5:00 pm, Friday, october 22 – 5:00 pm, Sunday, October 24, 2021 (VIRTUAL EVENT)

QSIDE is pleased to announce our inaugural Datathon4Justice Workshop. The Datathon4Justice will bring together multiple teams of seasoned and emerging data scientists, social scientists, and activists to work on a pre-scrubbed dataset to ask compelling questions, analyze data, and begin to use data to address real-world injustice, affect policy, and/or sway public opinion. Registration is now open!

Goals of the Datathon4Justice

The Datathon4Justice is a weekend-long commitment where students, professional researchers, and activists will come together in small teams to collaboratively examine a dataset. The goals are to share expertise, learn from one another, apply collective knowledge and analysis to a real-world criminal justice dataset, and leave with both new data science social justice skills and an enhanced understanding of how to work in interdisciplinary teams on real-world social justice problems.

Team Composition

Individuals of a broad range of skill levels and disciplinary interests are encouraged to participate. Teams will be mixed, to the greatest degree possible, of data scientists/statisticians/mathematicians, social scientists, humanists, and activists who are at varying levels of their research journeys.

Major Deadlines

  • October 8th, 2021: Registration Closes
  • October 22 – 24: Datathon4Justice (online/virtual event)


The theme for the 2021 Datathon4Justice is criminal justice. We have identified two datasets for the Datathon4Justice, which we’ll describe below.

Williamstown, MA Police Reports

Williamstown is a small town of just under 8000 residents in western Massachusetts. The Police Department in Williamstown, MA has been accused of a series of ethical violations, including sexual harassment, racial harassment of citizens and employees, and having a Hitler poster displayed in the staff room of the precinct for several years. QSIDE has obtained all of the police records for several years. Teams working with this dataset will look for any patterns or findings that indicate if and to what extent these biased behaviors were manifest in policing practices.

JUSTFAIR: Minnesota

The JUdicial System Transparency for Fairness through Archived/Inferred Records (JUSTFAIR) project initially brought together all records for federal courts to identify which judges were sentencing in the most biased ways based on race/ethnicity on the federal bench. The JUSTFAIR project is now moving into all 50 states, and we have secured and cleaned all of the data for the state of Minnesota. Teams working with these data will ask and answer questions about the equitable sentencing of defendants in the state of Minnesota.