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Modeling a Racial Caste System: Algorithmic Exposure of Virginia’s Jim Crow Laws is a groundbreaking project aimed at making the extensive and complex legal history of Jim Crow laws in Virginia more accessible and comprehensible through advanced machine learning techniques. The project seeks to return critical public documents to the public, enabling new research into the era of Jim Crow (1865-1968) and uncovering the legal mechanisms underpinning white supremacy in Virginia.

Guided by principles of inclusive collaboration, transparency, and open access, this project builds on the University of North Carolina’s model for text analysis to improve and expand the field of machine-led research. The project's vision includes opening the full corpus of Virginia's Jim Crow laws to algorithms and humanistic research, allowing for innovative exploration and understanding of this significant period in history. This project will reveal the full extent of Jim Crow legislation, enabling comparative research and opening discussions on dismantling its legacies. It aims to make Virginia’s laws from 1865 to 1968 searchable as a comprehensive corpus, overcoming the limitations of current print sources and fragmented digital access. By exposing the legal architecture of racial discrimination, the project will contribute to a deeper understanding of historical and ongoing racial inequities and support new research into the legal language and strategies of Jim Crow laws.


Can Computers Find Racist Laws?

Project Overview

Review the scope of the project and the steps taken to create a corpus of Virginia's Jim Crow-era laws.

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Why Algorithms?

Learn how algorithms enhance our ability to analyze Virginia’s Jim Crow-era laws by automating tasks such as sorting, classifying, and extracting information from large volumes of text

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Bibliography

Explore the bibliography to see the key references that informed our analysis of Virginia’s Jim Crow-era laws.

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Project Team

The project team behind the analysis of Virginia’s Jim Crow-era laws.

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