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.

Methods

We use group-based trajectory analysis to examine trends in recorded crime incidents on street segments in Brooklyn Park, a suburban city outside Minneapolis, Minnesota, over a 15-year period from 2000 to 2014.

Results

Consistent with the law of crime concentration at place, crime in Brooklyn Park is highly concentrated at a small percentage of micro-places. Two percent of street segments produced 50 % of the crime over the study period and 0.4 % of segments produced 25 % of the crime. The patterns of concentration are highly stable over time. However, the concentration of crime is substantially higher and there is much less street-by-street variability in Brooklyn Park compared to urban areas.

Conclusions

We find strong support for the application of the law of crime concentration at place to a non-urban setting, suggesting that place-based policing approaches tested in cities can also be applied to suburbs. However, there are also important differences in the concentration and variability of crime hot spots in suburbs that require further examination. Our study is based on a single setting that may not be representative of other suburban and rural areas. Finally, the clustering of hot spots raises questions about the use of street segments to analyze crime at suburban micro-places.

     

Is it Important to Examine Crime Trends at a Local “Micro” Level?: A Longitudinal Analysis of Street to Street Variability in Crime Trajectories

Over the last 40 years, the question of how crime varies across places has gotten greater attention. At the same time, as data and computing power have increased, the definition of a ‘place’ has shifted farther down the geographic cone of resolution. This has led many researchers to consider places as small as single addresses, group of addresses, face blocks or street blocks. Both cross-sectional and longitudinal studies of the spatial distribution of crime have consistently found crime is strongly concentrated at a small group of ‘micro’ places. Recent longitudinal studies have also revealed crime concentration across micro places is relatively stable over time. A major question that has not been answered in prior research is the degree of block to block variability at this local ‘micro’ level for all crime. To answer this question, we examine both temporal and spatial variation in crime across street blocks in the city of Seattle Washington. This is accomplished by applying trajectory analysis to establish groups of places that follow similar crime trajectories over 16 years. Then, using quantitative spatial statistics, we establish whether streets having the same temporal trajectory are collocated spatially or whether there is street to street variation in the temporal patterns of crime. In a surprising number of cases we find that individual street segments have trajectories which are unrelated to their immediately adjacent streets. This finding of heterogeneity suggests it may be particularly important to examine crime trends at very local geographic levels. At a policy level, our research reinforces the importance of initiatives like ‘hot spots policing’ which address specific streets within relatively small areas.     

The Concentration and Stability of Gun Violence at Micro Places in Boston, 1980–2008

Boston, like many other major U.S. cities, experienced an epidemic of gun violence during the late 1980s and early 1990s that was followed by a sudden large downturn in gun violence in the mid 1990s. The gun violence drop continued until the early part of the new millennium. Recent advances in criminological research suggest that there is significant clustering of crime in micro places, or “hot spots,” that generate a disproportionate amount of criminal events in a city. In this paper, we use growth curve regression models to uncover distinctive developmental trends in gun assault incidents at street segments and intersections in Boston over a 29-year period. We find that Boston gun violence is intensely concentrated at a small number of street segments and intersections rather than spread evenly across the urban landscape between 1980 and 2008. Gun violence trends at these high-activity micro places follow two general trajectories: stable concentrations of gun assaults incidents over time and volatile concentrations of gun assault incidents over time. Micro places with volatile trajectories represent less than 3% of street segments and intersections, generate more than half of all gun violence incidents, and seem to be the primary drivers of overall gun violence trends in Boston. Our findings suggest that the urban gun violence epidemic, and sudden downturn in urban gun violence in the late 1990s, may be best understood by examining highly volatile micro-level trends at a relatively small number of places in urban environments.     

TRAJECTORIES OF CRIME AT PLACES: A LONGITUDINAL STUDY OF STREET SEGMENTS IN THE CITY OF SEATTLE*

Studies of crime at micro places have generally relied on cross‐sectional data and reported the distributions of crime statistics over short periods of time. In this paper we use official crime data to examine the distribution of crime at street segments in Seattle, Washington, over a 14‐year period. We go beyond prior research in two ways. First, we view crime trends at places over a much longer period than other studies that have examined micro places. Second, we use group‐based trajectory analysis to uncover distinctive developmental trends in our data. Our findings support the view that micro places generally have stable concentrations of crime events over time. However, we also find that a relatively small proportion of places belong to groups with steeply rising or declining crime trajectories and that these places are primarily responsible for overall city trends in crime. These findings are particularly important given the more general decline in crime rates observed in Seattle and many other American cities in the 1990s. Our study suggests that the crime drop can be understood not as a general process that occurred across the city landscape but one that was generated in a relatively small group of micro places with strong declining crime trajectories over time.     

The Concentration and Stability of Drug Activity in Seattle,Washington Using Police and Emergency Medical Services Data

Objectives

Prior research demonstrates that crime is highly concentrated at place and that these concentrations are stable from year to year, highlighting the importance of place to crime control and prevention. A potential limitation is that most studies only use one data source to diagnose these patterns. The present study uses data from both police and emergency medical services (EMS) to explore the spatial concentration and stability of drug activity in Seattle, Washington from 2009 to 2014.

Methods

We use concentration graphs and group-based trajectory analysis to examine concentration and stability of calls related to drug activity in both data sources separately and combined. Additionally, we employ Andresen’s S-Index to determine the similarity of concentration within the SPD data, the EMS data and the combined data year to year as well as the degree of co-location between the SPD and EMS data during the study period.

Results

We find a high degree of concentration and group-based stability for both SPD and EMS drug calls across all street segments in Seattle. Conversely, we find only moderate local geographic stability of drug use across street segments as indicated by each of the data sources over the study period. Last, we find the spatial patterns in drug use as indicated by each data source are significantly different each year.

Conclusions

At the same time these findings provide support for the law of crime concentration, they also raise questions about local stability patterns. Additionally, they highlight the importance of expanding inquiries of crime and place research into new data sources. Our results serve to reinforce the importance of multiple data sets in quantifying, understanding, and responding to the drug problem in Seattle.

     

The Influence of Community Areas,Neighborhood Clusters,and Street Segments on the Spatial Variability of Violent Crime in Chicago

Objectives

The influence of three hierarchical units of analysis on the total spatial variability of violent crime incidents in Chicago is assessed. This analysis seeks to replicate a recent study that found street segments, rather than neighborhood units of analysis, accounted for the largest share of the total spatial variability of crime in The Hague, Netherlands (see Steenbeek and Weisburd J Quant Criminol. doi: 10.1007/s10940-015-9276-3, 2015).

Methods

We analyze violent crime incidents reported to the police between 2001 and 2014. 359,786 incidents were geocoded to 41,926 street segments nested within 342 neighborhood clusters, in turn nested within 76 community areas in Chicago. Linear mixed models with random slopes of time were estimated to observe the variance uniquely attributed to each unit of analysis.

Results

Similar to Steenbeek and Weisburd, we find 56–65 % of the total variability in violent crime incidents can be attributed to street segments in Chicago. City-wide reductions in violence over the observation period coincide with increases in the spatial variability attributed to street segments and decreases in the variability attributed to both neighborhood units.

Conclusions

Our results suggest that scholars interested in understanding the spatial variation of crime across urban landscapes should be focused on the small places that comprise larger geographic areas. The next wave of “neighborhood-effects” research should explore the role of hierarchical processes in understanding crime variation within larger areas.

     

The point break effect: an examination of surf,crime, and transitory opportunities

Opportunity theories of crime suggest that crime is highly specific and concentrated in time and space. Using these theories as a framework, this paper seeks to examine the transitory nature of crime. This hypothesis was tested using data from a coastal city in California to examine the relationship between surf conditions (measured at five daily time points) and number of crime incidents (n = 16,075). Crime totals were aggregated at the street segment level (n = 4551) for each day in 2011. These data were modeled using a series of panel negative binomial models, clustered by census block group. The findings suggest that surf conditions had an effect on the likelihood of crime incidents, but these effects were time specific. Favorable surf conditions were associated with increases in crime only between 2:30 pm and 5:29 pm. Additionally, locations closer to surf spots were associated with more crime, relative to locations farther away. Closer examination of micro-geographies aids in understanding how systematic shifts in routine activities affect the frequency and location of crime, and allows crime prevention to be more specialized and efficient. Adding to the extant understanding of hot times and opportunity structures will enable more effective allocation of resources and predictive policing efforts.     

Hot spots policing in a high-crime environment: an experimental evaluation in Medellín

Journal of Experimental Criminology - Test direct, spillover, and aggregate effects of hot spots policing on crime in a high-crime environment. We identified 967 hot spot street segments and...     

Replicating Group-Based Trajectory Models of Crime at Micro-Places in Albany,NY

Objectives

Replicate two previous studies of temporal crime trends at the street block level. We replicate the general approach of group-based trajectory modelling of crimes at micro-places originally taken by Weisburd et al. (Criminology 42(2):283–322, 2004) and replicated by Curman et al. (J Quant Criminol 31(1):127–147, 2014). We examine patterns in a city of a different character (Albany, NY) than those previously examined (Seattle and Vancouver) and so contribute to the generalizability of previous findings.

Methods

Crimes between 2000 and 2013 were used to identify different trajectory groups at street segments and intersections. Zero-inflated Poisson regression models are used to identify the trajectories. Pin maps, Ripley’s K and neighbor transition matrices are used to show the spatial patterning of the trajectory groups.

Results

The trajectory solution with eight classes is selected based on several model selection criteria. The trajectory of each those groups follow the overall citywide decline, and are only separated by the mean level of crime. Spatial analysis shows that higher crime trajectory groups are more likely to be nearby one another, potentially suggesting a diffusion process.

Conclusions

Our work adds additional support to that of others who have found tight coupling of crime at micro-places. We find that the clustering of trajectories identified a set of street units that disproportionately contributed to the total level of crime citywide in Albany, consistent with previous research. However, the temporal trends over time in Albany differed from those exhibited in previous work in Seattle but were consistent with patterns in Vancouver.

     

A randomized controlled trial of different policing strategies at hot spots of violent crime

Focusing police efforts on “hot spots” has gained acceptance among researchers and practitioners. However, little rigorous evidence exists on the comparative effectiveness of different hot spots strategies. To address this gap, we randomly assigned 83 hot spots of violence in Jacksonville, Florida, to receive either a problem-oriented policing (POP) strategy, directed-saturation patrol, or a control condition for 90 days. We then examined crime in these areas during the intervention period and a 90-day post-intervention period. In sum, the use of POP was associated with a 33% reduction in “street violence” during the 90 days following the intervention. While not statistically significant, we also observed that POP was associated with other non-trivial reductions in violence and property crime during the post-intervention period. In contrast, we did not detect statistically significant crime reductions for the directed-saturation patrol group, though there were non-significant declines in crime in these areas during the intervention period. Tests for displacement or a diffusion of benefits provided indications that violence was displaced to areas near the POP locations, though some patterns in the data suggest this may have been due to the effects of POP on crime reporting by citizens in nearby areas. We conclude by discussing the study’s limitations and the implications of the findings for efforts to refine hot spots policing.     

Where the Action is in Crime? An Examination of Variability of Crime Across Different Spatial Units in The Hague, 2001–2009

Objectives

To identify how much of the variability of crime in a city can be attributed to micro (street segment), meso (neighborhood), and macro (district) levels of geography. We define the extent to which different levels of geography are important in understanding the crime problem within cities and how those relationships change over time.

Methods

Data are police recorded crime events for the period 2001–2009. More than 400,000 crime events are geocoded to about 15,000 street segments, nested within 114 neighborhoods, in turn nested within 44 districts. Lorenz curves and Gini coefficients are used to describe the crime concentration at the three spatial levels. Linear mixed models with random slopes of time are used to estimate the variance attributed to each level.

Results

About 58–69 % of the variability of crime can be attributed to street segments, with most of the remaining variability at the district level. Our findings suggest that micro geographic units are key to understanding the crime problem and that the neighborhood does not add significantly beyond what is learned at the micro and macro levels. While the total number of crime events declines over time, the importance of street segments increases over time.

Conclusions

Our findings suggest that micro geographic units are key to understanding the variability of crime within cities—despite the fact that they have received little criminological focus so far. Moreover, our results raise a strong challenge to recent focus on such meso geographic units as census block groups.

     

Could Innovations in Policing have Contributed to the New York City Crime Drop even in a Period of Declining Police Strength?: The Case of Stop,Question and Frisk as a Hot Spots Policing Strategy

Available data make it impossible to reach strong conclusions about the role of policing in the New York crime decline. Instead, we examine whether innovations implemented in New York fit with what is known about effective policing strategies. Our main analysis focuses on how the New York City Police Department (NYPD) could have continued to contribute to the crime drop over the last decade when the number of police declined significantly. We examine geographic data on crime and stop, question and frisks (SQFs) to show that SQFs are concentrated at crime hot spots. We also show that the NYPD increased these specific hot spots policing strategies despite declining numbers. In our discussion, we speculate on whether this “doing more with less” could be an explanation for the continued crime drop in New York, noting the limitations of drawing conclusions from existing data. We also raise concerns about possible backfire effects of SQF hot spots approaches.     

Do Crime Hot Spots Exist in Developing Countries? Evidence from India

Objectives

To determine whether concentrations of crime documented in American cities such as Boston, Jacksonville, Minneapolis, Sacramento, and Seattle generalize to unique environments such as India.

Methods

Two years of motor vehicle theft (MVT) and burglary incidents from two police stations in Jaipur, India are analyzed. The degree to which crime clusters is documented using nearest neighborhood hierarchical clustering (NNHC). These results are compared to several widely cited studies documenting concentrations in the United States.

Results

The NNHC procedure identified five MVT hot spots, which accounted for just .09 % of the two station’s land, but over 13 % of these incidents, and four burglary hot spots, which accounted for less than 1 % of its land, but nearly 23 % of the incidents.

Conclusions

Given the stark differences in the built environment and sociological makeup of Jaipur, a better understanding of the forces that cause crime to concentrate to a high degree needs to be discerned before implementing law-enforcement driven policies derived from the scholarship of American cities. Additional research should also seek to replicate not just the degree to which crime clusters in these unique environments, but also its stability over time and micro place variation.

     

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

Objectives

Investigate the spatial concentrations and the stability of trajectories for disaggregated crime types on street segments and intersections in Vancouver, Canada.

Methods

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.

Results

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.

Conclusions

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.

     

CAN HOT SPOTS POLICING REDUCE CRIME IN URBAN AREAS? AN AGENT‐BASED SIMULATION*

Over the past two decades, there has been a growing consensus among researchers that hot spots policing is an effective strategy to prevent crime. Although strong evidence exists that hot spots policing will reduce crime at hot spots without immediate spatial displacement, we know little about its possible jurisdictional or large‐area impacts. We cannot isolate such effects in previous experiments because they (appropriately) compare treatment and control hot spots within large urban communities, thus, confounding estimates of area‐wide impacts. An agent‐based model is used to estimate area‐wide impacts of hot spots policing on street robbery. We test two implementations of hot spots policing (representing different levels of resource allocation) in a simulated borough of a city, and we compare them with two control conditions, one model with constant random patrol and another with no police officers. Our models estimate the short‐ and long‐term impacts on large‐area robbery levels of these different schemes of policing resources. These experiments reveal statistically significant effects for hot spots policing beyond both a random patrol model and a landscape without police. These simulations suggest that wider application of hot spots policing can have significant impacts on overall levels of crime in urban areas.     

The law of concentrations of crime at place: the case of Tel Aviv-Jaffa

Weisburd, Groff, and Yang argue that there is a ‘law of concentrations of crime at place’ within cities. In this paper, we provide a test for this proposition in Tel Aviv-Jaffa. We found that crime concentrations at street segments in 2010 were remarkably similar to those observed in American cities. About 4.5% of the street segments produced approximately 50% of the crime, and about 1% of street segments produced 25% of crime. Our study provides important verification of the broad applicability of the law of crime concentrations at place.     

Male and female child murderers: an empirical analysis of U.S. arrest data

Recent U.S. cases of murders by children below age 11 have captured national headlines. A review of the literature reveals that little is known about this population of juvenile homicide offenders (JHOs). Most studies on juvenile murderers have used small clinical samples, focused on adolescents, and concentrated on male offenders. Studies that have used Supplementary Homicide Report (SHR) data have found significant gender differences among juveniles below 18 years arrested for murder. This study investigated gender differences among 226 juvenile murderers ages 6 through 10 involved in single-victim incidents using bivariate and multivariate statistical techniques. Consistent with previous research, bivariate analyses revealed gender differences with respect to the type of weapon used, age of the victim, relationship to the victim, and circumstances of the crime. Logistic regression analysis identified female JHOs as more likely to use a knife, kill a family member, and kill a victim below age 5, when compared with male JHOs. From these findings, profiles of young male and female JHOs can be drawn. The article concludes with a discussion of the study's implications for prevention and treatment. The authors recommend that future research in gender differences among young children focus on examining psychological, neurological, and sociological variables not included in the SHR data set.     

DOES CRIME JUST MOVE AROUND THE CORNER? A CONTROLLED STUDY OF SPATIAL DISPLACEMENT AND DIFFUSION OF CRIME CONTROL BENEFITS*

Recent studies point to the potential theoretical and practical benefits of focusing police resources on crime hot spots. However, many scholars have noted that such approaches risk displacing crime or disorder to other places where programs are not in place. Although much attention has been paid to the idea of displacement, methodological problems associated with measuring it have often been overlooked. We try to fill these gaps in measurement and understanding of displacement and the related phenomenon of diffusion of crime control benefits. Our main focus is on immediate spatial displacement or diffusion of crime to areas near the targeted sites of an intervention. Do focused crime prevention efforts at places simply result in a movement of offenders to areas nearby targeted sites—“do they simply move crime around the corner”? Or, conversely, will a crime prevention effort focusing on specific places lead to improvement in areas nearby—what has come to be termed a diffusion of crime control benefits? Our data are drawn from a controlled study of displacement and diffusion in Jersey City, New Jersey. Two sites with substantial street‐level crime and disorder were targeted and carefully monitored during an experimental period. Two neighboring areas were selected as “catchment areas” from which to assess immediate spatial displacement or diffusion. Intensive police interventions were applied to each target site but not to the catchment areas. More than 6,000 20‐minute social observations were conducted in the target and catchment areas. They were supplemented by interviews and ethnographic field observations. Our findings indicate that, at least for crime markets involving drugs and prostitution, crime does not simply move around the corner. Indeed, this study supports the position that the most likely outcome of such focused crime prevention efforts is a diffusion of crime control benefits to nearby areas.     

Permeability and Burglary Risk: Are Cul-de-Sacs Safer?

That crime is concentrated in space is now accepted as commonplace. Explanations for why it clusters at particular locations are various reflecting the range of factors which are held to influence crime placement. In this article, we focus on the role of the permeability of the street network on the location of crime. We first review the research conducted hitherto, summarising the different approaches to analysis and the findings that have so far emerged. Then we present original analyses conducted at the street segment level to examine the issues at hand. In contrast to much of the prior research, in this study we examine the patterns for a large study area in which there is considerable variation in street network configuration. Moreover, and in contrast to all of the previous research, the approach to analysis takes into account the multi-level structure of the data analysed. The findings demonstrate that increased permeability is associated with elevated burglary risk, that burglary risk is lower on cul-de-sacs (particularly those that are sinuous in nature), and that the risk of burglary is higher on more major roads and those street segments that are connected to them. In the conclusion of the paper we outline an agenda for future research.     

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

Objective

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?

Methods

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.

Results

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.

Conclusions

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.