Understanding the punitive spatial pattern in Brazil and São Paulo's prison McDonald

Detalhes bibliográficos
Autor(a) principal: Israel, Vinicius Pinheiro
Data de Publicação: 2023
Outros Autores: Paez, Marina Silva, Souza, Rebecca de Oliveira
Tipo de documento: preprint
Idioma: por
Título da fonte: SciELO Preprints
Texto Completo: https://preprints.scielo.org/index.php/scielo/preprint/view/6550
Resumo: The study of the spatial distribution of Brazilian prisons is one of the ways to understand the mass incarceration phenomenon. By using the Penitentiary Census of the Ministry of Justice, 2014, we analyse punitive patterns around the country. The results show the existence of five punitive spatial clusters: two of which are prominent, in the Southeast region and the other centred in the Northeast region (between the states of Pernambuco and Ceará). Methodologically, we structured models for point patterns considering the geographic location (latitude and longitude), in addition, we introduced into the models the prisons’ characteristics, such as occupancy rate and prison capacity. As a result, it is possible to observe a statistical regularity that shows a differential punitive pattern in the São Paulo state. There are many units with large capacities, higher than other states' prisons. The statistical inference was made under the Bayesian paradigm, which allows characterizing the uncertainties of the models in a probabilistic way and circumventing the problems of scientific decision-making based on the p-value. The present paper is the first one to identify punitive groups in Brazil and to statistically verify the existence of different spatial patterns in São Paulo’s prisons, contributing to the debate on punitive policies in the country.
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spelling Understanding the punitive spatial pattern in Brazil and São Paulo's prison McDonaldCompreendendo o padrão espacial punitivo no Brasil e o McDonald prisional de São Paulopuniçãoviolênciametodologiaprisãoestatística espacialpunishmentviolencemethodologyprisonspatial patternThe study of the spatial distribution of Brazilian prisons is one of the ways to understand the mass incarceration phenomenon. By using the Penitentiary Census of the Ministry of Justice, 2014, we analyse punitive patterns around the country. The results show the existence of five punitive spatial clusters: two of which are prominent, in the Southeast region and the other centred in the Northeast region (between the states of Pernambuco and Ceará). Methodologically, we structured models for point patterns considering the geographic location (latitude and longitude), in addition, we introduced into the models the prisons’ characteristics, such as occupancy rate and prison capacity. As a result, it is possible to observe a statistical regularity that shows a differential punitive pattern in the São Paulo state. There are many units with large capacities, higher than other states' prisons. The statistical inference was made under the Bayesian paradigm, which allows characterizing the uncertainties of the models in a probabilistic way and circumventing the problems of scientific decision-making based on the p-value. The present paper is the first one to identify punitive groups in Brazil and to statistically verify the existence of different spatial patterns in São Paulo’s prisons, contributing to the debate on punitive policies in the country.Uma das maneiras de compreender o fenômeno do encarceramento em massa no Brasil é através do estudo da distribuição das unidades prisionais em seu território. A partir do Censo Penitenciário realizado pelo Ministério da Justiça, em 2014, foi feita uma análise de estatística espacial para identificar os padrões punitivos no país. Os resultados mostram a existência de cinco agrupamentos punitivos, sendo dois principais: um na região sudeste, centrado no estado de São Paulo, e outro no Nordeste, com centro entre os estados de Pernambuco e Ceará. Metodologicamente, modelos estruturados para padrões de pontos foram expandidos introduzindo características do fenômeno, além das geográficas (latitude e longitude), tais como: taxa de ocupação e capacidade dos presídios. Como resultado, foi possível observar uma regularidade estatística que mostra um padrão punitivo diferenciado em São Paulo. Observa-se grande quantidade de unidades com capacidade superior à de seus pares na região. A inferência estatística foi feita sob o paradigma bayesiano que permite caracterizar as incertezas dos modelos de forma probabilística e contornar os problemas de tomada de decisão científica baseada no p-valor. Este trabalho é o primeiro a identificar os agrupamentos punitivos no país e verificar estatisticamente a existência de padrões diferenciados nas unidades prisionais de São Paulo, contribuindo para o debate sobre o punitivismo no Brasil.SciELO PreprintsSciELO PreprintsSciELO Preprints2023-10-10info:eu-repo/semantics/preprintinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://preprints.scielo.org/index.php/scielo/preprint/view/655010.1590/SciELOPreprints.6550porhttps://preprints.scielo.org/index.php/scielo/article/view/6550/12541Copyright (c) 2023 Vinicius Pinheiro Israel, Marina Silva Paez, Rebecca de Oliveira Souzahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessIsrael, Vinicius PinheiroPaez, Marina SilvaSouza, Rebecca de Oliveirareponame:SciELO Preprintsinstname:Scientific Electronic Library Online (SCIELO)instacron:SCI2023-09-15T17:23:08Zoai:ops.preprints.scielo.org:preprint/6550Servidor de preprintshttps://preprints.scielo.org/index.php/scieloONGhttps://preprints.scielo.org/index.php/scielo/oaiscielo.submission@scielo.orgopendoar:2023-09-15T17:23:08SciELO Preprints - Scientific Electronic Library Online (SCIELO)false
dc.title.none.fl_str_mv Understanding the punitive spatial pattern in Brazil and São Paulo's prison McDonald
Compreendendo o padrão espacial punitivo no Brasil e o McDonald prisional de São Paulo
title Understanding the punitive spatial pattern in Brazil and São Paulo's prison McDonald
spellingShingle Understanding the punitive spatial pattern in Brazil and São Paulo's prison McDonald
Israel, Vinicius Pinheiro
punição
violência
metodologia
prisão
estatística espacial
punishment
violence
methodology
prison
spatial pattern
title_short Understanding the punitive spatial pattern in Brazil and São Paulo's prison McDonald
title_full Understanding the punitive spatial pattern in Brazil and São Paulo's prison McDonald
title_fullStr Understanding the punitive spatial pattern in Brazil and São Paulo's prison McDonald
title_full_unstemmed Understanding the punitive spatial pattern in Brazil and São Paulo's prison McDonald
title_sort Understanding the punitive spatial pattern in Brazil and São Paulo's prison McDonald
author Israel, Vinicius Pinheiro
author_facet Israel, Vinicius Pinheiro
Paez, Marina Silva
Souza, Rebecca de Oliveira
author_role author
author2 Paez, Marina Silva
Souza, Rebecca de Oliveira
author2_role author
author
dc.contributor.author.fl_str_mv Israel, Vinicius Pinheiro
Paez, Marina Silva
Souza, Rebecca de Oliveira
dc.subject.por.fl_str_mv punição
violência
metodologia
prisão
estatística espacial
punishment
violence
methodology
prison
spatial pattern
topic punição
violência
metodologia
prisão
estatística espacial
punishment
violence
methodology
prison
spatial pattern
description The study of the spatial distribution of Brazilian prisons is one of the ways to understand the mass incarceration phenomenon. By using the Penitentiary Census of the Ministry of Justice, 2014, we analyse punitive patterns around the country. The results show the existence of five punitive spatial clusters: two of which are prominent, in the Southeast region and the other centred in the Northeast region (between the states of Pernambuco and Ceará). Methodologically, we structured models for point patterns considering the geographic location (latitude and longitude), in addition, we introduced into the models the prisons’ characteristics, such as occupancy rate and prison capacity. As a result, it is possible to observe a statistical regularity that shows a differential punitive pattern in the São Paulo state. There are many units with large capacities, higher than other states' prisons. The statistical inference was made under the Bayesian paradigm, which allows characterizing the uncertainties of the models in a probabilistic way and circumventing the problems of scientific decision-making based on the p-value. The present paper is the first one to identify punitive groups in Brazil and to statistically verify the existence of different spatial patterns in São Paulo’s prisons, contributing to the debate on punitive policies in the country.
publishDate 2023
dc.date.none.fl_str_mv 2023-10-10
dc.type.driver.fl_str_mv info:eu-repo/semantics/preprint
info:eu-repo/semantics/publishedVersion
format preprint
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://preprints.scielo.org/index.php/scielo/preprint/view/6550
10.1590/SciELOPreprints.6550
url https://preprints.scielo.org/index.php/scielo/preprint/view/6550
identifier_str_mv 10.1590/SciELOPreprints.6550
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://preprints.scielo.org/index.php/scielo/article/view/6550/12541
dc.rights.driver.fl_str_mv Copyright (c) 2023 Vinicius Pinheiro Israel, Marina Silva Paez, Rebecca de Oliveira Souza
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 Vinicius Pinheiro Israel, Marina Silva Paez, Rebecca de Oliveira Souza
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv SciELO Preprints
SciELO Preprints
SciELO Preprints
publisher.none.fl_str_mv SciELO Preprints
SciELO Preprints
SciELO Preprints
dc.source.none.fl_str_mv reponame:SciELO Preprints
instname:Scientific Electronic Library Online (SCIELO)
instacron:SCI
instname_str Scientific Electronic Library Online (SCIELO)
instacron_str SCI
institution SCI
reponame_str SciELO Preprints
collection SciELO Preprints
repository.name.fl_str_mv SciELO Preprints - Scientific Electronic Library Online (SCIELO)
repository.mail.fl_str_mv scielo.submission@scielo.org
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