Jared is proud to serve on the advisory board for the Urban Institute’s Education Data Explorer. If you use data from the U.S. Department of Education, you are going to love this new tool. The team at Urban Institute has taken the hodge-podge of flat files, build-a-table tools, and links to data sources on the ED homepage and...
Jared is thrilled to be one of five inaugural advisors for the Racial Equity Data Hub, an ambitious and existing new initiative led by the Tableau Foundation. From the website: Tableau Foundation is hosting the Racial Equity Data Hub to share insights from leading experts at the intersection of data and equity issues, and to inspire...
Jared is happy to serve as an advisor for the Geospatial Neighborhood Analysis Package (geosnap) initiative. Civilytics often works with groups that want to understand data for their neighborhood, defined at a local level, not by how the Census has divvied up tracts. One of geosnap's important goals is to make modeling bespoke neighborhoods and...
Podcast from the national radio show Reveal featuring analysis from Civilytics on prison gerrymandering in Wisconsin, which distorts communities' political representation because of residential segregation and disparities in incarceration.
Readings on data analysis, data science, and artificial intelligence. Intended to spark new ideas and prompt critical thinking about organizations' data system design.
Civilytics won second prize (and learned a lot) in this competition focused on automating the combination of police data, census-level data, and other shapefiles for the Center for Policing Equity.
This data simulation package creates realistic synthetic data that allows users to collaborate across agencies without privacy concerns or the need for a data sharing agreement, while writing code that can then be translated back to the original data.
Civilytics provides R training ranging from single workshop introductions to R to advanced R training on spatial data analysis, web application development with Shiny, predictive analytics and more. The 'model and coach' approach is central to many of Civilytics' trainings.
This page archives one of the earliest R trainings put together by Jared. Since this project was completed in 2012 there have been many changes in R and a proliferation of wonderful open-access learning tools to learn R. These are provided here to document the history of this work, but we have more modern training...
Interactive equity-focused higher education admissions tool that distills dozens of measures of academic preparation into a single college readiness score that can be used to identify clusters of promising students by race/ethnicity and other characteristics.
Delivery of State-provided Predictive Analytics to Schools: Wisconsin’s DEWS and the Proposed EWIMS Dashboard
Situates the Wisconsin Dropout Early Warning System in the context of national models of predictive analytic systems in education, including a focus on the Early Warning Implementation Monitoring System (EWIMS).
The award-winning Wisconsin Dropout Early Warning System was co-developed with educators to ensure that the sophisticated enterprise scale machine-learning provides schools with a timely list of students who should be considered for additional support and attention.
Describes the Wisconsin Dropout Early Warning System (DEWS), a predictive model of student dropout risk for students in grades 6-9. Explains how DEWS' publicly available software modules can be applied to new data and outcomes.