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Anna Haensch, Ariana Mendible - Small Town Police Accountability A Data Science Toolkit | SciPy 2023
Small town police accountability requires powerful tools. Learn how a data science team used Altair and machine learning to analyze imperfect data, make it usable, and identify patterns in police behavior.
- The talk highlights the importance of small town police accountability and the challenges in accessing and analyzing small town police data.
- The team used Altair to create a map showing filtering for each different officer, providing spatial patterns on where someone might be policing.
- The data available is often imperfect and missing, requiring reorganization and cleaning to make it usable.
- The Freedom of Information Act (FOIA) is a federal law that guarantees access to data, but submitting a FOIA request can be a lengthy and challenging process.
- The team used supervised machine learning algorithms to analyze the data and identify patterns in police behavior.
- The project aims to create a reusable code repository so that other data scientists or researchers can replicate the work on their own towns.
- The talk emphasizes the importance of connecting with communities and involving them in the work to make it impactful.
- The team wants to create a toolkit that allows anyone, including non-experts, to access and analyze policing data.
- Currently, the toolkit is available on a GitHub repository.
- The team encourages listeners to get involved and help promote change in their own towns.