CourtLab.
Look beyond
the raw rate.
An interactive study of Seventh Circuit criminal appeals. The decisions, the comparisons, and the full analysis live in the application.
U.S. Court of AppealsSeventh CircuitThis seal identifies the court whose decisions this project studies. It is used for identification only. This is independent academic research, not affiliated with, endorsed by, or approved by the Seventh Circuit, the federal judiciary, or the United States.
Richard ZhuEmpirical legal research / 2024–2026
Different outcomes.
Different dockets.
When appellate outcomes vary across judges, how much reflects the judges—and how much reflects the cases they were given? My Northwestern thesis began with that question. CourtLab is where you can work through it.
Most of the visible spread follows the docket, not the judge.
Published opinions and routine dispositions behave very differently, and no two judges hear the same mix of them. Once posture, offense, and publication track are accounted for, the distance between judges narrows considerably.
The decisions, the estimates, and the caveats are all in the application.Keep the evidence
within reach.
Begin with decisions
Published and nonprecedential Seventh Circuit criminal decisions, extracted into a structured record that a reader can audit case by case.
Respect the panel
Each decision enters the model once. Its actual participating judges share the panel weight, so no judge carries a colleague’s case twice.
Compare with context
A Bayesian model accounts for posture, offense, and publication track before any two judges are placed side by side.
Keep uncertainty visible
Every estimate carries an interval, and the application lets readers change the comparison and watch how much it moves.
Modeled rates describe panel-associated differences after adjustment. They do not identify individual votes or causal effects.