March and April 2021: JAT datathon
For this year datathon, we partnered with the Judge Accountability Table (JAT) - a coalition of organizations working toward a shared mission of holding judicial candidates and judges accountable to our community’s vision of justice, and engaged R enthusiasts to explore judicial patterns in Philadelphia courts.
In March Kickoff meetup, our partner JAT representative Rebecca Hufstader and R-Ladies Philly co-organizer Karla Fettich oriented us about the basic structure of courts in Philadelphia, the mission of project and overview of datasets.
Have you heard? Our 2021 #RLadies datathon kicks off on March 17th! Join us to learn/practice R skills, collaborate, have fun working with real data, and help our community partner @judgeyourjudges better understand judicial patterns through data! https://t.co/VTtzhE5irE— R-Ladies Philly (@RLadiesPhilly) February 28, 2021
About 30 Philly’s R enthusiasts formed into three teams and started to explore this rich, messy data in different perspectives: 1) data visualization, 2) defining and quantifying judge “harshness” and 3) understanding systemic trends in the courts. Groups worked together over Slack and GitHub, meeting weekly virtually. After a productive month, all datathon participants and our JAT partners reconvened virtually for the conclusion meetup on April 28th , to present and discuss findings:
Team 1 - Data Visualization
Sybil Andrieux, Roy Aizen, June Choe, Kulbir Kaur, Alison Moss and Alice Walsh
The team created an interactive dashboard to visualize judicial patterns at various levels of abstraction, including sentencing patterns by judge and by race, bail increases and decreases by judge, bail patterns by season and so on. This team found that
Team 2 - Judge “harshness”
Russ Lavery, Shenee, Vera, Jessie Pluto, May Sophia, Alex Lesicko Adam Schlesinger, Jayeon Kim, Eamon Caddigan, Spandana Makeneni, Shanti Agung
The team focused on quantifying judge “harshness” through two general approaches – visualization and random coefficient modeling. They explored judge “harshness” through length of prison sentences and frequency of sentencing defendants to prison rather than probation, and found that Judge Coyle, Bronson and Cunningham tends to order longer than average sentences, and the first two are also more likely to sentence defendants to prison. Their modeling approach based on confinement days outcome also confirms that some judges are harsher than others, after taking defendant demographic information and offense grades into consideration.
Team 3 - Systemic Trends
Addison Larson, Alice Walsh, Christine Carmody, Chun Su, Hector Maldonado-Reis, Jake Riley, Jasmine Pham, Jessie Pluto, Katrina Gutierrez, Khushbu Patel, Meredith Lee, Mitch Maltenfort, Nathan Kendsersky, Trang Le, Zhenya
One of the questions this team looked into is how things have changed in the courts since District Attorney Larry Krasner took office in January 2018. By comparing various metrics 2 years prior and after his election, the team found that there was progress in Krasner’s first two years although there is still room for improvement. For example, black defendants tend to have lower rates of ROR after he takes office. Minimum bail set for first-degree felonies is more equitable between races since 2018, but inequity exists among first-degree misdemeanors. Bail policy around retail theft, DUI-first offense, and prostitution decrease after his 2018 bail reform, but bail policy becomes more harsh for strangulation and aggravated indecent assaults.
With active Q&A sessions at the end of amazing presentations, we concluded our community data project working with JAT this year by written-up reports (team 1, 2, 3) . Our participants also expressed they learned a lot, and highly appreciated the teamwork through the whole project.
We sincerely thank JAT for providing us valuable data and background resource, and participants for donating their time and expertise to a good cause.
This post was authored by Chun Su. For more information contact firstname.lastname@example.org