Crime dynamics in Edmonton’s train stations: analysing hot spots, harm spots and offender patterns

Abstract

PurposeThe objectives of this study are to (a) identify spatial and temporal crime concentrations, (b) supplement the traditional place-based analysis that defines hot spots based on counted incidents with an analysis of crime severity and (c) add to the research of hot spots with an analysis of offender data.Design/methodology/approachThis study explores crime concentration in mass transit settings, focusing on Edmonton’s Light Rail Transit (LRT) stations in 2017–2022. Pareto curves are used to observe the degree of concentration of crime in certain locations using multiple estimates; trajectory analysis is then used to observe crime patterns in the data on both places and offenders.FindingsA total of 16.3% of stations accounted for 50% of recorded incidents. Train stations with high or low crime counts and severity remained as such consistently over time. Additionally, 3.6% of offenders accounted for 50% of incident count, while 5% accounted for 50% of harm. We did not observe differences in the patterns and distributions of crime concentrations when comparing crime counts and harm.Research limitations/implicationsHot spots and harm spots are synonymous in low-crime-harm environments: high-harm incidents are outliers, and their weight in the average crime severity score is limited. More sensitive severity measures are needed for high-frequenty, low-harm enviornments. Practical implicationsThe findings underscore the benefits of integrating offender data in place-based applied research.Originality/valueThe findings provide additional evidence on the utility of place-based criminology and potentially cost-effective interventions.