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Evolution and study of a copycat effect in intimate partner homicides: A lesson from Spanish femicides

Torrecilla, José L., Quijano-Sánchez, Lara, Liberatore, Federico, López-Ossorio, Juan J. and González-Álvarez, José L. 2019. Evolution and study of a copycat effect in intimate partner homicides: A lesson from Spanish femicides. PLoS ONE 14 (6) , e0217914. 10.1371/journal.pone.0217914

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Abstract

Objectives This paper focuses on the issue of intimate partner violence and, specifically, on the distribution of femicides over time and the existence of copycat effects. This is the subject of an ongoing debate often triggered by the social alarm following multiple intimate partner homicides (IPHs) occurring in a short span of time. The aim of this research is to study the evolution of IPHs and provide a far-reaching answer by rigorously analyzing and searching for patterns in data on femicides. Methods The study analyzes an official dataset, provided by the system VioGén of the Secretaría de Estado de Seguridad (Spanish State Secretariat for Security), including all the femicides occurred in Spain in 2007-2017. A statistical methodology to identify temporal interdependencies in count time series is proposed and applied to the dataset. The same methodology can be applied to other contexts. Results There has been a decreasing trend in the number of femicides per year. No interdependencies among the temporal distribution of femicides are observed. Therefore, according to data, the existence of copycat effect in femicides cannot be claimed. Conclusions Around 2011 there was a clear change in the average number of femicides which has not picked up. Results allow for an informed answer to the debate on copycat effect in Spanish femicides. The planning of femicides prevention activities should not be a reaction to a perceived increase in their occurrence. As a copycat effect is not detected in the studied time period, there is no evidence supporting the need to censor media reports on femicides.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Public Library of Science
ISSN: 1932-6203
Date of First Compliant Deposit: 9 December 2019
Date of Acceptance: 20 May 2019
Last Modified: 04 Feb 2020 15:11
URI: https://orca.cardiff.ac.uk/id/eprint/127416

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