A spatial analysis of green teams: a tactical response to marijuana production in British Columbia

Over a period of 4 years (1997–2000), British Columbia (BC) experienced tremendous growth in the illicit production and distribution of domestically grown marijuana. By the close of 2000, each policing jurisdiction in BC had adopted a particular policy in response to grow operation proliferation. In summary, four policy responses were noted. First, some maintained the status quo wherein enforcement of police initiated investigations and citizens’ tips continued, but with no additional resources specifically dedicated to grow operations. Second, some jurisdictions suspended the majority of investigation and enforcement of grow operations. Third, some agencies implemented or reinforced existing resource intensive drug squads, which focused on trafficking, sales and production of all types of drugs. Finally, some of the jurisdictions formed specialized tactical units known as “green teams” that focused solely on the enforcement of marijuana production. In this paper, we evaluate the effectiveness of green teams using a Geographic Information System (GIS) and difference-in-difference estimates. The results indicate that green teams decrease grow operations within their target area without significant displacement to surrounding areas.

Birds of a Feather Fight Together: Status-Enhancing Violence,Social Distance and the Emergence of Homogenous Gangs

Objectives

This study proposes a theoretical framework for understanding two empirical findings from gang research: (1) gangs are generally racially homogenous, even in heterogeneous environments, and (2) gang violence tends to be intra-racial. We draw from the extensive literature on street gangs as well as from research on group formation and status-enhancing behavior to develop a theoretical model of gang formation.

Methods

Using game theory, we model the simultaneous decisions of individuals to commit status-enhancing acts of violence and to seek protection by joining a gang. We then conduct computer simulations to examine the resulting patterns of violence and gang composition.

Results

We demonstrate that as long as some social distance exists between racial groups in a community, gang violence will be intra-racial and gangs will be homogenous. We find that our results are robust to a number of simple variations of the model and allow us to generate several hypotheses about the nature of gang formation and patterns of violence.

Conclusions

When violence is motivated by socially constructed rewards, socially closer targets are likely to yield greater rewards. In such a system, individuals must reduce their likelihood of victimization by entering a social contract of non-violence (i.e. gang membership) with individuals who might view them as status-enhancing targets (i.e. socially close individuals). The result is that gangs are made up of socially close individuals interested in attacking other socially close individuals. Therefore, gangs tend to be racially homogenous and violence is overwhelmingly intra-racial.

     

Measuring and Modeling Repeat and Near-Repeat Burglary Effects

We develop a mathematical framework aimed at analyzing repeat and near-repeat effects in crime data. Parsing burglary data from Long Beach, CA according to different counting methods, we determine the probability distribution functions for the time interval τ between repeat offenses. We then compare these observed distributions to theoretically derived distributions in which the repeat effects are due solely to persistent risk heterogeneity. We find that risk heterogeneity alone cannot explain the observed distributions, while a form of event dependence (boosts) can. Using this information, we model repeat victimization as a series of random events, the likelihood of which changes each time an offense occurs. We are able to estimate typical time scales for repeat burglary events in Long Beach by fitting our data to this model. Computer simulations of this model using these observed parameters agree with the empirical data.

A New Twist on an Old Approach: A Random-Interaction Approach for Estimating Rates of Inter-Group Interaction

There are numerous instances in which researchers wish to measure the rate of intra- or inter-group interactions (whether positive or negative). When computing such measures as rates there is great uncertainty regarding the appropriate denominator: we analytically illustrate how the choice of the denominator when calculating such rates is not trivial and that some existing strategies create a built-in relationship between the computed rate and the group composition within the entity. Another strand of prior work only focused on the relative occurrence of intra- versus inter-group events, which does not account for the important theoretical possibility that both types of events might increase in certain social contexts. Our approach provides an advance over these earlier strategies as it allows one to take into account the relative frequency of interaction between members of different groups, but then translates this into per capita rates. We also provide an empirical example using data on inter- and intra-group robbery and aggravated assault events for block groups in a section of the city of Los Angeles to illustrate how our procedure works and to illustrate how other approaches can lead to dramatically different conclusions.     

Spatializing the Social Networks of Gangs to Explore Patterns of Violence

The majority of spatial studies of crime employ an inductive approach in both the modeling and interpretation of the mechanisms of influence thought to be responsible for the patterning of crime in space and time. In such studies, the spatial weights matrix is specified without regard to the theorized mechanisms of influence between the units of analysis. Recently, a more deductive approach has begun to gain traction in which the theory of influence is used to model influence in geographic space. Using data from Los Angeles, we model the spatial distribution of gang violence by considering both the relative location of the gangs in space while simultaneously capturing their position within an enmity network of gang rivalries. We find that the spatial distribution of gang violence is more strongly associated with the socio-spatial dimensions of gang rivalries than it is with adjacency-based measures of spatial autocorrelation.     

Explaining Crime Diversity with Google Street View

Journal of Quantitative Criminology - Crime diversity is a measure of the variety of criminal offenses in a local environment, similar to ecological diversity. While crime diversity distributions...     

Diffusion in Homicide: Exploring a General Method for Detecting Spatial Diffusion Processes

This article proposes a new method for examining dynamic changes in thespatial distribution of a phenomenon. Recently introduced exploratoryspatial data analysis (ESDA) techniques provide social scientists with anew set of tools for distinguishing between random and nonrandom spatialpatterns of events (Anselin, 1998). Existing ESDA measures, however, arestatic and do not permit comparisons of distributions of events in the samespace but across different time periods. One ESDA method—the Moranscatterplot—has special heuristic value because it visually displayslocal spatial relationships between each spatial unit and its neighbors. Weextend this static cross-sectional view of the spatial distribution ofevents to consider dynamic features of changes over time in spatialdependencies. The method distinguishes between contagious diffusion betweenadjoining units and hierarchical diffusion that spreads broadly throughcommonly shared influences. We apply the method to homicide data, lookingfor evidence of spatial diffusion of youth-gang homicides acrossneighborhoods in a city. Contagious diffusion between neighboring censustracts is evident only during the year of peak growth in total homicides,when high local rates of youth-gang homicides are followed by significantincreases in neighboring youth- nongang rates. This pattern is consistentwith a spread of homicides from gang youth to nongang youth. Otherwise, theincreases in both youth-gang and youth- nongang homicides generally occursimultaneously in nonneighboring tracts.