Session Laws Passed by the North Carolina General Assembly During 1866/67-1967, Identified by Machine Learning as Laws Likely to be Jim Crow Laws (XML format) version 1 Public Deposited

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Last modified date
  • August 31, 2020
Creator
  • Bruckner, Lorin
    • Affiliation: University of North Carolina at Chapel Hill. University Libraries
  • Byers, Neil
    • Affiliation: University of North Carolina at Chapel Hill. University Libraries
  • Dalwadi, Rucha
    • Affiliation: University of North Carolina at Chapel Hill. University Libraries
  • Henley, Amanda
  • Jansen, Matt
  • Thomas, Kimber
    • Affiliation: University of North Carolina at Chapel Hill. University Libraries
  • Sturkey, William
    • Affiliation: College of Arts and Sciences, Department of History
Contributor
  • Estorino, María R.
  • Eck, Montana
    • Affiliation: University of North Carolina at Chapel Hill. University Libraries
  • Long, Julia
    • Affiliation: University of North Carolina at Chapel Hill. University Libraries
  • Mullikin, Ashley
    • Affiliation: University of North Carolina at Chapel Hill. University Libraries
  • Nallaparaju, Siri
    • Affiliation: University of North Carolina at Chapel Hill. University Libraries
  • Oyeleke, Tim
    • Affiliation: University of North Carolina at Chapel Hill. University Libraries
  • Patton, Jenna
    • Affiliation: University of North Carolina at Chapel Hill. University Libraries
Abstract
  • This corpus was created for a text analysis project called On the Books: Jim Crow and Algorithms of Resistance. On the Books focused specifically on the laws passed during the Jim Crow Era, which is defined for this project as the period between Reconstruction and the Civil Rights Movement (1866-1967). In addition to creating the corpus, the project also used machine learning to identify discoverable North Carolina segregation statutes during the Jim Crow era. This corpus contains a single XML file containing all of the laws identified as a likely Jim Crow law. This work is licensed under a Creative Commons Attribution non-commercial 3.0 license: https://creativecommons.org/licenses/by-nc/3.0/
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  • Text
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  • Dataset
Rights statement
  • In Copyright
License
  • Attribution 3.0 United States
Funder
  • Funded by the Andrew W. Mellon Foundation as part of the first cohort for Collections as Data: Part to Whole.
Project director
Researcher
  • Carrier, Sarah
  • Kelber, Nathan
  • Sturkey, William
    • Affiliation: College of Arts and Sciences, Department of History
  • Thomas, Kimber
    • Affiliation: University of North Carolina at Chapel Hill. University Libraries
Language
  • English
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