population, with a specific focus on emotional and financial abuse. Using data from the intimate partner victimization module of the 2014 Canadian General Social Survey ( n = 17,950), the authors find that reporting one’s intimate partner threatened or abused companion animals in the home increased the probability that one had experienced at least one form of emotional abuse or financial abuse by 38.6% ( p ≤ .001) and 7.5% ( p ≤ .001), respectively, net of several key control variables. Moreover, the findings indicate that those who identify as women are significantly more likely to report their partner emotionally or financially abused them and threatened or mistreated their pet(s); the connection between animal maltreatment and IPV is particularly pronounced for emotional IPV when compared with other forms of IPV; challenge the commonplace conceptualization of animal abuse as a form of property abuse; and suggest a need for a more nuanced understanding of IPV perpetrators vis-à-vis animal maltreatment. This is the first study to use nationally representative data to assess the co-occurrence of animal abuse and IPV, and as such, it makes significant contributions to the interdisciplinary literature on animal abuse and IPV.
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How this classification was reachedexpand
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".