Abstract

This capstone project develops, critiques, and applies a Crime Harm Index (CHI) for the City of Rochester, New York, as an alternative to traditional crime measures that rely solely on raw counts. Rather than treating all offenses as equal “one crime = one unit,” the project weights crimes by the severity of harm they cause, using New York State sentencing guidelines as the core metric. Across four working papers, the project moves from conceptual foundations and limitations of harm-based metrics, to the construction of a Rochester-specific Crime Harm Index, and finally to a set of spatial regression models that link neighborhood disadvantage to crime harm. Together, these sections aim to show not only what a CHI can reveal about crime patterns, but also how and when it should be used in practice. Part One establishes the conceptual framework by defining a harm index and explaining why we might want to measure crime in terms of harm rather than frequency. It examines the Cambridge Crime Harm Index (CHI), the dominant paradigm for harm-based measurement, and explains how it employs national sentencing guidelines to translate offenses into "days of imprisonment" as a standardized unit of harm. The paper emphasizes the approach's virtues, including its cost-effectiveness, democratic basis in sentencing guidelines, and capacity to prioritize high-harm crimes that are frequently overlooked by traditional count-based metrics. It also briefly compares crime harm to other harm models, such as the drug harm and road harm indexes, which use health, financial, and community-level expenses to assess harm in their respective fields. This section discusses crucial concepts such as the three-pronged test (democracy, dependability, and cost) as a benchmark for determining if a damage index is applicable to real-world policy and enforcement. Part Two takes a step back and asks, "What are the limitations of using harm indexes, particularly when they are based on sentencing guidelines?" It analyzes how moral panics, public anxiety, and politics can drive sentencing policy, resulting in harm weights that do not always reflect the genuine social impact of an offense. This part also examines various methods of determining criminal severity, such as public opinion panels, victim surveys, and court records, and demonstrates how each introduces biases, ranging from media-influenced judgments to highly emotional victim answers. This section also discusses the issue of underreporting, pointing out that crimes like auto theft are routinely reported, whereas crimes like rape and sexual assault are significantly underreported. Finally, this section contends that, while harm indexes based on sentencing guidelines are imperfect, they remain a useful starting point. Part Three transitions from theory to implementation by creating a Crime Harm Index specifically for the City of Rochester. The Rochester CHI is built using crime data from 2023-2024, with New York State sentencing guidelines applied to 20 major crime types and harm scores calculated based on days of incarceration. Utilizing the same framework, the section also examines Rochester from 2009 to 2024, utilizing tables and visualizations to compare total crime counts and total crime harm over time. This enables the research to demonstrate how the picture changes when severity is taken into consideration, which crimes cause the most harm to the community, and how a harm-based lens indicates different priorities than typical count-based crime statistics. Part Four utilizes Rochester’s CHI to examine how neighborhood disadvantage correlates to crime harm at the census tract level. Using spatial regression models, this section investigates whether more disadvantaged tracts have higher rates of Robbery, Motor Vehicle Theft, and Dangerous Weapons Harm. Even after controlling for what happens in surrounding tracts, the findings demonstrate that higher neighborhood disadvantage is associated with increased robbery and weapons-related harm. On the contrary, motor vehicle theft harm appeared to be influenced more by opportunity and spatial spread than by disadvantage alone. Together, these models demonstrate how the CHI may be used not simply to define harm, but also to examine how socioeconomic inequality and location influence the distribution of that harm throughout Rochester.

Publication Date

12-15-2025

Document Type

Master's Project

Student Type

Graduate

Degree Name

Criminal Justice (MS)

Department, Program, or Center

Criminal Justice, Department of

College

College of Liberal Arts

Advisor

Irshad Altheimer

Campus

RIT – Main Campus

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