Analyzing the impact of particular judges on the US asylum process
In U.S. immigration courts, are certain judges and locations more likely to approve or deny claims of asylum?
logistic regression odds ratio/log odds ratio
Readings and links
- They fled danger at home to make a high-stakes bet on U.S. immigration courts, from Reuters
- EOIR data
- Incomplete and Garbled Immigration Court Data Suggest Lack of Commitment to Accuracy, from the Transactional Records Access Clearinghouse (TRAC)
- Short methodology description
In U.S. immigration courts, are certain judges and locations more likely to approve or deny claims of asylum? While logistic regression is an excellent choice in this situation, the dataset requires a hundred and one editorial decisions be made along the way. And in the end: even though it's an official government data dump, is the dataset even reliable enough for analysis?
Notebooks, Assignments, and Walkthroughs
While the immigration court dataset is huge, we're only looking for a subset of asylum cases that we can compare to one another.
Using logistic regression on an extra-rough dataset to see if we can see how nationality and different judges affect a person's chances of being granted asylum to the USA.