Effective Hot Spot Policing

Running head: EFFECTIVE HOT SPOT POLICING 1

Effective Hot Spot Policing

A Proposal

Nathanael Shermett

Arizona State University

EFFECTIVE HOT SPOT POLICING 2

Abstract

Though problem-oriented policing and hot spot policing are both effective, modern

policing strategies, some critics have argued that the risk of crime displacement can outweigh the

returns of hot spot policing, ultimately rendering it inefficacious. However, a growing body of

evidence suggests that crime displacement is not only uncommon, but significantly rarer than

diffusions of benefits. As diffusion is a desirable side effect of any policing strategy, it follows

that police officers should use the phenomenon to their advantage. Using the data and

methodologies of a number of hot spot policing studies—especially Koper’s (1995) research on

temporal diffusion—this paper proposes a number of simple steps a police department can take

to maximize their department’s effectiveness in high-crime areas.


Effective Hot Spot Policing

If a leading criminologist were to enter a stadium of ten thousand interested onlookers

and make the following statement: criminals often commit crimes because they believe that the

crime acts will benefit them in some way, it is unlikely anyone would be impressed. It is obvious,

after all, that most criminals commit their crimes because they have reasons to do so. Not good

reasons, perhaps, but reasons nonetheless. For example, a burglar might break into a house and

steal its owner’s jewelry because he wants money and does not believe he will be caught. If he

commits this crime, he expects to make a profit. Another example might be a father who is

abusive because he does not feel respected. If he forces his children to submit to him, then he

will feel respected—he loses nothing, and he gains respect. Morality aside, it could be said that

the decisions made by these two individuals are rational. This concept forms the basis of rational

choice theory (Scott, 2000, p. 126).

Today’s hot spot policing initiatives are grounded in rational choice theory. Though hot

spot policing has been at the center of a growing body of evidence-based research, some police

officers have expressed concern that hot spot policing is ineffective, and simply moves crime

from one area to another rather than actually reducing it (Telep, Mitchell, & Weisburd, 2014, p.

925). Evidence for this phenomenon, known as crime displacement, is mixed. Evidence for a

related phenomenon known as diffusion of benefits has also been contradictory, but new research

on this subject suggests that diffusion can have a very benign effect on properly implemented hot

spot policing strategies. This is especially true of temporal diffusion, in which a deterrent’s effect

on crime lasts longer than the period of time that the deterrent is actually present.


Focusing primarily on street crime, this paper will analyze the theory and reality of crime

displacement, as well as diffusions of benefits. It will also provide a glimpse into how these

phenomena functionally relate to hot spot policing, especially in light of recent studies conducted

in Maryland and California. This paper will conclude with a proposal for how police departments

can use this new research to implement effective hot spot policing tactics into their current

strategies.

Theoretical Basis For This Study

Rational choice theory posits that crime, at its most basic level, is the result of logical

decisions by the offender in which the perceived benefits of committing a crime are significantly

outweighed by the perceived drawbacks. In other words, a criminal’s decision to commit a crime

is a logical one. In John Scott’s Understanding Contemporary Society (2000), rational choice

theory is described plainly: “what distinguishes rational choice theory from [...] other forms of

theory is that it denies the existence of any kind of action other than the purely rational and

calculative” (p. 126). While it is often politically incorrect to claim crime is a logical option for

certain people in certain situations, beauty can be found in the theory’s simplicity and wide

applicability. Some have even argued that it applies in situations where an offender is motivated

pathologically or impulsively as well (e.g. Cornish, 2014, p. 2).

Rational choice theory is one of the most powerful and widely-supported theories in

criminology (Ostrom, 1998, p. 2). For every strong theory or explanation of crime that grounds

itself in rational choice theory, credibility is lent to it. There are certainly many, with strain

theory and routine activities being two of the most widely recognized, the latter of which will be


discussed shortly. Furthermore, empirically, there is no question that rational choice theory is a

highly powerful predictor of behavior and crime (Ostrom, 1998, p. 2). Of course, rational choice

theory is not without its problems. Due to its wide applicability, its ability to explain certain

correlates of crime is limited. For example, schizophrenia has been found to have a high

correlation with arrest rates for violence (Brennan, Mednick, & Hodgins, 2000). While rational

choice theory has been applied to situations in which an offender is motivated pathologically or

impulsively, this application does not provide practical insight into how those individuals

compare to other individuals, nor does it provide inside into what makes them different. For

example, consider a violent schizophrenic. From a purist’s rational choice perspective, all that

could be known about him is that if he finds more reason to commit a crime than reason not to,

he will. While this would likely be a true statement, its explanatory power leaves much to be

desired, as it says nothing about that individual’s propensity for crime relative to other

individuals’, schizophrenic or otherwise. This is true for any far-reaching theory in criminology.

The broader a given explanation of crime is, the greater the need for smaller, more specific

explanations to fill its holes. Another example would be in regards to crime’s tendency to occur

more frequently in low-income areas. Though rational choice theory might correctly argue that

the individuals who live in a low-income area have more to gain, and less to lose, by committing

a crime, it does not explain why. Instead, this trend in crime would be better explained by social

disorganization theory or strain theory, which look at crime in terms of the subculture and

socioeconomic class with which a criminal identifies (see Park, 1915; Agnew, 1992). Though

these theories cannot explain all types of crime, they provide valuable insight into the types of


crime that they can explain—much more so than rational choice theory can by itself. The

specifics of these particular theories, however, are beyond the scope of this paper.

In 1979, in order to narrow down the scope of rational choice theory, routine activities

theory was formally proposed (Felson & Cohen, 1979). An offshoot of the less-popular crime

opportunity theory, routine activities theory posits that criminals tend to commit crime if

opportunities present themselves during the course of the prospective criminal’s daily routine,

hence the name. For example, a violent alcoholic is more likely to rob a liquor store he

encounters on his daily walk home from work than a liquor store several blocks away he rarely

sees. Likewise, theoretically, a violent rapist is more likely to rape someone he encounters during

the course of his daily routine than someone he must go out of his way to hunt down.

Felson and Cohen (1979) suggest that, in order for crime to occur during a potential

criminal’s routine activities, three important criteria must be met (p. 588; Mustaine & Tewksbury,

1999, p. 47). The first, and perhaps most obvious, is that the offender must be motivated to

commit a crime. Most people do not commit criminal acts (besides perhaps speeding on their

way to work) during the course of their daily routine, even if an opportunity to do so presents

itself. According to routine activities theory, this motivation distinguishes most people from

potential offenders, and is a prerequisite for the theory.

Criminal motivation logically lends itself to routine activity theory’s second criterion: the

presence of a suitable target. For example, an alcoholic is more likely to rob a closed

convenience store that does not have barred windows than one that does—that is simply logical.


Furthermore, for a target to be suitable, it should somehow be valuable to the potential offender.

Felson and Cohen explain suitable targets as follows:

Target suitability is likely to reflect such things as value (i.e., the material or

symbolic desirability of a personal or property target for offenders), physical visibility,

access, and the inertia of a target against illegal treatment by offenders (including

the weight, size, and attached or locked features of property inhibiting its illegal

removal and the physical capacity of personal victims to resist attackers with or

without weapons). (p. 591)

Therefore, in addition to being motivated to commit a crime, a potential offender must also

encounter a suitable target, likely over the course of the potential offender’s routine activities—

otherwise, a crime is less likely to occur.

The third and final criterion presented by routine activities theory is related to the second,

but is much more relevant to our discussion of crime control and policing. In order for a crime to

occur, a “capable guardian”—someone or something with the ability to stop the crime or punish

the individual—must be absent (p. 604). This capable guardian might be a police officer, a

security guard, or even an ordinary civilian. A guardian can also be inanimate, such as a security

camera. With this third criterion, routine activities theory can be summed up as follows: if a

potential offender is (1) motivated to commit a crime, and if the potential offender happens to (2)

find a suitable target in the (3) absence of a capable guardian, then a crime is much more likely

to occur than if one or more of the three conditions is not met.


Routine activities theory has been validated empirically by a large number of studies. In

the words of researchers Mustaine and Tewksbury (1999), since its “large-scale emergence” in

the 1980s, routine activities theory “has provided both a host of initial explanations for what

might otherwise appear as disconnected and contradictory patterns of criminal victimization and

an easily comprehensible, apparently logical, explanation for many criminal events” (p. 47). In

their research, they compared female stalking victims from nine post-secondary educational

institutions, and ultimately concluded that “routine activities theory has a significant amount of

explanatory potential when it comes to influences over women’s stalking victimization”, noting

that “variation in the incidence of stalking [...] appears to be the result of a variety of lifestyle

behaviors [ultimately providing] support for routine activity explanations (p. 57). In an unrelated

“spatio-temporal” analysis of the interaction between offenders, victims, and potential guardians,

it was found that the basic premise of routine activities theory—that crime will decrease as

individuals spend more time away from home—was “strongly supported” (Groff, 2007, p. 98). A

2010 study by Pratt, Holtfreter, and Reisig of Arizona State University found that routine

activities can be generalized to internet behaviors as well (pp. 267-296).

Despite the fact that empirical tests are generally supportive (Groff, 2007, p. 98), routine

activities theory has been met with some criticism. Like with rational choice theory, however,

this criticism is not due to any inherent inaccuracy of the model. Instead, it is due to the fact that

routine activities theory is so widely applicable. For example, at least one researcher has called

routine activities theory a “description” of crime, ”not an explanation” (Jeffery, 1993, p. 492).

Furthermore, due to the fact that routine activities theory only presents three factors of crime


activity—motivated offenders, suitable targets, capable guardians—its specificity is inherently

limited. However, for the purposes of this paper’s research and proposal, this particular

limitation is not a major concern.

Problem-Oriented Policing

According to Spelman and Eck (1987), problem-oriented policing is a tactical approach

to crime prevention that allows “police officers, detectives, and their supervisors [...] to identify,

analyze, and respond, on a routine basis, to the underlying circumstances that create the incidents

that prompt citizens to call the police” (p. 2). In other words, problem-oriented policing

addresses the underlying causes of crime—not the crimes themselves—with the hope of

preventing much criminal activity from ever occurring in the first place.

The relationship between routine activities theory and problem-oriented policing is often

modeled as a “problem analysis triangle” or “crime triangle” (Clark & Eck, 2005):


In this model, the inner triangle represents both the motivated offender and the suitable target.

The motivated offender is the “offender”, and the suitable target is both the “place” and

“target/victim”, with the former representing the location of the target. For some types of crime,

such as vandalism, the “place” and “target” can be the same. However, in the case of

interpersonal crime, auto theft, and some other types of crime, the target is not a place, but rather

a person or object whose location is constantly changing. Therefore, the “place” and

“target/victim” are two separate variables, and represent two different sides of the crime triangle.

The outer triangle represents routine activities theory’s capable guardian, as well as the

individuals who are capable of controlling their corresponding variable. Each side’s

corresponding variable is provided by the inner triangle. Therefore:

A handler is an individual who is capable of controlling an offender. This may be a

friend, family member, spouse, mentor, et cetera.

A manager is an individual who is responsible for controlling behavior at a given

location. This may a homeowner, a house sitter, a property manager, a teacher at a

school, et cetera.

A guardian is the person who protects the target or victim. This may be the victim

themselves, a police officer, a security guard, a watchdog, et cetera.

A problem-oriented approach to policing would consider these three relationships in determining

how to best address a recurring problem. However, only one side of the triangle needs to be

disrupted in order to prevent a given crime. For example, if a school is constantly vandalized,

then a police department might work to either change the nature of the place itself, or the


oversight of its teachers and property manager. If an offender constantly recidivates, then a

police officer might try to teach the offender’s family and mentors how to positively influence

the individual to not commit more crimes in the future. If women are often attacked in a certain

high-crime area, a police department might hold a self-defense workshop nearby and provide

free pepper spray to the participants. In these examples, the police first identify a problem,

consider its place in the crime triangle, and then work to change the outer triangle in order to

prevent it from reoccurring.

Hot Spot Policing

According to Braga, clusters of high-crime areas (i.e. hot spots) “generate half of all

criminal events [in a city landscape]” (Braga, 2005, p. 317). Therefore, it follows that if police

resources were more heavily focused on these high-crime problem areas, more crime will be

deterred than if police resources were instead focused on areas with lower crime rates. This is

known as hot spot policing, and a growing body of studies has demonstrated that it can be a very

effective means of deterring criminal activity (e.g. Braga, 2005; Koper, 1995; Braga,

Papachristos, & Hureau, 2012; Telep, Mitchell, & Weisburd, 2014). During a systematic review

conducted by Braga, it was found that of five experiments evaluating the efficacy of hot spot

policing strategies, four revealed statistically significant benefits to hot spot policing strategies

compared to control strategies (Braga, 2005, p. 336). The author suggested that the insignificant

data in the fifth study can probably be attributed to methodological problems (p. 336).

One of the earliest, most famous hot spot policing experiments was conducted by

Sherman and Weisburd (1995). It demonstrated empirically that hot spot policing can have a


statistically significant impact on crime (Sherman and Weisburd, 1995). Over the course of one

year, the researchers randomly increased the dosage of police patrol at 55 of 110 hot spots in

Minneapolis, ultimately recording 7,542 hours of systematic observations (p. 635). Though their

data showed wide seasonal fluctuations, they ultimately concluded that substantial increases in

police patrol presence can result in “modest,” statistically significant reductions in crime (p. 625).

Another early study conducted that same year found even more promising results, but was

conducted a bit differently. Researchers Weisburd and Green identified 56 drug hot spots in

Jersey City and then had police officers engage local business owners and citizens in drug

control efforts at these locations (Weisburd & Green, 1995). The police also initiated drug

crackdowns and a maintenance effort with the department’s local patrol division (p. 711).

Following the seven-month intervention, the researchers found “consistent and strong effects” on

disorder-related emergency calls for service (p. 731). Evidently, hot spot policing can be a very

effective policing strategy.

Displacement Effects and Diffusion of Benefits

Though the scientific literature on hot spot policing is overwhelmingly positive, some

police officers have expressed concerns regarding its effectiveness (Telep, Mitchell, & Weisburd,

2014, p. 925). While it is logical to assume that a capable guardian’s presence can deter a

potential offender from committing a crime, it will not necessarily take away the offender’s

original motivation for doing so. Therefore, if an offender is motivated enough to commit a

crime, he or she can simply choose to commit the crime somewhere else instead, away from the

capable guardian’s influence. For a highly motivated offender, this would be a rational decision.


This phenomenon is known as crime displacement, and defines a shift of crime, be that

shift a change in a crime’s location, a change in the time the crime was committed, or a number

of other changes. At the time of this writing, six types of crime displacement have been formally

identified: temporal, in which criminals commit the same crime at a different time; tactical,

where criminals “adopt a different modus operandi”; target, where criminals select a different

target for crime, such as types of housing; crime-type, where criminals commit a different type of

crime; spatial, where criminals commit crime in a different location, (as was the case in the

vandalism example); and perpetrator, in which apprehended criminals are simply replaced with

new ones (Bowers & Johnson, 2003, p. 276). For the purposes of this paper, spatial and temporal

displacement will be most frequently discussed, as they tend to be the most heavily studied types

of displacement in criminology.

Surprisingly, though crime displacement seems to be a reasonable expectation following

the introduction of a capable guardian, it does not always occur. Instead, crime has been

demonstrated to occasionally decrease in both the area in which a capable guardian is introduced

as well the surrounding areas, even if they remain untouched by the new guardian. This

phenomenon is known as diffusion of benefits, and defines the “diffusion” of a capable

guardian’s perceived presence into an area larger than itself (Clarke & Weisburd, 1994, pp. 168-

169). Diffusion of benefits, like crime displacement, can also manifest spatially and temporally.

Returning to the previously used park vandalism example, if a capable guardian is introduced to

a park and a spatial diffusion of benefits occurs, then vandalism will not only decrease in that


park, but also the surrounding areas. This phenomenon has also been dubbed the “halo effect”

and “bonus effect” (Guerette & Bowers, 2009, p. 1334).

Though displacement and diffusion of benefits are treated as separate phenomena—as

they are, and as they are referred to in this paper—it may be helpful to view their relationship as

lying on a linear spectrum. Clarke and Weisburd (1994) describe diffusion of benefits as being a

reverse, “benign” displacement in which the “burden of victimization [is spread out] more

equitably across a community”, or with less serious crimes (p. 167). Guerette and Bowers (2009)

build on this idea and explain that there is generally a positive relationship between the size of

the intervention effect and the resulting displacement or diffusion of benefits (p. 1334). Diffusion

of benefits, then, only occurs after an unknown intervention-to-displacement ratio is surpassed,

with smaller interventions being more highly correlated with crime displacement instead of

diffusions of benefits. However, it must be reiterated that though viewing these phenomena on a

linear spectrum may be useful theoretically, they are nonetheless distinct phenomena.

Several studies have attempted to measure both displacement and diffusion. However,

doing so can be complicated, and methodological problems have traditionally been overlooked

(Weisburd et al., 2006, p. 551). As a result, the frequency of the occurrence of crime

displacement is often overstated (p. 553). Some more recent studies, however, have been more

rigorously designed, and are casting doubt on the notion that crime displacement is common. For

example, in a 2006 study on prostitution and drug crimes, over 6,000 social observations were

conducted in target and catchment areas (see Weisburd et al., 2006). The study was further

supplemented with both interviews and ethnographic field observations. Contrary to long-


standing beliefs regarding the nature of crime displacement, the authors found that police

interventions at crime hot spots were significantly more likely to result in diffusion of benefits

than spatial displacement (p. 576). According to the authors, their study is possibly the first

direct empirical study of displacement (p. 551). A more recent 2014 study drew similar

conclusions, but also considered temporal displacement and crime-type displacement (Rosenfeld,

Deckard, & Blackburn, 2014). In this study, thirty-two crime hot spots in St. Louis were assigned

displacement catchment areas (p. 435). They were also randomly allocated to two treatment

conditions and a control condition. Both treatment conditions increased directed patrol, whereas,

to quote the authors, “the experimental protocol limited other enforcement activity in one of the

treatment conditions and increased it in the other” (p. 428). The experiment was a success and

the intervention “substantially reduced” non-domestic firearm assaults in the study’s treatment

areas. However, despite the intervention, the authors concluded that they could find “no

evidence” of spatial, temporal, or crime-type displacement (p. 445). However, there was also no

evidence of diffusion of benefits (p. 445).

In addition to traditional studies, a number of meta-analyses have been conducted on

crime displacement, and most agree that displacement is less common than diffusion. A 1994

meta-analysis found that of 55 studies reviewed, 60% showed evidence of crime displacement,

while only 11% showed evidence of diffusion of benefits. Of the 7 studies specifically measuring

temporal displacement, however, it was observed in 100% of cases, while of the 34 studies

measuring spatial displacement, displacement was only found in 53% of cases (Hesseling, 1994,

pp. 218-219). Though this meta-analysis shows remarkably little evidence of diffusion overall, it


is important to consider than it was conducted more than twenty years ago. A more recent study

done in 2011 found that in a collection of 44 studies, only 39% showed evidence of spatial

displacement. No other types of displacement were measured (Bowers et al., 2011, p. 358). Of

the studies measuring diffusion of benefits, it was found in 43% of studies, and not found in 5%

of studies. The remaining 52% of studies did not measure diffusion. Furthermore, another meta-

analysis conducted in 2012 found that of 17 studies measuring spatial displacement after police

interventions, only 18% found possible displacement effects, whereas 47% found possible

diffusion effects (Braga, Papachristos, & Hureau, 2012, p. 22).

Displacement and Diffusion in Hot Spot Research

Considering these data show that diffusion of benefits is likely a real phenomenon, it

follows that—assuming diffusion is not random—the occurrence of diffusion of benefits can be

modeled and predicted experimentally. A 1995 study conducted at the University of Maryland

tested this notion with temporal diffusion of benefits, and found that it is indeed predictable

(Koper, 1995). Using observational data from the Minneapolis Preventive Patrol Experiment—a

one-year study that examined the effects of police presence at 100 crime hot spots—Koper found

that the length of time a capable guardian was present at a hot spot correlates directly with the

residual deterrent effect after the guardian leaves. For periods of time greater than approximately

10 minutes, the residual deterrent effect was found to be significantly greater than what would be

generated by a guardian simply driving through a hot spot. This effect was found to peak at

approximately 14-15 minutes, after which returns began to diminish. This correlation is known

as the Koper Curve. To quote the author, “the findings suggest that longer [police] presences, at


least up to a point, increase uncertainty and raise perceptions of risk at hot spots. This outcome

lengthens survival times, probably through a combination of driving away some troublesome

persons and making others more cautious for some time afterward” (Koper, 1995, p. 668). These

findings suggest significant temporal diffusions of benefits in which the benefits of a capable

guardian’s presence extends beyond the length of time he or she is actually on-site. The author

also notes that an implicit finding of the results is that this type of preventative patrol may also

decrease noncriminal disorderly behaviors, hinting at the possibility of diffusion extending

across different types of crime as well. Unfortunately, due to limitations of the Minneapolis

Preventative Patrol Experiment, spatial diffusion could not be measured.

A study conducted by the Sacramento Police Department recently attempted to

experimentally test Koper’s conclusions. This was done in order to determine the efficacy of the

Koper Curve as a framework for more efficient patrols (Telep, Mitchell, & Weisburd, 2014). In

the study, Sacramento police officers were assigned 1-6 random crime hot spots each day, and

were instructed to visit these hot spots in a predetermined order that was also randomized.

Though the study did not completely control for the behavior and activity of the individual police

officers upon arriving at the hot spot, they were instructed to spend 12-16 minutes at each one,

and to also try to visit each hot spot at least once every two hours. They were also encouraged to

initiate contact with the community during these stops. In order to increase internal validity, 21

control hot spots received ordinary attention. The authors of this study concluded that there was

an overall significant decrease in both calls to service and index crimes after the tactic was

implemented. Though the authors admitted to having some trouble measuring spatial


displacement due to the proximity of many crime hot spots, they nonetheless found displacement

to be insignificant at the hot spots where it could be measured. No spatial diffusion was

identified either, but considering the decrease in service calls and index crime is attributable to

the experiment, the same temporal diffusion that Koper identified may have been at play.

Conclusion

Though the possibility of crime displacement remains a concern for some police officers,

the results of the studies at the University of Maryland and in Sacramento suggest that diffusion

of benefits significantly outweighs any malignant crime displacement (Koper, 1995; Telep,

Mitchell, & Weisburd, 2014, p. 925). These two studies constitute strong evidence that temporal

diffusion, when manipulated correctly, can significantly increase the effectiveness of hot spot

policing tactics. Some things are still not understood about the relationship between crime

displacement and diffusion, but this preliminary research suggests that police departments can

nonetheless begin to implement effective tactics around what is known. Koper’s data seem to be

particularly relevant, and the Koper Curve provides a simple, yet powerful, framework by which

these strategies can be integrated into a police department’s current strategy.

Application and Proposal

While more empirical research needs to be done to determine the functional reality of the

Koper Curve, as well as the degree to which temporal diffusion can be exploited by police

departments, the statistical strength of Koper’s study—along with its empirical qualification by

the Sacramento Police Department—provides a strong rationale for the implementation

elsewhere of strategies similar to those in Sacramento. Therefore, at least until new research


recommends otherwise, I propose that all police forces follow a similar strategy in their high-

crime jurisdictions, under the following prerequisites and suggestions:

Any implementation of these strategies should be done in cooperation with one or

more criminologists so as to create an effective experimental design and more usable

data for future adaptation.

Police departments interested in implementing these strategies must first have adequate

data on crime hot spots. Though there is little reason to suspect Koper’s data would not

be relevant at non-hot spot locations, there is likewise little reason to suspect temporal

diffusion at low-crime areas would have a significant impact on city or jurisdiction’s

crime rates. Furthermore, if a police officer were to spend several minutes at a low-

crime area instead of a high-crime hot spot, they would inevitably be making

themselves less available at areas where they are more needed, potentially increasing

crime rates rather than decreasing them.

Hot spots should be defined using the same parameters set by both the Minneapolis

Hot Spots Experiment and the Sacramento experiment (see Telep et al., 2014, p. 913):

1. No hot spot is to be larger than one standard linear street block.

2. No hot spot is to extend for more than one half block from either side of an

intersection.

3. No hot spot is to be within one standard linear block of another hot spot.

Control hot spots should be utilized. They should be randomized to increase validity,

and they should not see a change in police activity after the implementation of these


strategies. Though Sacramento did see a significant decrease in crime by modeling

their patrols after the Koper Curve, not all police departments will necessarily see

improvements. All police jurisdictions are different, and as a result certain tactics may

be more or less effective in certain situations. While it is reasonable to assume that

that strategies utilized in Sacramento would be effective in many other police

jurisdictions, the use of control hot spots will ensure that a police department can

actually determine whether or not the strategies are effective or ineffective in their

department, and act accordingly.

The strategy should be implemented for a minimum of 90 days. This number is the

same used in the Sacramento Police Department’s experiment, after which they were

able to find significant data. If a shorter treatment time is used, it is more likely that the

resultant data will be skewed and misrepresent the treatment effect. However, if it is

possible to maintain the new strategy longer than 90 days, this would be even more

desirable. Telep et al. note that “[in Sacramento] a lengthier intervention period may

have been associated with greater crime declines” (2014, p. 929).

Hot spot data, both before and after the treatment is implemented, should be made

publicly available to other researchers, as well as any observed displacement or

diffusion effects. Koper’s hot spot policing recommendations have not been utilized in

a large number of experiments, and as a result, research on the Koper Curve is still

limited. If more data becomes publicly available, then the effectiveness of Koper’s


recommendations can be empirically studied more easily, accelerating research in this

area.

Every day, police officers should be assigned 1-6 random non-control hot spots, as was

done in the Sacramento experiment (Telep et al., 2014, p. 915). If possible, police

officers should stop at their assigned hot spot areas for approximately 12-18 minutes,

during which time they should attempt to interact with individuals in the area, focusing

on problem-oriented policing when possible. While the Sacramento implementation of

the Koper Curve urged officers to stop for 12-16 minutes at each hot spot, this range is

skewed slightly to the left of the Koper Curve’s peak effectiveness (see Koper, 1995,

pp. 664-667; Telep et al., 2014, p. 915). By imploring officers to stay at their hot spot

for 12-18 minutes, they may be less tempted to leave early and miss the 15 minute

mark’s peak benefit.

Police officers should revisit their assigned hot spots at least once every 2 hours.

Though this number is arbitrary, it is the recommendation utilized in the Sacramento

experiment, and that experiment saw a significant decrease in crime. Unfortunately,

Koper’s data do not provide strong insight into more ideal revisitation times (see

Koper, 1995, p. 666).

If these prerequisites and suggestions are considered, I hypothesize that most high-crime police

jurisdictions will see statistically significant decreases in crime. Koper’s data, coupled with the

Sacramento Police Department’s empirical qualification, make a strong case for the Koper

Curve’s empirical reliability. Small decreases in crime can go a long way, and considering the


significant impact of the Sacramento study occurred after only 90 days, it is exciting to consider

what effect other police departments will see, especially over longer treatment times. I implore

any police department reading this proposal to test it in their own jurisdictions and to share their

results. Evidence-based hot spots policing strategies are growing at an alarming rate, and as more

studies are published, police departments at the forefront of this research will likely see even

greater reductions in crime and deviancy than they already have.


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Effective Hot Spot Policing

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