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The criminal justice system has often relied upon the use of statistical evidence to support policy implications. Evidence based sentencing is a model that incorporates risk assessments to determine an offender’s future dangerousness. Once relegated for the most violent of crimes, states are now increasingly turning to the use of logarithms to determine recidivism and subsequently, an offender’s eligibility for parole or probation. Static factors such as race are often used in these logarithms, creating a discriminatory practice that can aggravate an offender’s assessment. These models have been consistently rejected by similarly progressive countries, international law, and most recently, the United States Supreme Court in Buck v. Davis. Incarceration rates in the United States have surged over the last few decades, and minorities are increasingly overrepresented. Sentencing needs to be based on the individual’s crime and their specific punitive and rehabilitative needs, not on whether a logarithm has yielded a high-risk result.