The spatial heterogeneity of factors of feminicide: The case of Antioquia-Colombia

In Latin America, homicide is a leading cause of death among women. The aim of this paper is to examine the spatial heterogeneity of factors influencing feminicide in Antioquia, Colombia. This article adds the impact of drug trafficking location on feminicide to the existing research. Classic models...

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Autores:
Tipo de recurso:
Fecha de publicación:
2018
Institución:
Universidad de Medellín
Repositorio:
Repositorio UDEM
Idioma:
eng
OAI Identifier:
oai:repository.udem.edu.co:11407/4573
Acceso en línea:
http://hdl.handle.net/11407/4573
Palabra clave:
Coca production; Drug trafficking; Feminicide; Geographically weighted Poisson regression; Spatial non-stationarity
drug; Gross Domestic Product; heterogeneity; mortality; parameterization; regression analysis; trafficking; womens status; Antioquia [Colombia]; Colombia
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http://purl.org/coar/access_right/c_16ec
Description
Summary:In Latin America, homicide is a leading cause of death among women. The aim of this paper is to examine the spatial heterogeneity of factors influencing feminicide in Antioquia, Colombia. This article adds the impact of drug trafficking location on feminicide to the existing research. Classic models assume that the parameters of these factors are spatially distributed in a constant manner. However, this assumption has been frequently challenged due to the systematic differences of feminicide occurring within different geographical units, giving rise to the presence of spatial heterogeneity. In this article, geographically weighted Poisson regression (GWPR) is used to explore the spatial heterogeneity in these data relationships. Feminicide in the Department of Antioquia, Colombia, is studied using a range of classic explanatory factors. The results show that, in addition to the classic factors, coca-producing areas in Antioquia are directly related to number of feminicides. The findings also show that relationships in feminicide data are better presented by GWPR than by the classic model. © 2018 Elsevier Ltd