Law Enforcement Response to Crime in Tennessee: Incident Clearance Rates in Rural vs Nonrural Counties

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Incident clearance rates are calculated by dividing the total number of crime occurrences by those solved by police in a given area. While these percentages are commonly used as a measure of law enforcement effectiveness, they are largely influenced by geographic size, economy, and cultural factors. For instance, rural police tend to have fewer financial resources and may not have sufficient personnel and technology to investigate certain criminal offenses. Rural communities also tend to be more close-knit, have stronger social ties, and residents often know one another, which can influence reporting rates and police strategies. Improving our understanding of clearance rates across rural and urban counties is necessary to increase the effectiveness of location-specific law enforcement practices. Data for the present study were obtained from the Tennessee Incident Based Reporting System for reported incidents of crimes against persons and subsequent clearance rates in 2015. Whether an incident was cleared by arrest, cleared by exceptional reasons, or not cleared was noted. Exceptional clearances refer to situations where an offender died prior to being arrested, a prosecutor declined a case, extradition was denied, a victim refused to cooperate, or a juvenile was responsible for the incident. Using the 2013 Rural Urban Continuum Codes (RUCC), counties were categorized based on geographic size and proximity to metropolitan areas, Tennessee's 95 counties were grouped into metropolitan counties (RUCC codes 1-3; n = 42), nonmetropolitan counties with an urban population (RUCC codes 4-7; n = 37), and completely rural counties or those with a population of less than 2,500 (RUCC codes 8-9; n = 16). Preliminary ANOVA analyses with post hoc comparisons using the Bonferroni test suggest that rural counties (M=73.0%, SD=18.1) had higher incidence clearance rates [F(2,92) = 4.19, p = .018], compared to both metropolitan counties (M=61.1%, SD=14.3, p =.024) and nonmetropolitan counties with urban populations greater than 2,500 (M=61.2%, SD=14.2, p =.029). Similarly, rural counties (M=71.9%, SD=18.3) had significantly higher rates of clearance by arrest [F(2,92) = 9.29, p = .000] than metropolitan counties (M=51.5%, SD=14.9, p =.000) and nonmetropolitan counties with urban populations greater than 2,500 (M=55.7%, SD=16.6, p =.004). In contrast, a nonparametric Kruskal-Wallis one-way ANOVA test yielded insignificant differences across the three groups with regard to exceptional clearance rates [F(2,74) = 5.79, p = .055]. Thus, initial findings reveal that overall clearance and clearance by arrest rates in rural areas differ from more urban locations. Additional analyses regarding county-level differences in incidence clearance rates across various types of offenses will be explored. Possible factors that may contribute to discrepancies across counties and future directions will be discussed.


Johnson City, TN

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