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CA Dept. of Justice OpenJustice Project
Modeling & Hypothesis Testing
Below, members of the Data Science Working Group have been charged with answering, via inferential statistics, some of the California Department of Justice’s inquiries around criminal justice. These more pointed inquiries were inspired by the OpenJustice project’s exploratory analyses at OpenJustice.org.
Responsible DSWG Members:
- Catherine Zhang
- John Huynh
- Saniya Jesupaul
- Holly Davis
- Brian Smith
- Jude Calvillo
Status, as of August 20, 2016:
- Prompts were verified by the CA DOJ’s OpenJustice team, and we’re now in regular contact.
- Prompt #1 pretty much complete (Anonymous Analyst) »
- Prompt #2 in draft stage (Catherine Z.) »
- New members, John Huynh and Saniya Jesupaul, are beginning to tackle Prompt #5 via linear models and diagnostics.
- Continuing to gather additional data/features for all predictive modeling prompts.
- Which counties/agencies arrest African American juveniles at a statistically significantly higher rate than that of other counties/agencies?
- Extending analysis to each ethnic group represented
- Drilling down to felonies vs. misdemeanors
For the same criminal offense, are particular ethnic juvenile groups more likely to be treated with harsher consequences by law enforcement?
Statewide, what contextual and ethnic factors best predict the arrest of juveniles for felonies?
Statewide, what contextual and ethnic factors best predict the arrest of juveniles for battery, specifically?
- For resource allocation prompt: ~. predictors to statewide crime rate (i.e. not necessarily optimization; just a first, exploratory step, probably via LM)