Data on a sample of 100 Defensive Asylum Cases as they progress through the immigration court system.
Data Description: This dataset is a sample of 100 cases that have processed through the United States immigration court system seeking defensive asylum in the last ~ 10 years (2010-2019). This dataset covers information about the case and their time in different parts of the immigration court process through data about their case proceedings, scheudled hearings and the judges that have heard their cases. Some variables that are of particular intrested may be the DEC_CODE which represents the outcome of the case.
Questions/Related Tasks: What is the relationship between case decision and Nationality of the asylum seeker? What is the split in the Nationality? How long do cases take to complete the entire legal process? What is the number of workload/cases per judge?
Attributes most interesting to me: For me this is realted to my PhD research, so I am most intrested in the actual court process, how the cases proceed. Therefore the attributes that mean the most to me are the proceedingIDs(categorical) and the scheduleIDS (Categorical) and their associated dates(some are ordered dates others are quantitative) to see how they progress based on different characteristics such as nationality(categorical) and gender(categorical).