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.

     

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.

     

Measuring the Spatial and Temporal Patterns of Police Proactivity

Objectives

To measure where officers engage in proactive, self-initiated activities, how much time they spend being proactive, and whether their proactive activities coincide with crime patterns.

Methods

This study uses Andresen’s Spatial Point Pattern Test to compare the spatial similarity between police proactivity and crime, as well as regression modeling to explore the relationship between proactivity and crime and the time spent on proactivity and crime.

Results

In the jurisdiction examined, high levels of proactivity are noted. This proactive activity is more likely to occur in places where crime is most concentrated. Additionally, the number of proactive calls and the proactive time spent per crime-and-disorder call remain high and stable across spatial scales. For each crime call received at a street block, police initiated 0.7 proactive activities and spent approximately 28 min carrying out proactive works.

Conclusions

This study develops a way of measuring proactive activity by patrol officers using calls for service data. We find that not only do officers in this jurisdiction exhibit higher levels of proactivity to prevent crime (compared to reacting to crime), but they also do so in targeted, micro-place ways. Agencies may consider using similar techniques to gauge the levels of proactivity in their agencies if proactive activity is a goal.

     

Assessing the Validity of the Law of Crime Concentration Across Different Temporal Scales

Objectives

The present study examined if Weisburd’s (Criminology 53(2):133–157, 2015) law of crime concentration held across different theoretically relevant temporal scales.

Methods

The cumulative percentages of Philadelphia, PA USA street blocks and intersections experiencing 25 and 50 % of street robberies by hour of the day, days of the week, and seasons of the year were compared to the bandwidth percentages established by Weisburd (2015). Different analyses were used to determine the stability of the micro-places’ street robbery levels within the three temporal scales.

Results

We found that the cumulative percentages of street blocks and intersections experiencing 25 and 50 % of street robberies at each of the three temporal scales closely matched the bandwidth percentages expected from Weisburd (2015) and some micro-places experienced street robberies across all temporal periods while others had more isolated temporal concentrations.

Conclusion

Weisburd’s (2015) law of crime concentration holds across different theoretically relevant temporal scales, and future criminology of place studies should not ignore temporal crime patterns. Further, it may be possible to refine hot spots policing approaches by incorporating spatial–temporal crime concentrations.

     

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.

     

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 efficacy of foot patrol in violent places

Objectives

This study examines the effectiveness of foot patrol in violent micro-places. A large urban police department deployed foot patrol in micro-places (hot spots) for a period of 90 days for two shifts each day. Our objective is to determine whether this activity impacted violent crime in these hot spots and whether spatial displacement of crime occurred.

Methods

Eight eligible foot beat locations were set by examining crime rates for previous years in order to identify micro-places of high criminal activity. We employed a quasi-experimental design comparing the four treatment to the four control areas, estimating panel-specific autoregressive models for 30 weeks prior to and 40 weeks after the treatment.

Results

Time series models revealed statistically significant reductions in violent crime in the micro-places receiving foot patrol treatment, while no such reductions were observed in the control areas. The deterrent effect, however, was short and dissipated quickly. Control areas did not experience any crime prevention benefit during this time period. No evidence of crime displacement to spatially contiguous areas was detected.

Conclusions

This contributes to the growing body of knowledge that focused police strategies within hot spots impact violent crime. Specifically, the implementation of foot patrol in high crime hot spots led to measurable reductions in aggravated assaults and robberies, without displacing crime to contiguous areas.

     

Measuring Crime Concentration Across Cities of Varying Sizes: Complications Based on the Spatial and Temporal Scale Employed

Objectives

We argue that assessing the level of crime concentration across cities has four challenges: (1) how much variability should we expect to observe; (2) whether concentration should be measured across different types of macro units of different sizes; (3) a statistical challenge for measuring crime concentration; (4) the temporal assumption employed when measuring high crime locations.

Methods

We use data for 42 cities in southern California with at least 40,000 population to assess the level of crime concentration in them for five different Part 1 crimes and total Part 1 crimes over 2005–2012. We demonstrate that the traditional measure of crime concentration is confounded by crimes that may simply spatially locate due to random chance. We also use two measures employing different temporal assumptions: a historically adjusted crime concentration measure, and a temporally adjusted crime concentration measure (a novel approximate solution that is simple for researchers to implement).

Results

There is much variability in crime concentration over cities in the top 5 % of street segments. The standard deviation across cities over years for the temporally adjusted crime concentration measure is between 10 and 20 % across crime types (with the average range typically being about 15–90 %). The historically adjusted concentration has similar variability and typically ranges from about 35 to 100 %.

Conclusions

The study provides evidence of variability in the level of crime concentration across cities, but also raises important questions about the temporal scale when measuring this concentration. The results open an exciting new area of research exploring why levels of crime concentration may vary over cities? Either micro- or macro- theories may help researchers in exploring this new direction.

     

The introduction of CCTV and associated changes in heroin purchase and injection settings in Footscray,Victoria, Australia

Objectives

In June 2011, closed-circuit television (CCTV) was introduced in Footscray (a suburb of Melbourne, Australia) to help deter street-based drug trading. We investigate whether there were subsequent shifts in the settings (e.g., street, house) in which heroin was purchased or injected by people who inject drugs (PWID).

Methods

Using heroin purchase data from the Melbourne Injecting Drug User Cohort Study, multinomial logistic models with fixed effects for CCTV introduction were used to estimate the percentage of: (1) heroin purchased on the street, from mobile dealers and in house settings; and (2) heroin injections occurring in street, car, public toilet, and house settings. Displacement effects were investigated with a logistic model capturing the likelihood of traveling to Footscray to purchase heroin.

Results

Following CCTV introduction, the percentage of heroin injections occurring in public toilet settings decreased by 13 % (95 % CI ?27 %, ?0 %). This was accompanied by a non-significant increase in the percentage of heroin injections in street settings of 23 % (95 % CI ?1 %, +41 %). Changes in other settings were small and non-significant. No suburb displacement effects were found.

Conclusions

The introduction of CCTV in Footscray may have displaced PWID who previously injected heroin in public toilets to street settings. Apart from this, Footscray’s street-based heroin market operates much as it did before CCTV.

     

Measuring Disorder: Observer Bias in Systematic Social Observations at Streets and Neighborhoods

Objectives

The present study focuses on Systematic Social Observation (SSO) as a method to investigate physical and social disorder at different units of analysis. The study contributes to the aggregation bias debate and to the ‘social science of ecological assessment’ in two ways: first, by presenting a new model that directly controls for observer bias in ecological constructs and second, by attempting to identify systematic sources of bias in SSO that affect the valid and reliable measurement of physical and social disorder at both street segments and neighborhoods.

Methods

Data on physical disorder (e.g., litter, cigarette butts) and social disorder (e.g., loitering adults) from 1422 street segments in 253 different neighborhoods in a conurbation of the greater The Hague area (the Netherlands) are analyzed using cross-classified multilevel models.

Results

Neighborhood differences in disorder are overestimated when scholars fail to recognize the cross-classified data structure of an SSO study that is due to allocation of street segments to observers and neighborhoods. Not correcting for observer bias and observational conditions underestimates the disorder–crime association at street segment/grid cell level, but overestimates this association at the neighborhood level.

Conclusion

Findings indicate that SSO can be used for measuring disorder at both street segment level and neighborhood level. Future studies should pay attention to observer bias prior to their data collection by selecting a minimum number of observers, offering extensive training, and collecting information on the urban background of the observers.

     

A quasi-experimental evaluation of the impact of bike-sharing stations on micro-level robbery occurrence

Objectives

To examine if the implementation of bike-sharing stations is linked to robbery occurrence in micro-level street corner units in Cincinnati, OH, USA.

Methods

Propensity score matching was used to select comparison street corner units. The effect of bike-sharing station implementation on robbery occurrence across weekly, biweekly, and monthly observations was estimated using repeated measures multi-level logistic regression models.

Results

Bike-sharing stations did not statistically significantly link to robbery occurrence in immediate or nearby street corner units after implementation.

Conclusions

Numerous explanations consistent with Crime Pattern Theory may explain the null effect of bike-sharing stations on robbery occurrence. Future research should continue to examine how changes in the urban backcloth, such as bike-sharing stations, impact geographic crime patterns.

     

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.

     

The Structure of Citizen Perceptions of Crime and Disorder: New Insights from a Caribbean Community

Objectives

This study builds on existing research from US cities on the construct and discriminant validity of perceptual measures of crime and disorder. It seeks to determine whether citizens distinguish between crime and disorder.

Methods

This study draws on quantitative and qualitative data from a high-crime community in Trinidad and Tobago, a small-island developing nation in the eastern Caribbean. Analysis of the quantitative data relies on exploratory and confirmatory factor analysis methods designed for use with categorical observed variables and continuous latent variables.

Results

In contrast to previous research, we find that citizens do distinguish between physical disorder and general crime, but there is a perceptual overlap for some drug-related offenses and types of social disorder.

Conclusions

This study raises questions about the external validity of research on the relationship between perceptions of crime and disorder conducted in the US, and contributes to ongoing discussions and debates about the meaning of disorder. The findings suggest the need for theory and research to explain how context shapes not only the magnitudes of these perceptions, but also their structures. The results also demonstrate the benefits of mixed-methods research approaches in this area of study.

     

Immigration and Crime in the New Destinations, 2000–2007: A Test of the Disorganizing Effect of Migration

Objectives

Drawing from a social disorganization perspective, this research addresses the effect of immigration on crime within new destinations—places that have experienced significant recent growth in immigration over the last two decades.

Methods

Fixed effects regression analyses are run on a sample of n = 1252 places, including 194 new destinations, for the change in crime from 2000 to the 2005–2007 period. Data are drawn from the 2000 Decennial Census, 2005–2007 American Community Survey, and the Uniform Crime Reports. Places included in the sample had a minimum population of 20,000 as of the 2005-07 ACS. New destinations are defined as places where the foreign-born have increased by 150 % or more since 1990 and with a minimum foreign-born population of 1000 in 2007.

Results

Results indicate new destinations experienced greater declines in crime, relative to the rest of the sample. Moreover, new destinations with greater increases in foreign-born experienced greater declines in their rates of crime. Additional predictors of change in crime include change in socioeconomic disadvantage, the adult-child ratio, and population size.

Conclusions

Results fail to support a disorganization view of the effect of immigration on crime in new destinations and are more in line with the emerging community resource perspective. Limitations and suggestions for future directions are discussed.

     

The Murder Mystery: Police Effectiveness and Homicide

Objective

Previous aggregate analyses of the effect of police on crime show that increases in police staffing are especially effective at preventing homicide. This conflicts with evidence that suggests standard police methods should be more effective at preventing robbery, auto theft, and other property crimes. My objective is to reconcile the two.

Methods

Regression of crime rates on uniformed police staffing and other economic and demographic covariates, for a panel of 59 US cities for the period 1970–2013.

Results

Lagged crime rates are strong and statistically significant predictors of both policing staffing and crime rates, particularly homicide. When lags are included in the specification, the apparent effect of police on homicide drops by more than 70 %; there is little change in the effect of police on other crimes. Findings are robust with respect to specification and method.

Conclusions

Previous studies omitted lags and overstated the effectiveness of police on homicide. Because murder accounts for almost 40 % of all costs of crime in US cities, it is no longer clear whether increasing police force size is a cost-effective way to cut crime. Improving police tactics is more likely to work and less expensive.

     

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.

     

Predictive Crime Mapping: Arbitrary Grids or Street Networks?

Objectives

Decades of empirical research demonstrate that crime is concentrated at a range of spatial scales, including street segments. Further, the degree of clustering at particular geographic units remains noticeably stable and consistent; a finding that Weisburd (Criminology 53:133–157, 2015) has recently termed the ‘law of crime concentration at places’. Such findings suggest that the future locations of crime should—to some extent at least—be predictable. To date, methods of forecasting where crime is most likely to next occur have focused either on area-level or grid-based predictions. No studies of which we are aware have developed and tested the accuracy of methods for predicting the future risk of crime at the street segment level. This is surprising given that it is at this level of place that many crimes are committed and policing resources are deployed.

Methods

Using data for property crimes for a large UK metropolitan police force area, we introduce and calibrate a network-based version of prospective crime mapping [e.g. Bowers et al. (Br J Criminol 44:641–658, 2004)], and compare its performance against grid-based alternatives. We also examine how measures of predictive accuracy can be translated to the network context, and show how differences in performance between the two cases can be quantified and tested.

Results

Findings demonstrate that the calibrated network-based model substantially outperforms a grid-based alternative in terms of predictive accuracy, with, for example, approximately 20 % more crime identified at a coverage level of 5 %. The improvement in accuracy is highly statistically significant at all coverage levels tested (from 1 to 10 %).

Conclusions

This study suggests that, for property crime at least, network-based methods of crime forecasting are likely to outperform grid-based alternatives, and hence should be used in operational policing. More sophisticated variations of the model tested are possible and should be developed and tested in future research.

     

Examining the Relationship Between the Structural Characteristics of Place and Crime by Imputing Census Block Data in Street Segments: Is the Pain Worth the Gain?

Objective

The current study proposes unique methods for apportioning existing census data in blocks to street segments and examines the effects of structural characteristics of street segments on crime. Also, this study tests if the effects of structural characteristics of street segments are similar with or distinct from those of blocks.

Methods

This study compiled a unique dataset in which block-level structural characteristics are apportioned to street segments utilizing the 2010 U.S. Census data of the cities of Anaheim, Santa Ana, and Huntington Beach in Orange County, California. Negative binomial regression models predicting crime that include measures of social disorganization and criminal opportunities in street segments and blocks were estimated.

Results

The results show that whereas some of the coefficients tested at the street segment level are similar to those aggregated to blocks, a few were quite different (most notably, racial/ethnic heterogeneity). Additional analyses confirm that the imputation methods are generally valid compared to data actually collected at the street segment level.

Conclusions

The results from the street segment models suggest that the structural characteristics from social disorganization and criminal opportunities theories at street segments may operate as crucial settings for crime. Also the results indicate that structural characteristics have generally similar effects on crime in street segments and blocks, yet have some distinct effects at the street segment level that may not be observable when looking at the block level. Such differences underscore the necessity of serious consideration of the issues of level of aggregation and unit of analysis when examining the structural characteristics-crime nexus.

     

Effect of emergency winter homeless shelters on property crime

Objective

To evaluate the effect of emergency winter homeless shelters on property crimes in the nearby communities.

Methods

Every winter between 2009 and 2016, the City of Vancouver, Canada opened shelters to protect the homeless from harsh winter conditions. The city opened 19 shelters, but only five to nine of them were open in any one winter. Using the variation in timing and placement of the shelters, we contrast crime rates in the surrounding areas when the shelters are open and closed.

Results

The presence of a shelter appears to cause property crime to increase by 56% within 100 m of that shelter, with thefts from vehicles, other thefts, and vandalism driving the increase. However, when a homeless shelter opened, rates of breaking and entering commercial establishments were 34% lower within 100 m of that shelter. The observed effects are concentrated close to shelters, within 400 m, and dissipate beyond 400 m. Consistent with a causal effect, we find a decreasing effect of shelters with increasing distance from the shelter.

Conclusions

While homeless shelters are a critical social service, in Vancouver, they appear to impact property crime in the surrounding community. Shelters may warrant greater security to control property crime, but the data suggest that any increase in security need not extend beyond 400 m, about two to three blocks, from the shelters.

     

The Scary World of Online News? Internet News Exposure and Public Attitudes Toward Crime and Justice

Objectives

A substantial body of literature indicates that certain forms of media consumption may increase anxiety about crime and support for social controls. However, few studies have examined whether Internet news consumption is positively associated with such attitudes. The void is significant given the public’s increasing use of online news sources. This study addresses this research gap.

Methods

We draw on data from four national surveys conducted between 2007 and 2013, which collectively include interviews with more than 13,000 Americans. Using OLS and logistic regression, we assess the relationships between exposure to traditional and online media and perceptions of victimization risk, support for punitive crime policies, and views about police powers.

Results

Consistent with prior work, we find positive relationships between exposure to traditional forms of media—television news and crime programming—and anxiety about victimization and support for harsh crime policies. In contrast, Internet news exposure is generally not associated with anxieties about crime or support for getting tough on criminals. However, there is evidence of an interactive relationship between political ideology and Internet news exposure.

Conclusions

The results provide little support for cultivation theory in the context of Internet news consumption. We discuss the import of our findings, and suggest new lines of research to explore the correlates and the effects of exposure to online news sources.