Law of Crime Concentrations at Places Research Paper

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Crime is not distributed randomly across jurisdictions but instead clusters geographically. As Eck and Weisburd (1995, 12) note in their chapter on theories of crime and place, “Crime events are not uniformly distributed, a fact known for over a century. At every level of aggregation, some geographic areas have less crime than others.” This has been demonstrated historically at multiple levels of geography (Weisburd et al. 2009a), and it is a fact that is typically well recognized by even private citizens, who may characterize some locations or neighborhoods as “good” and others as “bad.” What has received less empirical attention until recently, however, is the strong concentration of crime at particular small places across cities. Places in this “micro” context are specific locations within the larger social environments of communities and neighborhoods (Eck and Weisburd 1995). Recent studies point to the potential theoretical and practical benefits of focusing research on crime places. In particular there has been a consistent finding that crime is tightly concentrated at just a small number of micro places in a city. These places are typically referred to as crime hot spots (Sherman and Weisburd 1995). They represent small geographic areas with high levels of criminal activity (typically measured by crime incidents or emergency calls for service) relative to other places in the city. This microgeographic conception of place approaches the distribution of crime with much smaller units of analysis than the neighborhoods or communities that have traditionally been of interest to criminologists studying crime and place (Weisburd et al. 2009a).

In one of the pioneering studies in this area, for example, Sherman et al. (1989) found that only 3.5 % of the addresses in Minneapolis, Minnesota, produced 50 % of all calls to the police in a single year. Fifteen years later, in a retrospective longitudinal study in Seattle, Washington, Weisburd et al. (2004) reported that between 4 % and 5 % of street segments in the city accounted for 50 % of crime incidents for each year over 14 years. These findings suggest that a focus on “good” and “bad” neighborhoods misses an important part of the story (see Groff et al. 2010). The unit of interest in understanding the distribution of crime should be much smaller in scope. A very small proportion of places in a jurisdiction are typically responsible for a substantial percentage of citywide crime.

The findings of remarkable concentrations of crime at place raise a more general question about the phenomenon of crime in cities. Is there some general law that applies across cities that dictates the general concentration of crime? This is the question raised in a recent book by Weisburd et al. (2012) entitled The Criminology of Place: Street Segments and Our Understanding of the Crime Problem. Studying crime at street segments in Seattle, they found a remarkable stability of crime concentrations each year over a 16-year period. They argue that these data, as well as prior studies showing similar concentrations of crime for specific years in other cities (e.g., see Pierce et al. 1988; Sherman et al. 1989), suggest that crime concentrations at micro places are relatively constant with about 5 % of places producing about 50 % of crime in a city each year.

The idea of a “law” of crime rates is not a new one. Emile Durkheim raised this possibility more than a century ago. Durkheim suggested that crime was not indicative of pathology or illness in society but at certain levels was simply evidence of the normal functioning of communities (Durkheim 1893 [1964], 1895 [1964]). For Durkheim, the idea of a normal level of crime reinforced his theoretical position that crime helped to define and solidify norms in society. While Durkheim’s proposition regarding a normal level of crime in society does not seem to fit recent experience and is seldom discussed by criminologists today, Weisburd et al. (2012) argue that there is indeed a “normal level of crime” in cities, but one that relates to the concentration of crime at place and not to the overall rate of crime. While the absolute levels of crime in cities vary year to year, the extent of crime concentrations remains similar. The idea of a “law of crime concentrations” will be discussed in more detail after first reviewing more thoroughly the empirical research suggesting that crime is highly concentrated at micro units of geography.

Empirical Examples Of The Concentration Of Crime

A number of studies over the past 20–30 years have found that a relatively small number of micro places are responsible for a significant proportion of total crime in a city. One of the most important early studies in this area was Sherman et al.’s (1989) analysis of emergency calls for service to addresses over a single year (December 1985–December 1986). Sherman et al. (1989) found that only 3.3 % of the addresses in Minneapolis produced just over 50 % of all calls to the police. If crime were randomly distributed across the 115,000 addresses in Minneapolis, one would not expect any places to have 15 or more calls in a single year. Instead, Sherman and colleagues (1989) found 3,841 such addresses, indicating that crime is far more concentrated than would be expected by chance. Pierce and colleagues (1988) found almost identical results when examining crime call concentrations in Boston, Massachusetts.

Weisburd et al. (1992) examined the distribution of crime in Minneapolis when aggregating address level data for a subsequent year (June 1987–June 1988) to crime hot spots of about one street block in length. Examining blocks with at least 20 hard crime (i.e., serious violent and property crime) calls for service, they found 365 hot spots in the city, which represented about 2.5 % of Minneapolis’ street segments. These streets accounted for 27.3 % of all hard crime calls for service in the city. These streets also accounted for 27.8 % of soft crime (i.e., disorder) calls for service across the 1-year period. Overall then, whether examining individual addresses or clusters of high crime addresses, crime was highly concentrated at a small number of places.

More recently, Weisburd, Telep, and Lawton (in press) found high rates of concentration when examining crime incidents in New York City in 2009 and 2010. About 77 % of total incidents were geocoded to street segments. Approximately 52 % of the incidents on street segments were found in the top 5 % of street segments both years. Just under a quarter of crime incidents were found at 1 % of the street segments. Similar concentrations were found when examining incidents geocoded to intersections. About half of incidents at intersections were found at the top 5 % of the intersections, while slightly more than 20 % were found at the top 1% of intersections. Between 55 % and 60 % of the street segments and intersections each year had no crime incidents.

Weisburd and Amran (forthcoming) found similarly high rates of the concentration of crime at place when examining crime incidents at street segments in 2010 in Tel Aviv-Jaffa, Israel. One quarter of all incidents were found at just 0.9 % of the street segments in the city, and 50 % of incidents were located at about 4.5 % of total street segments. About 60 % of street segments in the city did not experience any crime incidents in 2010. These findings suggest the broad application of the “law of concentrations” for crime at place. Even in a jurisdiction thousands of miles from the United States, similar levels of crime concentration were found.

Spelman (1995) offers some words of caution about the use of cross-sectional data in analyzing the concentration of crime at place (see Eck and Weisburd 1995). He examined calls for service at schools, public housing projects, subway stations, and parks and playgrounds longitudinally in Boston. He found evidence of a high degree of stability of crime at the “worst” of these places over a 3-year period. While the top 10 % of public places in terms of crime were responsible for about 30 % of calls for service (see also Eck et al. 2000), he notes that “Much of the concentration of crime among locations is due to random and temporary fluctuations that are beyond the power of the police and the public to control reliably” (Spelman 1995, 142). Thus, even though many of the highest crime places remained high crime, some of the change over time reflected random variation, suggesting the importance of longitudinal approaches to the study of crime at place. Despite these cautions, Spelman (1995) still advocated for efforts such as community problem-solving to address underlying problems at persistent high crime locations.

More recently, two studies in Seattle have examined the distribution of crime at street segments using a much longer time series. Weisburd et al. (2004) not only confirmed the concentration of crime but also the stability of such concentrations across a long time span. Weisburd et al. (2004) examined street segments in the city of Seattle from 1989 through 2002. They found that 50 % of crime incidents over the 14-year period occurred at between 4 % and 5 % of the street segments each year. This concentration was also very stable year to year.

Weisburd et al. (2012) updated and expanded these analyses, examining crime incidents at street segments in Seattle from 1989 to 2004. They again found that crime was highly concentrated and these concentrations remained fairly stable across the time period under study. They found that each year 50 % of crime incidents occurred on between 4.7 % and 6.1 % of street segments (see Fig. 1). All crime was found on around 60 % of street segments each year, suggesting that about 40 % of street segments recorded no crime each year in Seattle. The 247 highest crime street segments, about 1 % of the total in Seattle, were responsible for over 23 % of crime incidents across the 16-year period. Crime was even more heavily concentrated when examining a smaller proportion of citywide crime. For example, in the year 2000 in Seattle, just 11 street segments out of over 24,000 in total were responsible for 5 % of crime in the city, and only 31 streets produced over 10 % of the crime incidents.

Law of Crime Concentrations at Places Research Paper

These strong crime concentrations remain when focusing on specific types of offenders or crimes. For example, Weisburd et al. (2009b) examined the concentration of crime incidents in which a juvenile was arrested in Seattle. They found even stronger levels of concentration than for crime incidents more generally. Less than 1 % of street segments were responsible for 50 % of juvenile arrest incidents each year from 1989 to 2002. Only 86 street segments accounted for one third of all official juvenile arrest incidents over the 14-year period. As another example, Weisburd and Mazerolle (2000) examined the number of calls for service in 56 drug hot spots in Jersey City, New Jersey, that made up about 4.4 % of the street segments and intersection in the city. About half (47 %) of both narcotics arrests and calls for service were found in these hot spots, suggesting the strong concentration of drug activity in Jersey City.

In Boston, Braga et al. (2010) found that just 4.8 % of the street segments were the site of 73.9 % of all gun assaults over a 29-year period. Braga et al. (2011) also examined the concentration of robbery incidents at street segments and intersections in Boston from 1980 to 2008. Each year, about 2 % of street units accounted for 50 % of the robbery incidents in the city. The top 52 street units, which represented just 0.18 % of total units in the city, were responsible for 10,886 of the 135,276 robberies (8.0 %) over the 29-year period. Commercial robberies are even more highly concentrated than street robberies. From 1980 to 2008, just 1.3 % of street segments were responsible for about half of commercial robberies. In Minneapolis, Sherman et al. (1989) found that the 54 addresses (about 0.047 % of the total addresses in the city) that had at least ten calls for service for public predatory crime (a combination of robbery, auto theft, and rape) were responsible for over 7.5 % of all such calls.

These trends for specific crime types are once again consistent when looking at data from outside the United States. Andreson and Malleson (2011) examined the distribution of calls for service for seven offense types in Vancouver, Canada, in 1991, 1996, and 2001. They found that for each crime type, 50 % of calls were found on between about 1 % and 8 % of street segments. Burglary showed the lowest level of concentration, although in 2001, for example, 50 % of burglary calls were on 7.61 % of street segments and only 39.43 % of streets had any burglary calls. Robbery was incredibly concentrated in Vancouver. In 2001, 50 % of robbery calls were found on just 0.84 % of street segments in the city, and only 5.32 % of streets had any robbery calls.

Sherman (1995) argues that such clustering of crime at places is even greater than the concentration of crime among individuals. Weisburd et al. (2004) found that 5 % of streets produced 50 % of crime throughout the 14-year study period. In Wolfgang et al.’s (1972) groundbreaking Philadelphia, Philadelphia birth cohort study, they found that 6 % of the cohort produced 50 % of the offenses committed by the cohort. While these statistics seem similar, 6 % of a city’s population is likely to yield thousands of targets, while 5 % of street segments in a city like Seattle is only around 1,500 places. And those places are not “moving” targets for police since they stay in the same place. This suggests that focusing on places may be more efficient than focusing on people (Weisburd and Telep 2010). As Sherman (1995, 37), “Why aren’t we thinking more about wheredunit, rather than just whodunit?” Importantly, Weisburd and colleagues (2012) also found that the micro place concentrations in Seattle were not just proxies for neighborhoodlevel effects (see also Groff et al. 2010). While they did find some evidence of larger area effects in their analyses and some clustering of high crime streets, particularly in the Central Business District, their overall conclusion was that there is a great deal of street-by-street heterogeneity in crime patterns. In other words, crime hot spots can be found throughout the city, and so there is a great deal of variability street-to-street within both “good” and “bad” neighborhoods.

A Law Of Crime Concentrations

These findings about the concentration of crime are particularly interesting in light of Emile Durkheim’s classic proposition that the level of crime is stable in society or rather that there was a “normal level” of crime in society. For Durkheim, this meant that crime was not necessarily an indication of an illness or pathology in society but rather that healthy societies would inevitably have some normal level of crime. Crime waves and crime drops in this context can be seen as the result of some “abnormality” in a society that results from crisis or dramatic social change.

Underlying Durkheim’s proposition was his understanding of crime as a product of social definition. Kai Erickson (1966) was to build upon this idea in his classic study Wayward Puritans, where he sought to show that the definition of crime had a social function. By defining others as deviant, society can help draw the boundaries between acceptable and unacceptable conduct (see also Adler and Adler 2009). Defining people as criminal in this sense serves a function in defining the moral boundaries of society. One can know the boundaries of acceptable behavior by observing “deviants” who are sanctioned for violating societal norms.

Crime rates over the last few decades would seem to strongly contradict Durkheim’s conception of normal levels of crime in society. Between 1973 and 1990, violent crime doubled, and then in the 1990s, the USA experienced a well-documented “crime drop” (Blumstein and Wallman 2000). In the 1970s, Blumstein and Cohen (1973) hypothesized that Durkheim’s proposition could be applied to punishment in America, where imprisonment rates had remained static for a long period of time. But recent dramatic increases in the US incarceration rate in the 1980s and 1990s would seem inconsistent with the normal crime or “normal punishment” (Blumstein and Cohen 1973) hypothesis.

Weisburd et al. (2012), however, take a different approach to Durkheim’s theory and instead argue that there is indeed a “normal” level of crime in cities, but one that relates to the concentration of crime at place and not to the overall rate of crime. They claim that a different proposition from Durkheim’s can be raised at this juncture and should be examined in future studies. There appears to be a “law of concentrations” of crime at place. The consistency of crime concentrations at micro places over time and across geographic locations as diverse as Minneapolis, Minnesota, and Tel Aviv-Jaffa, Israel, suggests that there is some underlying social process pushing crime to certain levels of concentration in modern cities.

What might lead to this stability? It is important to note at the outset that the concentration of crime follows patterns of concentration in many other areas of scientific inquiry (e.g., see Eck et al. 2007; Koch 1999; Sherman 2007). Joseph Moses Juran (1951) first noted this concentration in looking at economic activities, coining the phrase “the vital few and the trivial many.” Juran sought to emphasize to managers that they should focus on the small number of events or cases that produce the majority of relevant business activities, for example, the small number of defects that cause most complaints about products or the small number of clients that are responsible for a majority of revenue. Juran termed this phenomenon the “Pareto Principal” after Vilfredo Pareto (1909), who first brought attention to what is sometimes referred to as the 80-20 rule (see Koch 1999). Pareto observed that a number of distributions seem to follow this specific pattern of concentration. For example, in studying land ownership in Italy, he found that 80 % of the land was controlled by just 20 % of the population. He also observed that 20 % of the pea pods in his garden produced 80 % of the peas. The 80-20 rule is generally seen only as an approximation, but it applies fairly well to Weisburd et al.’s (2012) data in Seattle. Eighty percent of the crime incidents each year were found on between 19 % and 23 % of the street segments. Of course, the question remains, what leads to the tremendous concentration and stability of crime at microgeographic places over time?

In their discussion of the concentration of crime at facilities, Eck and colleagues (2007) discuss how crime follows the J-curve pattern found in a number of other phenomena. As they describe, “To reveal a J-curve, the number of crimes in a given time period at each facility needs to be known, and then the facilities ranked from those with the most crimes to those with the fewest. If a bar chart of the crime frequency is drawn, a few facilities at the left end of this distribution will have many crimes, but as one moves to the right there will be a steep drop-off in crimes that flattens out at a very few or no crimes for the majority of the facilities. The resulting graph resembles a reclining J” (Eck et al. 2007, 228). The words “micro place” can easily be substituted for “facilities.”

They point to five potential reasons why crime might be concentrated at particular facilities, which are relevant to consider when understanding the concentration of crime at micro places. The first was noted above; some portion of the concentration can be explained by random variation. That is, some hot spots of crime would likely cool off without any intervention. Random variation, however, is not the whole story, as Weisburd et al. (2012) demonstrated by showing that the hottest street segments in Seattle remained high crime throughout the 16-year study period. A second explanation is changes in reporting processes. If the police changed their crime incident reporting protocols, for example, this could have some impact on the level and concentration of crime, although again this does not explain the stability of concentration in Seattle, which experienced no major change in reporting patterns from 1989 to 2004.

The last three potential explanations focus on the characteristics of particular facilities (or places). Eck and colleagues (2007) point to offenders, targets, and place management as potential reasons why some facilities may be riskier than others. Some places may be crime attractors if they tempt potential offenders with rampant opportunities for criminal activity. Places can also be rich in targets and be crime generators. Finally, poor place management (i.e., a lack of supervision and guardianship) can be a crime enabler. Examining the characteristics of places was the focus of Weisburd et al.’s (2012) research in Seattle, and they demonstrated that crime opportunity factors play a key role in explaining the concentration of crime in hot spots. These factors are important for understanding why some places become hot spots, but they do not necessarily explain why such a small number of hot spots are responsible for such a high percentage of crime citywide.

Can Durkheim’s initial insights also be used to consider possible reasons for this law of concentrations of crime at place? Following Durkheim and other theorists that built on his work, one would look to the role of crime at place in defining normative boundaries in society. In this case, it could be argued that a certain number of places in the city with severe crime problems serve as lessons for the city more generally. This would fit well with the finding by Weisburd et al. (2012) that crime hot spots are found throughout the city. Accordingly, everyone would have direct visceral experiences with the “bad places” in the city, and perhaps that serves to define the “moral boundaries” of place for individuals. The normal level of crime concentrations in this context would relate to the proportion of problem places that are needed to bring the lessons of moral boundaries to the city’s residents.

Another possible explanation for a law of concentrations comes from the concentration of other characteristics of places in the city. For example, Weisburd et al. (2012) note that the concentration of bus stops or number of public facilities, like crime, stays relatively stable over long periods. Perhaps the law of concentrations of crime is related to the overall distribution of social and environmental characteristics of places in cities. Does the stability of patterns of business and employment in a city, for example, reflect more general patterns of concentration that are related to the growth and development of urban areas? Cities regulate such concentrations, by defining commercial, business, and industrial use of property. Perhaps the normal concentrations of crime are simply a reflection of the normal concentrations of other social activities in the city. The law of concentrations of crime at place may simply be a reflection of a more general law of the stability of concentrations of specific aspects of social and economic life in the city, as discussed above with Juran’s (1951) notion of the Pareto Principle.

But this brings the discussion back to Durkheim, because crime is a social phenomenon and its tolerance is a social construct. Is society willing to tolerate crime at only a certain proportion of the landscape of a city? Is the law of concentrations a result of the boundaries of crime at place that citizens are willing to tolerate? Will people become worried and call for action when crime hot spots increase beyond a specific proportion of places in the city, and will they become more lax when the concentrations are below that level? Certainly, this law of concentrations needs to be studied across other metropolitan centers around the world to see how widely it applies. More generally, it is time for scholars to explore more directly the explanation for the law of concentrations of crime trends at micro places. In the spatial context, scholars should explore both social and environmental characteristics of street segments that are important to understanding the concentration of crime at place.


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