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Anthrozoös
A multidisciplinary journal of the interactions between people and other animals
Volume 29, 2016 - Issue 1
462
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Original Articles

Predictors of Views about Punishing Animal Abuse

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ABSTRACT

The current study used scenarios of animal cruelty based on actual events to explore what factors predict perceptions of punishments for animal cruelty. Five hundred thirty-eight university undergraduates participated in the study. Participants read scenarios based on an actual event of animal cruelty and with information on statutes addressing animal cruelty in their state. Participants were then asked to give ratings for punishment of the animal cruelty perpetrator. A canonical correlation analysis was used to test the multivariate shared relationship between the set of eight predictor variables and the criterion variable set of 15 punishment ratings. The response distributions were highly skewed for seven of the 15 criterion variables, highlighting the strong sentiments participants expressed against animal cruelty. The canonical correlation analysis identified significant criterion variables that were predicted by two of the empirically manipulated predictor variables (Perpetrator Age and Location of Crime) along with one subject variable (Participant Femininity). This set of predictor variables correlated with the criterion variable set that included Allowed with Children and Amount of Fine for Suffering. There was a main effect for Perpetrator Age, such that the degree to which participants thought a perpetrator of animal cruelty should be allowed alone with children depends on the age of the perpetrator. Mean responses were stronger for scenarios with perpetrators aged 28 than with perpetrators aged 12. The average response to Amount of Fine for Suffering was larger when the animal cruelty happened at a pet kennel than if the crime occurred at an animal shelter. Implications for these significant predictor and criterion variables are discussed in the context of interdisciplinary theory and practical implications for public policy.

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