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JUSTFAIR: Judicial System Transparency through Federal Archive Inferred Records.
Ciocanel, Maria-Veronica; Topaz, Chad M; Santorella, Rebecca; Sen, Shilad; Smith, Christian Michael; Hufstetler, Adam.
Afiliação
  • Ciocanel MV; Department of Mathematics, Duke University, Durham, NC, United States of America.
  • Topaz CM; Institute for the Quantitative Study of Inclusion, Diversity, and Equity, Williamstown, MA, United States of America.
  • Santorella R; Department of Mathematics and Statistics, Williams College, Williamstown, MA, United States of America.
  • Sen S; Division of Applied Mathematics, Brown University, Providence, RI, United States of America.
  • Smith CM; Department of Mathematics, Statistics, and Computer Science, Macalester College, St. Paul, MN, United States of America.
  • Hufstetler A; Department of Sociology, Berea College, Berea, KY, United States of America.
PLoS One ; 15(10): e0241381, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33104748
ABSTRACT
In the United States, the public has a constitutional right to access criminal trial proceedings. In practice, it can be difficult or impossible for the public to exercise this right. We present JUSTFAIR Judicial System Transparency through Federal Archive Inferred Records, a database of criminal sentencing decisions made in federal district courts. We have compiled this data set from public sources including the United States Sentencing Commission, the Federal Judicial Center, the Public Access to Court Electronic Records system, and Wikipedia. With nearly 600,000 records from the years 2001-2018, JUSTFAIR is the first large scale, free, public database that links information about defendants and their demographic characteristics with information about their federal crimes, their sentences, and, crucially, the identity of the sentencing judge.
Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Tipo de estudo: Estudo prognóstico Idioma: Inglês Revista: PLoS One Assunto da revista: Ciência / Medicina Ano de publicação: 2020 Tipo de documento: Artigo País de afiliação: Estados Unidos

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Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Tipo de estudo: Estudo prognóstico Idioma: Inglês Revista: PLoS One Assunto da revista: Ciência / Medicina Ano de publicação: 2020 Tipo de documento: Artigo País de afiliação: Estados Unidos