Project Resolve: Reducing Recidivism using Advanced Analytics
Description
The United States has an institutional prison system built on the principle of retributive justice combined with racial prejudice that despite countless efforts for reform currently holds 2.3 million individuals, primarily minorities, behind bars. This institution has remained largely unchanged, meanwhile 83.4% of those who enter the system will return within one decade and it currently costs nearly $39 billion each year (Alper 4). Because the prison institution consistently fails to address the core root of crime, there is a great need to reconsider the approach taken towards those who break our nation’s laws with the dual purpose of enhancing freedom and reducing crime. This paper outlines an original theoretical framework being implemented by Project Resolve that can help to identify and implement solutions for our prison system without reliance on political, institutional, or societal approval. The method focuses on three core goals, the first is to connect as much of the data surrounding prisoners and the formerly incarcerated as possible, the second is to use modern analytic approaches to analyze and propose superior solutions for rehabilitation, the third is shifting focus to public interest technology both inside prisons and the parole process. The combination of these objectives has the potential to reduce recidivism to significantly, deter criminals before initial offense, and to implement a truly equitable prison institution.
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2020-05
Agent
- Author (aut): Gilchrist, Troy
- Thesis director: Martin, Thomas
- Committee member: Wenrick, Lukas
- Contributor (ctb): Department of Economics
- Contributor (ctb): Barrett, The Honors College