Publications

Education Data Done Right

Education Data Done Right
New book covering the missing elements critical to success in building data capacity in education agencies. Authored by 3 data analysts with expertise in public education agencies.

How to Take Back the Budget

How to Take Back the Budget
New guide to help communities review and change the police budget in their city or county. Provides practical steps to quickly translate budget jargon into real world information.

Publication from Community Resource Hub: Cops Don’t Stop Violence

Publication from Community Resource Hub: Cops Don’t Stop Violence
New co-authored resource critiquing data and narratives used to justify increased police spending, problems with crime stats and studies, and evidence-based strategies to stop violence.

Prison Gerrymandering on Reveal

Prison Gerrymandering on Reveal
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.

Policing the American University

Policing the American University
New report combining data from the FBI's Uniform Crime Report and the U.S. Department of Education to examine how common campus police departments are, how many people they employ, and what kind of arrests they make.

Readings in Ethical Data Science

Readings in Ethical Data Science
Readings on data analysis, data science, and artificial intelligence. Intended to spark new ideas and prompt critical thinking about organizations' data system design.

Effect of English Proficiency Classification on Student Outcomes: Evidence from Wisconsin

Effect of English Proficiency Classification on Student Outcomes: Evidence from Wisconsin
Article examines English Language Learner reclassification policies using a regression discontinuity framework to show that being reclassified as fully English proficient has positive effects for students' educational outcomes.

Building an Accurate Statewide Dropout Early Warning System in Wisconsin

Building an Accurate Statewide Dropout Early Warning System in Wisconsin
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.

Delivery of State-provided Predictive Analytics to Schools: Wisconsin’s DEWS and the Proposed EWIMS Dashboard

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).

School Boards and the Democratic Promise

School Boards and the Democratic Promise
Examines the degree of democratic control communities exercise over school boards through elections, combining election results for Wisconsin school districts with administrative records on local conditions.