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Recidivism Algorithm Policy Memo

An argument for using algorithms appropriately to predict recidivism

Project at the University of Pennsylvania, Fall 2022

This sample memo was practice for communicating heavy data-based reasoning in plain language for a non-technical audience. It required advocating for using algorithms to estimate recidivism of applicants to an ex-prisoner job program, a very sensitive topic that balances societal and individual impact.

Link to memo

The modeling and cost-benefit analysis is based on cleaned data from Public Policy Analytics textbook, Chapter 7 and similar job training programs.

Tools Used:

  • R Tidyverse Packages and Markdown for data wrangling, modeling, and cost benefit analysis
  • Policy research
  • Concise, non-technical communication of technical concepts and conclusions

Hi, I’m Ben.

I’m a data analyst and visualization specialist with a designer background.

I started in graphics and communication design to learn essential tools for problem solving, and I was fortunate to work on many projects that solved communication challenges online and in 3D space. Now I'm taking these user-focused design skills and applying them to today's civic issues through geospatial data analysis, data vis, and front-end development tools.

I love working with other specialists to learn their processes and create useful insights, engaging sites, and accessible experiences. If I can be of service to your own projects, please send me a message!

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