Law Of Crime Concentration Research Articles

Crime within a bandwidth: Testing 'the law of crime concentration at place' in Brussels

Crime within a bandwidth: Testing 'the law of crime concentration at place' in Brussels

Crime within a Bandwidth: Testing “the Law of Crime Concentration at Place” in Brussels

Crime within a Bandwidth: Testing “the Law of Crime Concentration at Place” in Brussels

Examining the Generalizability of Weisburd’s Law of Crime Concentration

Examining the Generalizability of Weisburd’s Law of Crime Concentration

MeasuringMarginalCrime Concentration: A New Solution to an Old Problem

Objectives:In his 2014 Sutherland address to the American Society of Criminology, David Weisburd demonstrated that the share of crime that is accounted for by the most crime-ridden street segments is notably high and strikingly similar across cities, an empirical regularity referred to as the “law of crime concentration.” In the large literature that has since proliferated, there remains considerable debate as to how crime concentration should be measured empirically. We suggest a measure of crime concentration that is simple, accurate and easily interpreted.Methods:Using data from three of the largest cities in the United States, we compare observed crime concentration to a counterfactual distribution of crimes generated by randomizing crimes to street segments. We show that this method avoids a key pitfall that causes a popular method of measuring crime concentration to considerably overstate the degree of crime concentration in a city.Results:While crime is significantly concentrated in a statistical sense and while some crimes are substantively concentrated among hot spots, the precise relationship is considerably weaker than has been documented in the empirical literature.Conclusions:The method we propose is simple and easily interpretable and compliments recent advances which use the Gini coefficient to measure crime concentration.

Too Fine to be Good? Issues of Granularity, Uniformity and Error in Spatial Crime Analysis

Crime counts are sensitive to granularity choice. There is an increasing interest in analyzing crime at very fine granularities, such as street segments, with one of the reasons being that coarse granularities mask hot spots of crime. However, if granularities are too fine, counts may become unstable and unrepresentative. In this paper, we develop a method for determining a granularity that provides a compromise between these two criteria. Our method starts by estimating internal uniformity and robustness to error for different granularities, then deciding on the granularity offering the best balance between the two. Internal uniformity is measured as the proportion of areal units that pass a test of complete spatial randomness for their internal crime distribution. Robustness to error is measured based on the average of the estimated coefficient of variation for each crime count. Our method was tested for burglaries, robberies and homicides in the city of Belo Horizonte, Brazil. Estimated “optimal” granularities were coarser than street segments but finer than neighborhoods. The proportion of units concentrating 50% of all crime was between 11% and 23%. By balancing internal uniformity and robustness to error, our method is capable of producing more reliable crime maps. Our methodology shows that finer is not necessarily better in the micro-analysis of crime, and that units coarser than street segments might be better for this type of study. Finally, the observed crime clustering in our study was less intense than the expected from the law of crime concentration.

The Application of the “Law of Crime Concentration” to Terrorism: The Jerusalem Case Study

One of the areas in terrorism that has not been adequately examined, is the geographic concentration of terror attacks in a city’s micro places. The literature related to the geographical distribution of terror generally focuses on macro places: continents, countries, and regions. In contrast, in the study of ordinary crime, significant studies have been conducted on the distribution of crime in micro-places “hot spots”. The findings of these studies have great significance when adopting models of law enforcement. This study examines whether there is a concentration of terror attacks in a limited number of hot spots that are stable over time. This study examines the entire population of terror attacks in the city of Jerusalem between 2000 and 2017 (249 attacks involving explosives, shootings, stabbings, attacks with a deadly weapon, and run over attacks) as a case study. We investigated and mapped each attack’s exact location (for the majority of attacks) and characterized the particular micro places of these terror attacks, as well as the attacks themselves. The research revealed that there is a higher frequency of terror attacks concentrated in specific hot spots and that they are stable over time. The concentration of terror attacks calls for a specialized counterterrorism response equivalent to “hot spots policing” based on the characteristics of the potential terrorist hot spots.

Spatial and temporal patterns of violent crime in a Brazilian state capital: A quantitative analysis focusing on micro places and small units of time

The present research analyses a local variation of the problem of violence in Brazil and focuses on Florianópolis, the capital of the state of Santa Catarina, long considered the flagship of security in the country, although currently seeing an increase in violent crimes. A quantitative analysis has been implemented to test whether the law of crime concentration and the assumption of spatial-temporal dissimilarity of crime events were consistent for the specific case under study. The results show that crime concentration in Florianópolis is more accentuated than even previous literature would suggest and that the degree of concentration of street robberies and homicides is temporally stable. However, the specific locations where crime took place change over time depending on temporal dimensions such as the season, day of the week, and the hour of the day. Yet, homicide spatial patterns have shown to be less sensitive to seasonal variations. Although this conclusion challenged the initial expectations derived from previous literature, it provides a meaningful explanation of current trends of violent crime in Florianópolis, which are increasingly linked to organized crime and illegal drug trade.

Crime concentrations and micro places: An empirical test of the “law of crime concentration at places” in Belgium

This study examines the extent to which crime concentrations occur at micro places, in order to test Weisburd’s law of crime concentration at places, in two large Belgian cities. Police-registered crime data for the period 2004–2012 were used. Analyses were conducted at the grid level (using 200 meters by 200 meters grid cells), as a proxy for behavior settings. This study assesses Weisburd’s theoretical proposition and by (partly) replicating prior empirical research, we conclude that the findings are in line with those from prior studies regarding crime concentration at micro places. Finally, opportunities and avenues for future research on crime places are discussed.

The spatial concentration and stability of crime in a South African township

The law of crime concentration at places motivates that a small number of locations are responsible for a disproportionate amount of crime. Research applying the law has largely been confined to the United States and Europe with much less known about spatial crime concentrations and their stability in less developed contexts, particularly in Africa. In this study, we explore the spatial concentration of crime in a setting axiomatically different from the West, namely Khayelitsha, a township on the outskirts of Cape Town in South Africa. Specifically, we describe rape, robbery and assault concentrations in Khayelitsha from 2008 to 2015 and examine the extent to which these concentrations change over time. Similar to international research, we found that crime in Khayelitsha spatially concentrates and that these concentrations are remarkably stable. Practical implications of these findings are discussed in the context of a historically unique post-apartheid South African spatial setting.

Hot Spots of Crime and Place‐Based Prevention

AbstractThe August Vollmer Award Address is intended to focus on contributions to justice and on the recipient's research and policy experiences. This contribution begins with the recipient recapping his personal journey to recognizing hot spots of crime and their importance for prevention. He then goes on to summarize the “law of crime concentration” and its importance for the logic model underlying this approach. He describes the seminal Minneapolis Hot Spots Patrol Experiment and the subsequent evaluation research in hot‐spots policing and place‐based prevention more generally that led to its broad acceptance as an effective crime prevention strategy. Finally, the author turns to key unanswered questions in place‐based prevention, focusing on police legitimacy, identifying jurisdictional effects, and emphasizing the importance of harnessing informal social controls.

The Law of Crime Concentration at Places: Editors’ Introduction

The empirical observation that a small number of micro places generate the bulk of urban crime problems has become a criminological axiom. These micro places, commonly referred to as “hot spots” of crime, have been defined as clusters of street addresses, groupings of street blocks, and particular street intersections and street segments (Weisburd et al. 2009). High-activity crime places have been found in neighborhoods characterized by both low and high levels of social disadvantage (Weisburd and Green 1995; Curman et al. 2015). More recently, researchers have also demonstrated that the concentration of crime at particular places is stable over time (Weisburd et al. 2004; Braga et al. 2010; Andresen and Malleson 2011). The stability of crime at hot spots reinforces the logic that underlies place-based prevention strategies. Without intervention, crime hot spots are not likely to disappear in short time periods. Concentrating crime prevention resources on such places makes good sense both for short term and long term gains (Braga and Weisburd 2010; Weisburd et al. 2004).

The Law of Crime Concentration: An Application and Recommendations for Future Research

We address four outstanding empirical questions related to the “law of crime concentration” (Weisburd in Criminology 53:133–157, 2015): (1) Is the spatial concentration of crime stable over time? (2) Do the same places consistently rank among those with the highest crime counts? (3) How much crime concentration would be observed if crimes were distributed randomly over place? (4) To what degree does the spatial concentration of crime depend on places that are crime free? The data are annual counts of violent and property crimes in St. Louis between 2000 and 2014. Temporal stability in the spatial inequality of crime is measured by computing the fraction of crimes that occur in the 5% of street segments with the highest crime frequencies each year. The spatial mobility of crime is measured by computing the number of years each street segment appears in the top 5% of street segments. Poisson simulations are used to estimate the fraction of crimes that could appear in the top 5% of street segments on the basis of chance alone. The impact of crime-free locales on the spatial concentration of crime is evaluated by comparing results from analyses that include and exclude crime-free street segments from the crime distributions. The concentration of crime is highly unequal and stable over time. The specific street segments with the highest crime frequencies, however, change over time. Nontrivial fractions of street segments may appear among the 5% with the highest crime frequencies on the basis of chance. Spatial concentration of crime is reduced when crime-free street segments are excluded from the crime distributions. The law of crime concentration is not a measurement artifact. Its substantive significance, however, should be assessed in future longitudinal research that replicates the current study across diverse social settings.

Community Criminology: Fundamentals of Spatial and Temporal Scaling, Ecological Indicators, and Selectivity Bias. By Ralph Taylor. New York: New York University Press, 2015. Pp. xii+329. $49.00.

<i>Community Criminology: Fundamentals of Spatial and Temporal Scaling, Ecological Indicators, and Selectivity Bias</i>. By Ralph Taylor. New York: New York University Press, 2015. Pp. xii+329. $49.00.

Testing the “Law of Crime Concentration at Place” in a Suburban Setting: Implications for Research and Practice

Objective To assess whether the “law of crime concentration at place” applies in a non-urban context. We test whether longitudinal trends in crime concentration, stability, and variability apply in a suburban setting.

The Trajectories of Crime at Places: Understanding the Patterns of Disaggregated Crime Types

Investigate the spatial concentrations and the stability of trajectories for disaggregated crime types on street segments and intersections in Vancouver, Canada. A longitudinal analysis of 16 years of crime data using street segments and intersections as the units of analysis. We use the k-means non-parametric cluster analysis technique considering eight crime types: assault, burglary, robbery, theft, theft of vehicle, theft from vehicle, other, and total crime. The overall results for the individual crime types versus overall crime are similar: crime is highly concentrated regardless of crime type, most street segment and intersection trajectories are stable over time with the others decreasing, and most decreasing trajectories are in the same general areas. However, there are notable differences across crime types that need to be considered when attempting to understand spatial pattern changes and implement crime prevention initiatives. The law of crime concentration at places holds in Vancouver, Canada for disaggregated crime types in the context of spatial concentrations and their stability over time. However, notable differences exist across crime types that should be accounted for when developing theory or policy.