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Dissertação
Modelo de decisão multicritério para classificar municípios quanto ao risco de violência doméstica contra a mulher: um estudo a partir da Amazônia paraense
Violence against women (VAW) is one of the most serious local and global public health issues, requiring effective public policies to tackle it. The aim of this project is to present a multi-criteria decision analysis (MCDA) model based on ELECTRE Tri-B to classify municipalities in the state of...
Autor principal: | SOUZA JÚNIOR, João Lúcio de |
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Grau: | Dissertação |
Idioma: | por |
Publicado em: |
Universidade Federal do Pará
2024
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Assuntos: | |
Acesso em linha: |
https://repositorio.ufpa.br/jspui/handle/2011/16663 |
Resumo: |
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Violence against women (VAW) is one of the most serious local and global public health
issues, requiring effective public policies to tackle it. The aim of this project is to present
a multi-criteria decision analysis (MCDA) model based on ELECTRE Tri-B to classify
municipalities in the state of Pará according to the risk of violence against women in their
territories, in order to map them in descending order in terms of this risk. A model is
proposed that considers among the criteria for analysis and classification the existence of
support and protection facilities for women in these municipalities, called the Assistance
and Protection Index (IAP), as well as socio-economic indicators of the municipalities
such as Gross Domestic Product (GDP), Human Development Index (HDI) and Degree of
Income Concentration (GINI). The results obtained from the multi-criteria decision model
reveal interesting patterns: municipalities with a lower risk of violence against women
(VCM), protective equipment and good socio-economic indicators, but a high rate of
complaints, corroborating the maxim that environments with more mechanisms to protect
women lead to a higher number of complaints. Thus, the methodology used allowed for the
identification of municipalities where there is a greater risk of VAW, the mapping of these
municipalities and regions, enabling targeted actions that are more likely to be effective in
combating and preventing VAW. |