FGV Digital Repository
    • português (Brasil)
    • English
    • español
      Visit:
    • FGV Digital Library
    • FGV Scientific Journals
  • English 
    • português (Brasil)
    • English
    • español
  • Login
View Item 
  •   DSpace Home
  • Rede de Pesquisa e Conhecimento Aplicado
  • Projetos de Pesquisa Aplicada
  • Modelos matemáticos e computacionais de otimização de estratégias de redução dos níveis de violência no Brasil / RP
  • View Item
  •   DSpace Home
  • Rede de Pesquisa e Conhecimento Aplicado
  • Projetos de Pesquisa Aplicada
  • Modelos matemáticos e computacionais de otimização de estratégias de redução dos níveis de violência no Brasil / RP
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Browse

All of DSpaceFGV Communities & CollectionsAuthorsAdvisorSubjectTitlesBy Issue DateKeywordsThis CollectionAuthorsAdvisorSubjectTitlesBy Issue DateKeywords

My Account

LoginRegister

Statistics

View Usage Statistics

Exploring counterfactual antecedents to reduce criminality in Rio de Janeiro

Thumbnail
View/Open
PDF (3.765Mb)
Date
2021-12-22
Author
Guardieiro, Vitória Aquino
Metadata
Show full item record
Abstract
This research aimed to analyze the impact that socioeconomic and urban vari- ables have on crime rates for Rio de Janeiro. To achieve that, we structured a dataset containing, for each neighborhood, the per capita crime rate for three dif- ferent categories of crimes (against passersby, stores, and vehicles), socioeconomic variables (regarding education, age, income, employment, and others), and urban variables (such as the number of industries, commerces, and public administration establishments). Then, we used those features to identify the hotspot neighbor- hoods for each crime type and studied possible counterfactuals for specific regions. We found that not only do the different crimes happen in different parts of the city (passerby crime hotspots concentrate in the South and North zones, the store ones in the South and Central zones, and the vehicle ones in the North zone) but also that the counterfactuals vary significantly depending on the analyzed neigh- borhood. We found, for example, that economic inequality and unemployment can be relevant factors for the passerby and store crimes in wealthier neighborhoods, while the lack of people movement is relevant for other neighborhoods regarding passerby crime.
URI
https://hdl.handle.net/10438/31623
Collections
  • Modelos matemáticos e computacionais de otimização de estratégias de redução dos níveis de violência no Brasil / RP [6]
Knowledge Areas
Matemática
Tecnologia
Subject
Inteligência artificial
Aprendizado do computador
Criminalidade urbana
Violência
Segurança pública
Keyword
Violência

DSpace software copyright © 2002-2016  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 


DSpace software copyright © 2002-2016  DuraSpace
Contact Us | Send Feedback
Theme by 
@mire NV
 

 

Import Metadata