Thanks to all who participated in this remarkable event! We had more than 150 registrants from 35 colleges and universities and several non-profits, mission-driven organizations, and for-profits who came together to analyze data and help build tools for ongoing analysis and action!
Participating organizations include Agnes Scott, Augsburg, Bard, Cal Poly Pomona, Century, Clark, Colgate, College of William and Mary, Colorado State, Cornell, Denison, Enlightened Pathways, Epic, Florida Atlantic, Indeed, Lewis, Macalester, Michigan State University, Mt. Holyoke, Northeastern, Northwestern, NYU, Pitzer, Portland Community College, Prison Fellowship, Rochester, Seattle University, Simpson, Smith, Southwestern, University of California, Los Angeles, University of California, San Diego, University of Michigan, University of Nebraska, Lincoln, University of Wisconsin, USC, Vanderbilt, Wartburg, and Williams!
6:00 pm, Friday, November 4 – 5:00 pm, Sunday, November 6, 2022 (VIRTUAL EVENT)
QSIDE is thrilled to announce the 2022 Datathon4Justice! Details are below.
Working hours for Datathon4Justice (all times are ET US):
Friday, November 4
- 6:00 p.m. – 6:50 p.m.: Welcome, introductions, and opening plenary
- SToPA Research Lab Friday, 6:10 p.m. – 6:30 p.m. ET, Drs. Ariana Mendible and Manuch Aminian
- JUSTFAIR Research Lab, 6:30 p.m. – 6:50 p.m. ET, Dr. Chad Topaz
- 7:00 p.m. – 9:00 p.m.: Initial team meetings, defining research questions, explaining work processes, and creating/forming working teams
- Outputs: Please post your research question(s) in the Slack channel.
Saturday, November 5
- 10:00 a.m. – 10:30 a.m.:
- Marina Siqueira, JUSTFAIR Illinois research at Northwestern University, 10:10 a.m. – 10:25 a.m. ET
- Clarissa Ache Cabello, SToPA research, Durham, North Carolina at Duke University, 10:25 a.m. – 10:40 a.m. ET
- 10:40 a.m. – 1:30 p.m.: Research team work
- 1:30 p.m. – 2:30 p.m.: Break, optional lunch meeting to confer with members of other teams.
- 2:30 p.m. – 5:00 p.m.: Research team work
- 5:00 p.m. – 6:00 p.m.: Report out from each team on their progress, approximately 10 minutes each.
- Outputs: Please update the Slack channel with major outputs from your day.
Sunday, November 6
- 10:00 a.m. – 10:30 a.m.: Welcome, final plenary
- STAMP Research Lab, Diana Estrada Alamo and Geri Dimas, 10:10 a.m. – 10:25 a.m. ET
- JUSTFAIR Ohio Accelerator project, Ronald Wells, 10:25 a.m. – 10:45 a.m. ET
- 10:45 a.m. – 1:30 p.m: Research team work
- 1:30 p.m. – 2:00 p.m.: Break, optional lunch meeting to confer with members of other teams.
- 2:00 p.m. – 3:30 p.m.: Research team work, prepare for final report out.
- 3:30 p.m. – 5:00 p.m: Final report out and closing remarks.
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.
Datasets
The theme for the 2022 Datathon4Justice is criminal justice. We have identified two datasets for the Datathon4Justice, which we’ll describe below.
Small Town Police Accountability
Teams will be able to work on previously collected and cleaned data from either Williamstown, MA, or Durham, NC, or to work on procuring and cleaning data from Kenosha, WI, Troy, NY, and/or Rockford, IL or Joliet, IL.
JUSTFAIR: A 50-state strategy
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. Data have been, or are being collected through the research lab in nine states: Montana, Illinois, Minnesota, Michigan, North Carolina, Virginia, New York, Pennsylvania, and Wisconsin. Teams can choose to continue collecting these data, or can use data that is previously collected to analyze.
Datathon4Justice 2022 Projects
JUSTFAIR
The JUdicial Sentencing for Transparency for Fairness in Archived, Inferred, Records (JUSTFAIR) is a project focused on creating greater transparency for the sentencing practices of judges in the federal and state judiciaries. The QSIDE JUSTFAIR research lab currently has projects at various stages of sophistication in 14 states (Alabama, Colorado, Illinois, Maryland, Michigan, Minnesota, Montana, New Jersey, New York, North Carolina, Pennsylvania, Virginia, Washington, and Wisconsin) and at the federal level. We have identified four types of projects that teams could participate in for the JUSTFAIR project, outlined below.
- Project 1: Finding, procuring, and cleaning data from new states.
We are currently actively working on finding and collecting data in 14 states. If a state that you care about or are interested in is *not* in the list above, or if you simply prefer to be part of a team investigating a new state from the ground up, this is a good project for you. - Project 2: Building a metadata standard for court structures.
The research lab has been collecting metadata about the structure of the courts in a number of states. These data need to be reviewed vis a vis one another and a metadata standard needs to be developed to describe the structure of the courts in all 50 states. - Project 3: Munging existing data.
The JUSTFAIR research lab has been collecting data over the course of the past year. We have three states with data that are in a state where they can be analyzed: Illinois, Minnesota, and Montana. Teams that want to interrogate an existing dataset can use these data as a starting point. - Project 4: Building the JUSTFAIR toolkit.
As we build our individual pieces of the JUSTFAIR system, we want to begin abstracting out the work done by each group into a toolkit of sorts that can be used across teams working on different states.
SToPA
The Small Town Police Accountability (SToPA) research lab is working on analyzing police records in small towns to map out policing activities and to identify potential biased policing practices.
- Project 1: Finding, procuring, and cleaning data from new towns.
Unlike judicial sentencing data, police records data are often not readily available in public portals. That being said, there may be ways to find and scrape data from new small towns, or to begin the process of requesting data from a town that holds relevance to you and/or your team. - Project 2: Munging existing data.
We currently have data from Williamstown, MA, and from Durham, NC. If you are interested in exploring these data further, you are welcome to analyze these data. - Project 3: Building the SToPA toolkit.
The long-term plan for the SToPA lab is to build out a toolkit that will help activists and data scientists in small towns find, procure, clean, analyze, and leverage data to create more equitable policing practices and outcomes. We have significant resources in this project, and it would be immensely helpful to begin pulling them together and abstracting the principles into this toolkit.
STAMP Lab
The Stopping Trafficking And Modern-day Slavery Research Lab, sponsored by and in partnership with RedCompass Labs, is examining the space of human trafficking to identify mechanisms to find and stop these behaviors, which disproportionately impact women and minoritized persons, both in the U.S. and around the globe.STAMP Lab Project: Scale and scope of U.S. Trafficking
Very little valid, reliable data exists to identify either the scale and scape or the loci of activity for human trafficking activities in the United States. This project will begin to ideate a way to investigate and begin to answer this question.