Sentencing Data for January 6 Defendants with Judge Appointment Effects

Replication data supports research on judicial appointment effects on sentencing outcomes for defendants in the January 6 Capitol breach. The dataset was created by Ethan D. Boldt, Hayley Munir, Jason S. Byers, and Michael C. Gizzi for publication in Political Research Quarterly. It was last updated on March 16, 2026, on the Harvard Dataverse platform.

Use Cases

• Analyze the relationship between judge appointment method and sentencing severity based on the study's focus.
• Model sentencing outcomes for January 6 defendants based on judicial and case characteristics.
• Investigate potential disparities in judicial decision-making based on the described appointment effects.

Strengths

• Data is directly linked to a peer-reviewed publication in Political Research Quarterly.
• Last update recorded as March 16, 2026, indicating recent maintenance.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and sample data are unknown, which limits suitability assessment.

Provenance

Source

Harvard Dataverse

Collection Method

Replication data for an academic study; likely compiled from court records.

Time Range

Likely covers the period following the January 6, 2021, Capitol breach.

Freshness

Last updated 2026-03-16 22:21:21; freshness should be verified.

Geography

Likely focuses on United States federal courts.