There is nothing so bad that it can not work: a Bayesian analysis of poverty
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Redes (Santa Cruz do Sul. Online) |
Texto Completo: | https://online.unisc.br/seer/index.php/redes/article/view/12685 |
Resumo: | This article aims to understand the relationships between different forms of poverty and, thus, to verify if a specific type of deprivation inhibits the individual's ability to overcome other forms of deprivation. An approach used to understand the mechanisms that govern how the relations between the levels of poverty refer to the Bayesian network. The data used refer to information on income, health, education and housing for 5,565 Brazilian municipalities between 1970 and 2010, being a source of information provided by the Brazilian Institute of Geography and Statistics. The results highlighted the existence of relations between the analyzed aspects of poverty. Direct influences of all deprivations on health conditions were observed, indicating that precarious health conditions usually arise in environments where other types of diseases arise. The education indicator reflects information on monetary deprivation, and this relationship is positive. Finally, monetary shortages are also responsible for limiting access to decent housing and a healthier living condition. |
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There is nothing so bad that it can not work: a Bayesian analysis of povertyNo hay nada tan ruim que no puede piorar: un análisis Bayesiana de la pobrezaNão há nada tão ruim que não possa piorar: uma análise bayesiana da pobrezaPobreza. Rede Bayesiana. Municípios.Poverty. Network Bayesian. Municipals.La pobreza. Red Bayesiana. Municipios.This article aims to understand the relationships between different forms of poverty and, thus, to verify if a specific type of deprivation inhibits the individual's ability to overcome other forms of deprivation. An approach used to understand the mechanisms that govern how the relations between the levels of poverty refer to the Bayesian network. The data used refer to information on income, health, education and housing for 5,565 Brazilian municipalities between 1970 and 2010, being a source of information provided by the Brazilian Institute of Geography and Statistics. The results highlighted the existence of relations between the analyzed aspects of poverty. Direct influences of all deprivations on health conditions were observed, indicating that precarious health conditions usually arise in environments where other types of diseases arise. The education indicator reflects information on monetary deprivation, and this relationship is positive. Finally, monetary shortages are also responsible for limiting access to decent housing and a healthier living condition.Este artículo pretende comprender las relaciones existentes entre diferentes formas de pobreza y, así, verificar si un determinado tipo de carencia inhibe la capacidad del individuo de superar de otras formas de privaciones. El enfoque utilizado para entender los mecanismos que rigen las relaciones entre distintos niveles de pobreza se remite a la red bayesiana. Los datos utilizados se refieren a las informaciones sobre renta, salud, educación y vivienda para 5.565 municipios brasileños entre 1970 y 2010, siendo la fuente de tales informaciones debida al Instituto Brasileño de Geografía y Estadística. Los resultados destacan la existencia de relaciones entre las facetas de la pobreza analizadas. Se observaron influencias directas de todas las privaciones sobre las condiciones de salud, indicando que precarias en salud normalmente surgen en ambientes donde otros tipos de carencias afloran. Otro hecho importante es que las privaciones educativas no son explicadas por ninguna de las ópticas tratadas y, por lo tanto, retratan un carácter exógeno. El indicador de educación también refleja información sobre la privación monetaria, siendo tal relación de carácter positivo. Por último, las carencias monetarias son responsables de limitar el acceso a una vivienda digna.Este artigo visa compreender as relações existentes entre diferentes formas de pobreza e, assim, verificar se um determinado tipo de carência inibe a capacidade de o indivíduo superar de outras formas de privações. A abordagem utilizada para entender os mecanismos que regem as relações entre distintos níveis de pobreza remete-se a rede bayesiana. Os dados utilizados referem-se às informações sobre renda, saúde, educação e habitação para 5.565 municípios brasileiros entre 1970 e 2010, sendo a fonte de tais informações devida ao Instituto Brasileiro de Geografia e Estatística. Os resultados destacam a existência de relações entre as facetas da pobreza analisadas. Foram observadas influências diretas de todas as privações sobre as condições de saúde, indicando que precariedades em saúde normalmente surgem em ambientes onde outros tipos de carências afloram. O indicador de educação reflete informações sobre a privação monetária, sendo tal relação de caráter positivo. Por fim, carências monetárias são responsáveis por limitar, também, o acesso a uma moradia digna e a uma condição de vida mais salutar.Edunisc - Universidade de Santa Cruz do Sul2020-11-27info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://online.unisc.br/seer/index.php/redes/article/view/1268510.17058/redes.v25i4.12685Redes ; Vol. 25 (2020): Edição Especial; 1933-1952Redes; Vol. 25 (2020): Edição Especial; 1933-1952Redes; Vol. 25 (2020): Edição Especial; 1933-1952Redes; v. 25 (2020): Edição Especial; 1933-19521982-6745reponame:Redes (Santa Cruz do Sul. Online)instname:Universidade de Santa Cruz do Sul (UNISC)instacron:UNISCporhttps://online.unisc.br/seer/index.php/redes/article/view/12685/pdfCopyright (c) 2020 Redesinfo:eu-repo/semantics/openAccessCosta, Rodolfo Ferreira Ribeiro da2021-01-08T19:43:05Zoai:ojs.online.unisc.br:article/12685Revistahttp://online.unisc.br/seer/index.php/redeshttp://online.unisc.br/seer/index.php/redes/oairedes_unisc_maff@terra.com.br||etges@unisc.br1982-67451414-7106opendoar:2021-01-08T19:43:05Redes (Santa Cruz do Sul. Online) - Universidade de Santa Cruz do Sul (UNISC)false |
dc.title.none.fl_str_mv |
There is nothing so bad that it can not work: a Bayesian analysis of poverty No hay nada tan ruim que no puede piorar: un análisis Bayesiana de la pobreza Não há nada tão ruim que não possa piorar: uma análise bayesiana da pobreza |
title |
There is nothing so bad that it can not work: a Bayesian analysis of poverty |
spellingShingle |
There is nothing so bad that it can not work: a Bayesian analysis of poverty Costa, Rodolfo Ferreira Ribeiro da Pobreza. Rede Bayesiana. Municípios. Poverty. Network Bayesian. Municipals. La pobreza. Red Bayesiana. Municipios. |
title_short |
There is nothing so bad that it can not work: a Bayesian analysis of poverty |
title_full |
There is nothing so bad that it can not work: a Bayesian analysis of poverty |
title_fullStr |
There is nothing so bad that it can not work: a Bayesian analysis of poverty |
title_full_unstemmed |
There is nothing so bad that it can not work: a Bayesian analysis of poverty |
title_sort |
There is nothing so bad that it can not work: a Bayesian analysis of poverty |
author |
Costa, Rodolfo Ferreira Ribeiro da |
author_facet |
Costa, Rodolfo Ferreira Ribeiro da |
author_role |
author |
dc.contributor.author.fl_str_mv |
Costa, Rodolfo Ferreira Ribeiro da |
dc.subject.por.fl_str_mv |
Pobreza. Rede Bayesiana. Municípios. Poverty. Network Bayesian. Municipals. La pobreza. Red Bayesiana. Municipios. |
topic |
Pobreza. Rede Bayesiana. Municípios. Poverty. Network Bayesian. Municipals. La pobreza. Red Bayesiana. Municipios. |
description |
This article aims to understand the relationships between different forms of poverty and, thus, to verify if a specific type of deprivation inhibits the individual's ability to overcome other forms of deprivation. An approach used to understand the mechanisms that govern how the relations between the levels of poverty refer to the Bayesian network. The data used refer to information on income, health, education and housing for 5,565 Brazilian municipalities between 1970 and 2010, being a source of information provided by the Brazilian Institute of Geography and Statistics. The results highlighted the existence of relations between the analyzed aspects of poverty. Direct influences of all deprivations on health conditions were observed, indicating that precarious health conditions usually arise in environments where other types of diseases arise. The education indicator reflects information on monetary deprivation, and this relationship is positive. Finally, monetary shortages are also responsible for limiting access to decent housing and a healthier living condition. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-11-27 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://online.unisc.br/seer/index.php/redes/article/view/12685 10.17058/redes.v25i4.12685 |
url |
https://online.unisc.br/seer/index.php/redes/article/view/12685 |
identifier_str_mv |
10.17058/redes.v25i4.12685 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://online.unisc.br/seer/index.php/redes/article/view/12685/pdf |
dc.rights.driver.fl_str_mv |
Copyright (c) 2020 Redes info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2020 Redes |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Edunisc - Universidade de Santa Cruz do Sul |
publisher.none.fl_str_mv |
Edunisc - Universidade de Santa Cruz do Sul |
dc.source.none.fl_str_mv |
Redes ; Vol. 25 (2020): Edição Especial; 1933-1952 Redes; Vol. 25 (2020): Edição Especial; 1933-1952 Redes; Vol. 25 (2020): Edição Especial; 1933-1952 Redes; v. 25 (2020): Edição Especial; 1933-1952 1982-6745 reponame:Redes (Santa Cruz do Sul. Online) instname:Universidade de Santa Cruz do Sul (UNISC) instacron:UNISC |
instname_str |
Universidade de Santa Cruz do Sul (UNISC) |
instacron_str |
UNISC |
institution |
UNISC |
reponame_str |
Redes (Santa Cruz do Sul. Online) |
collection |
Redes (Santa Cruz do Sul. Online) |
repository.name.fl_str_mv |
Redes (Santa Cruz do Sul. Online) - Universidade de Santa Cruz do Sul (UNISC) |
repository.mail.fl_str_mv |
redes_unisc_maff@terra.com.br||etges@unisc.br |
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1800218772619919360 |