Criminal Careers of Places Research Paper

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Though both individuals and places have long been the foci of criminological research, the majority of criminological research focuses on individual criminal involvement (Reiss 1986). As a result, criminologists often assume that places play a relatively minor role in explaining crime compared to an individual’s criminal propensity. In fact, there has been a long history of studying of crime at places dating back to the nineteenth century.

In the recent decades, there has been a gradually increasing interest in academia to study crime at places. Particularly, research has focused on the distribution of crime across geographic places as well as the explanatory factors of crime at places (Weisburd et al. 2012; Sampson et al. 1997). To provide an overview for the recent development, this research paper reviews literature related to crime concentration, longitudinal crime rates at places, and empirical findings as well as challenges faced when studying the criminal career of places.

Among studies of crime distributions at places, one of the most well-known and widely agreed-upon findings is the concentration of crime at a small number of places. The earliest work known to demonstrate this empirically was from French scholar Michel-Andre´ Guerry and the Venetian cartographer Adriano Balbi. They published three maps on the distribution of crime in France in the years 1825–1827. In 1833 the influential Essai sur la statistique morale de la France was published, in which Guerry examined whether poverty and density of population might explain higher crime rates (Guerry 1833). His map shows clear patterns of differential concentration patterns of crime. The rich northern departements were confronted with higher property crime rates than the poor departements in the south of France. He concluded that the level of poverty was not the direct cause of crime. Similarly, his data suggested that population density was not a cause of crime. In 1836 his friend Alexandre Parent-Duchaˆtelet published an empirical study containing maps on the distribution of prostitution from 1400 until 1830 in Paris (Parent-Duchaˆtelet 1836). Because of the official control of brothels by the Paris authorities, systematic data were available on prostitutes, especially from the years 1817 to 1827. Even information regarding the departements where they came from was collected. Not surprisingly, the center of the city had the highest number of prostitutes. He used neighborhoods, as defined by administrative boundaries, as the unit of analysis.

Other scholars also studied these issues in the 1830s. Most notably, the work of Adolphe Quetelet (1831[1984]) examined crime rates across provinces and countries in France and found that places with higher property crime rates tended to be wealthier. He pointed out on his maps that crimes, just like wealth, are not distributed equally across places. Guerry and Quetelet could be considered as pioneers of crime and place research, and their works set the stage for later theorizing linking crime and place.

Almost 100 years after the work of Guerry and Quetelet, in a classic study of juvenile delinquency, Shaw and McKay examined the residential locations of juvenile offenders and then pinned the addresses on a big map of the city of Chicago (Shaw and McKay 1942). The geographic distributions of those addresses showed clear clustering patterns in their residential locations. Through their close observations and explorations of the city, Shaw and McKay concluded that not all areas were plagued with the same amount of crime. The so-called transition zone outside of the center of the city had the highest amount of crime in the whole city. Specifically, places with higher juvenile crime rates tended to be closer to the center of the city, disorganized, occupied by the poor, and also possessed other social illnesses. Moreover, Shaw and McKay (1942) argued that as long as the structural factors of a place, such as poverty, racial heterogeneity, urban decay, and population turnover rates, remain stable, crime rates will as a result also remain stable over time.

Despite the preponderant evidence found on the stability of crime places, others have found that crime rates do change under certain circumstances. For example, the argument that crime remains stable in Chicago was challenged by studies done in later years (Bursik and Webb 1982). Specifically, Bursik and Webb reanalyzed crime rates in Chicago neighborhoods with an extended dataset compared to the original one used by Shaw and McKay and found that the stability of crime in Chicago was purely a historical artifact. Crime rates in Chicago started to fluctuate after WWII. The lack of empirical credibility, the focus on individuals as the center of study, and other theoretical flaws contributed to the decline of the traditional social disorganization theory formulated by Shaw and McKay. However, in the 1980s a group of young scholars led by Albert Reiss started to take a new interest in the study of crime places, rather than individuals. Editing an early volume in the Crime and Justice series, Reiss and Tonry (1986) sought to bring Communities and Crime to the forefront of criminological interests. Reiss sought to raise a new set of questions about crime that had been ignored in earlier decades: “Recent work on communities and crime has turned to an observation that Shaw and McKay neglected: not only do communities change their structures over time but so often do their crime rates … a recognition that communities as well as individuals have crime careers” (Reiss 1986, p. 19). Work developed in this period drew upon the identification of neighborhoods and communities to expand insights about the development of crime (Bursik and Webb 1982; Clarke 1983).

Sampson (1993) also pointed out the importance of linking time and place in the study of crime. Criminology had been dominated by methodological individualism; as such, the understanding of crime had been decontextualized. Putting crime back to its place has then become salient for a more holistic understanding of crime. Another major problem was the lack of a temporal perspective, as well as the availability of longitudinal data, in crime and place research. Without taking into account the actual sequence of actions, it is not possible to understand the causal mechanisms behind the phenomenon (Sampson 1993, p. 430). To address this issue, Sampson argues that communities have “careers” in crime, and longitudinal study is needed to disentangle changes in crime rates in communities (see also, Reiss 1986). The initiative to refocus criminological inquiries at places has led to two different but tightly linked tracks of study examining crime at places. The first line of research focuses on the hot spots phenomenon that examines stability of crime across geographic units to identify where the concentration of crime locates. The second line of research moves one step further and focuses on tracing the trajectories of crime trends of places over time.

Crime Concentration At Places

Crime concentration has been found in many studies across different places at different geographic levels. Early research done by Guerry, Quetelet, and Shaw and McKay clearly demonstrated that crime was concentrated in a few places. In more recent years, the research findings on crime concentration and the empirical findings about hot spots of crime enhanced development of theoretical ideas about crime distribution at places. The introduction of new theoretical ideas, such as situational crime prevention (Clarke 1983), routine activities theory (Cohen and Felson 1979), environmental criminology, and crime pattern theory (Brantingham and Brantingham 1984), invited people to explore the linkage between crime and places. At the same time, the popularity of personal computer and the affordable mapping software allow for timelier and more in-depth crime analysis to visualize the concentration patterns of crime for both researchers and practitioners. This theoretical development and technological advancement jointly promoted the research of crime at place.

Subsequent research continued to identify high-crime neighborhoods within cities (Bursik and Webb 1982; Sampson and Groves 1989). The concentration of crime has been found at various geographic levels, not just the neighborhood level. The law of concentration also applies to specific types of “places.” Spelman (1995) examined calls for service at public places such as schools, housing projects, subway stations, parks, and playgrounds, over a 4-year time period in Boston. Analysis results showed that there were strong place-to-place variations on crime and disorder rates. Specifically, the worst 10 % of public places were responsible for about 30 % of crime. In addition to the concentration of crime, Spelman also found that long-run risks at places remained quite stable and explained a substantial amount of variation in citizen’s calls for service. Concentration patterns have also been observed in “high-risk” places such as bars/taverns. For example, Sherman et al. (1992) examined tavern crimes in Milwaukee and found that as few as 15 % of taverns in the city accounted for more than 50 % of the crimes that occurred in all taverns.

The extent of concentration is even more salient at small geographic areas like addresses and places, than in larger aggregations of geography such as neighborhoods or census tracts. In one of the pioneering studies in this area, Lawrence Sherman and colleagues found that the majority of citizens’ calls for service were generated by about 3 % of addresses in Minneapolis, Minnesota.

Fifteen years later, using street segments as the unit of analysis, Weisburd et al. (2004) demonstrated similar concentration rates in Seattle, WA. That is, about 4–5 % of street segments accounted for about 50 % of all crime each year. This percentage remained quite stable during their 14-year observation period. Using 16 years of data and adding refinement to the definition of street segments, Weisburd et al. (2012) analyzed extended data from Seattle and reconfirmed the concentration of crime at the street-segment level. In Seattle, over 9 % of the segments did not evidence a single crime incident over this 16year period. Consistent with the Pareto Principle (a.k.a. the 80–20 rule), they found that 80 % of crime incidents were found on between 19 % and 23 % of segments across their study period, while 100 % of incidents fell on between 60 % and 66 % of segments in a given year. Another study by Weisburd and Amram (forthcoming) found that 5 % of the street segments in Tel Aviv were responsible for 50 % of the crime incidents, a statistic remarkably similar to the results from Seattle. These studies and others (Brantingham and Brantingham 1984; Clarke 1983) have established crime places as an important focus of criminological inquiry and practical crime prevention.

The concentration of crime at “hot spots” is also observed for specific crime types. Braga et al. (2010) examined gun crimes in Boston and concluded that street segments and intersections account for less than 5 % of the total streets in the city but had over 75 % of gun violence incidents within them. Additionally, Weisburd and Mazerolle (2000) found that approximately 20 % of all disorder crimes and 14 % of crimes against persons were concentrated in just 56 drug-crime hot spots in Jersey City, New Jersey, an area that comprised only 4.4 % of street segments and intersections in the city. Similarly, Eck et al. (2000) found that the most active 10 % of places (in terms of crime) in the Bronx and Baltimore accounted for approximately 32 % of a combination of robberies, assaults, burglaries, grand larcenies, and auto thefts. Finally, examining juvenile arrests over a 14-year period, Weisburd et al. (2009) also found an extreme concentration rate – 3–5 % of street segments were responsible for all juvenile arrests during any given year. In short, the findings from studies provide strong support for the idea of a “law of concentrations” for crime at places.

To date, the available empirical evidence clearly shows that crime does not randomly distribute across places. Rather, research has found that a small number of places contribute a disproportionate share of crime. This finding echoes the results from the famous Philadelphia Cohort Study, in which Wolfgang et al. (1972) found that less than 6 % of individuals were responsible for more than 50 % of the arrests. The comparison result led Sherman to argue that future crime is “six times more predictable by the address of the occurrence than by the identity of the offender” (1995, pp. 36–37). He then asked “why aren’t we doing more about it? Why aren’t we thinking more about wheredunit, rather than just whodunit?” As such, many scholars proposed the need to study of crime places using criminal career perspective.

Stabilities And Changes Of Crime At Places

Following the tradition of Chicago school, scholars like Robert Bursik and his colleagues started to focus on how crime develops in communities. Specifically, some scholars began to apply the concepts drawn from the criminal career paradigm to examine whether places, just like individuals, also have “criminal careers” (Reiss 1986, p. 19; Sherman 1995). For example, Schuerman and Kobrin (1986) applied a dynamic model to explaining neighborhood crime characteristics over time. Recognizing the importance of understanding developmental crime trends, Sherman (1995) pointed to the relevance of the criminal career paradigm to the study of longitudinal crime rates at micro places. Other important concepts have also been borrowed from the criminal career paradigm to study the onset, continuity, specialization, and desistance of crime at places (Spelman 1995).

Among the research of crime at places, stability of crime trends is the most common finding across different geography. For example, Griffiths and Chavez’s (2004) study of Chicago neighborhoods also found support for the argument that places might follow very different trajectories with regard to homicide trends between 1980 and 1995. Specifically, they found that different neighborhoods exhibited different homicide trends – some had stable trajectories, some had increasing trends, while others had experienced high number of homicides. But the majority of the neighborhoods demonstrated stable homicide trends, while a smaller percentage of neighborhoods showed high increasing homicide rates during the same time.

The stability of crime at places is also found at smaller geographic units. Weisburd and colleagues applied the criminal career concepts to examine stability and changes in crime rates of street segments in Seattle, WA (Weisburd et al. 2004, 2012). Specifically, Weisburd et al. (2004) found chronic hot spots and chronic cold spots of crime over 14 years of analysis.

With additional 2 years of data, (Weisburd et al. (2012)) reconfirmed the previous findings using group-based trajectory analysis (see Nagin and Land 1993) to classify street segments into different trajectory groups based on their levels and directions of crime trends. They found 22 distinct groups of street segments following different developmental trends. Out of the trajectory groups, almost half of the street segments (49.6 %) were classified into the “crime-free” trajectory group as they had crime counts at or near zero for every year of the study. The second biggest trajectory group was trajectories that featured with “low stable” crime trends. Totally, 32 % of street segments with relatively low crime rates that remained stable over the 16-year study period were classified into this category. The next category was the “moderate stable” trajectory that had a moderate crime rate that was flat over time and contained 1.2 % of the street segments in Seattle. Importantly, the stability of crime is not limited to low-crime places. In fact, they also found that about 1 % of street segments, the “chronic high” trajectory, evidenced a stable high crime rate over time. Despite the nationwide crime drop observed in the early 1990s, those places continued to experience high crime problems over that period of time. In sum, Weisburd et al. (2012) found that over 80 % of streets in Seattle had extremely stable crime patterns over time. Though the hot spots phenomenon has been supported by numerous studies, this was the first time research was able to empirically demonstrate the long-term stability of hot spots (and cold spots) at such a micro level of geography.

The extent of stability of crime trends is astonishing over such a long period of time. Nonetheless, they also found places with fluctuating crime rates. Consistent with the crime drop phenomenon across the US cities through the 1990s and early 2000s, they found places that experienced declines in crime. The “low-rate decreasing” category accounted for 9.3 % of segments that had relatively low crime rates which evidenced declines in crime. The “high-rate decreasing” group contained 2.4 % of segments that had high rates which decreased over time. While most segments remained stable or experienced crime drops over this period, there were some segments which experienced crime spikes over the study period. In the city of Seattle, about 3.8 % of street segments featured “low increasing” crime rates, while another 0.9 % of segments experienced “high increasing” crime rates over the 16-year period.

The findings from Weisburd et al. (2012) produced two major conclusions about criminal career of places. First, crime is not only concentrated at small places, these “hot spots” remain stable across time. In fact, the majority of places feature extremely stable crime patterns longitudinally. This means that crime prevention practitioners can focus their resources on relatively few crime hot spots and deal with a large proportion of the crime problem. Importantly, places are not “moving targets.” Place-based crime prevention provides a target that “stays in the same place.” Thus, crime prevention policies targeting high-risk places could be beneficial. Secondly, despite the stability and continuity of crime rates at most places, there is still a great deal of variability across street segments over time in Seattle. Thus, it is important to understand factors that determine the changes in crime at those places.

What Factors Predict Crime Change?

While scholars have provided a strong empirical basis for the assumption that crime is strongly clustered at crime hot spots and that there are important developmental trends of crime at place, existing research provides little insight into the factors that underlie these patterns. For example, we could identify only three prior published studies that specifically examined developmental patterns of crime at micro places over time. One study conducted by Spelman (1995) looked at specific places such as high schools, public housing projects, subway stations, and parks in Boston, using 3 years of official crime information. Taylor (1999) examined crime and fear of crime at 90 street blocks in Baltimore, Maryland, using a panel design with data collected in 1981 and 1994. These studies are limited only to a small number of locations and to a few specific points in time. To provide a comprehensive examination of risk and protective factors that could affect the developmental patterns of crime at places, Weisburd et al. (2012) collected 25 data sources which represented key concepts from two major place-based theoretical perspectives – social disorganization theory and opportunity theory. They examined relationships between the developmental crime patterns derived from group-based trajectory analysis and social disorganization and opportunity variables. The explanatory power between variables was compared and contrasted to identify important risk and protective factors in explaining specific development processes of crime at place. Multinomial logistic regression was used to compare the two most distinct crime places, the crime-free places versus the chronic-crime segments, and see what factors best distinguish between the two places. The following sections report on findings from a comprehensive study done by Weisburd et al. (2012).

Opportunity Measures And Crime Hot Spots

The importance of opportunity theories for understanding crime at place has a long history in criminology (Brantingham and Brantingham 1984; Clarke 1983; Cohen and Felson 1979). A focus on crime naturally leads scholars to specific places or situations and the opportunities that situations and places provide for crime. Based on opportunity theory, the key elements of the crime triangle are motivated offenders, potential targets, and capable guardians (Cohen and Felson 1979).

To test the validity of opportunity theory in predicting crime trends at places, Weisburd and colleagues applied the theoretical framework to the Seattle data and found a general support for the theory. Firstly, an increase in motivated offenders, as represented by an increase in high-risk juveniles on a street segment, has a strong and significant impact on the likelihood of the street segment being classified into the high-rate chronic hot spots pattern. Indeed, for every additional high-risk juvenile found on a street segment, the likelihood of being in this group as opposed to the crime-free group more than doubles. A positive change over time in the number of high-risk juveniles on a street segment also increases the likelihood of being a chronic-crime pattern street segment. Of course, the fact that high-risk juveniles on a street increases crime risk does not mean that these juveniles are the culprits. It may be their friends who commit crimes on the street in the course of their routine activities (possibly visiting the high-risk juveniles who live on a particular street segment).

Secondly, with all else being equal, it would be expected that as the number of suitable targets increases, the number of crimes would also increase. Weisburd and colleagues used four measures to capture the number and attractiveness of targets on a street segment: employment, public facilities, residential population, and retail business sales. The results show that employment is the single most important variable in explaining the likelihood of a street falling in the high chronic-crime group as opposed to the crime-free group. For every additional employee on a street segment, the odds of falling in this pattern increase by 8 %. The change in number of employees over time also has a strong and significant impact in the same direction, though of a somewhat smaller magnitude. The presence of public facilities within a quarter mile of a street segment also significantly increases the probability of being in the chronic-crime-trajectory pattern. Having a public facility such as a community center, park, library, middle or high school, or a hospital within a quarter mile increases the likelihood of being in the chronic-crime group (as contrasted with the crime-free group) by almost 25 %.

Residential population also has a very strong impact on the likelihood of being a crime hot spot in the data. As would be expected by opportunity theory, the larger the residential population, the more likely a street segment is to be in the chronic-crime group. In contrast, the measure of retail sales was not statistically significant in predicting street segments to be in the chronic high group. It may be that the amount of retail sales does not reflect the number of patrons or visitors to the street or that after accounting for employment, public facilities, and residential population, most of the variability has been captured on street segments. Nonetheless, the presence of suitable targets as indicated by employees, facilities, and residential population is a key factor in explaining crime hot spots.

The findings for guardianship, however, are less clear. Guardianship was measured by the existence of a police or fire station within a quarter of a mile of a street segment. Another common measure used in the situational crime prevention research is street lighting, which was measured by wattage. However, both measures of guardianship reached statistical significance, but not in the expected direction. The presence of a police or fire station increases the likelihood of a street segment being in the chronic-crime pattern. Additionally, more wattage of lighting on a street is associated with a higher likelihood of being a crime hot spot. Weisburd et al. argue that these inconsistent findings could be a result of the fact that the presence of police/fire station and high wattage lighting are both more likely to be found in areas with higher population density. Moreover, it is also possible based on situational crime prevention theory that having a police station, or increased street lighting, in location with more crime problems were responses to higher crime rates. Thus, the findings could be spurious and confounded with population density or prior crime problems.

In addition to the key elements of opportunity theory, it is also found that accessibility and urban form, like types of street, are significant variables in predicting that a street segment will be a crime hot spot. For example, the number of bus stops and arterial roads both increase the likelihood of being in the chronic-crime group as contrasted with the crime-free group.

Social Disorganization And Crime Hot Spots

As mentioned earlier in this research paper, social disorganization theory is another major theoretical approach for the study of places. A series of variables reflecting structural components of social disorganization have been tested in the past, including socioeconomic status, population heterogeneity, mobility, and female-headed households. A neighborhood that is poor, more disadvantaged, heterogeneous in terms of racial or ethnic composition, and more urbanized tends to be more vulnerable to crime and other social problems. Using the Seattle data, Weisburd et al. (2012) tested social disorganization theory at the street-segment level to see whether the core theoretical concepts help predict chronic-crime places. They found that socioeconomic status represented by the value of residential property on a street segment and the amount of housing assistance is both strongly and significantly related to a street segment falling in the chronic-crime group.

The other two structural dimensions reflecting social disorganization were mixed land use and racial heterogeneity. However, both of these measures were not statistically significant in differentiating between the chronic-crime and crime-free groups. In terms of the extent of urbanization, it was captured by the distance of the street away from the city center. It had an overall impact on predicting crime, in that areas closest to the center of the city had the highest crime rates. These were the areas where new immigrants and poorer residents were concentrated, where social control was weak, and juvenile delinquency and crime problems would accordingly be concentrated. In addition to those structural characteristics, Weisburd et al. also included description of physical conditions in the model. Physical disorder such as litter, trash, graffiti, and abandoned cars are the most direct indicators of social disorganization (Shaw and McKay 1942[1969]), and its relationship to developmental trajectories of crime at street segments is very strong. A street segment is much more likely to be in the chronic-trajectory pattern as opposed to the crime-free pattern if it has higher reports of physical disorder incidents. Additionally, increases in physical disorder are also positively associated with higher likelihoods of being in the chronic-crime trajectory.

Recent conceptualizations of social disorganization theory draw distinctions between the structural characteristics of areas and the mediating factors that connect the structural factors and outcome variables like crime (see Bursik and Grasmick 1993; Sampson et al. 1997; Sampson and Groves 1989). The strength of social ties among residents, also called social capital, determines the extent to which social control functions in areas. Different measures identified in prior studies have been used to conceptualize the intermediating mechanism including participation in local organizations (Sampson and Groves 1989), willingness (or perception of responsibility) to intervene in public affairs (Sampson et al. 1997), local friendship networks (Sampson and Groves 1989), mutual trust (Sampson et al. 1997), and unsupervised teens wandering on the street (Sampson and Groves 1989; Sampson et al. 1997). These factors are believed to condition the effects of structural disadvantage on local crime problems.

The empirical validity of these measures has been tested in many studies. However, Weisburd and colleagues (2012) were first to test the idea at the micro geographic level over a long period of time. Based on the data, they found that truant juveniles on a street segment significantly increased the likelihood of it being in a crime hot spot, while high level of collective efficacy (as measured by percentage of active voters) decreased the chance of a place being a crime hot spot. It seems, accordingly, that the more involved the residents are in public affairs, the less likely the streets are to have chronic-crime problems. Thus, social control could be built at street level to reduce the crime problem.

Conclusion

Overall, research has found that crimes are clustered in a small number of places, regardless of the geographic unit of analysis examined. The “hot spots” phenomenon suggests that we could identify and deal with a large proportion of crime problems by focusing on just a very small number of places. In addition to the concentration of crime, recent studies have found that crime hot spots remain very stable over time. However, despite the preponderant evidence for crime stability at places, other scholars have also identified a smaller proportion of places with changing crime rates (Griffiths and Chavez 2004; Weisburd et al. 2004, 2012). These studies find that changes in social characteristics and contextual factors can also lead to change in crime rates at places. Specifically, social disorganization theory and opportunity theory are both relevant in predicting crime at places. For example, the number of residents, unsupervised teens wandering the streets, the more (or less) committed citizens are to public affairs, and having more potential crime targets in an area all determine the occurrence of crime at any given place.

Another recent development of place-based criminology is the emphasis on studying micro geographic areas like addresses or street segments, rather than larger geographic units such as communities, neighborhoods, or census tracts. Weisburd et al. (2012), Braga and colleagues (2010), Taylor (1999), and other scholars have demonstrated a stronger crime concentration effect at micro places and have thus argued that focusing on micro places could be promising and more efficient for crime prevention efforts.

Crime at place is very predictable, and therefore, it is possible not only to understand why crime is concentrated at place but also to develop effective crime prevention strategies to ameliorate crime problems at places. Criminologists and crime prevention practitioners can identify key characteristics of places that are correlated with crime. At a policy level, it is important to focus on initiatives like “hot spots policing” that address specific streets within relatively small areas. If police become better at recognizing the “good streets” in the bad areas, they can take a more holistic approach to addressing crime problems.

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