On the invitation of the Philadelphia Police Department, police and academic researchers worked together to plan the Philadelphia Foot Patrol Experiment as a randomized control trial. 60 violent crime hot spots were targeted during the summer of 2009, and after three months violence had reduced by 23 percent compared to comparison areas. Analysis of the results found little displacement, but did find at threshold level for effectiveness. Recent follow-up work has further illuminated the long-term effects of the study. Faculty: Jerry Ratcliffe, Eilzabeth Groff, Jennifer Wood
The Philadelphia Foot Patrol Experiment was a major research collaboration between the Philadelphia Police Department and researchers in the Department of Criminal Justice involving over 200 police officers on foot beats around some of the city’s most violent corners.
Since the 1980s, it had long been the opinion of many police and criminology researchers that police foot patrols improve community perception of the police and reduce fear of crime, but they don’t prevent actual crime. Results from the Philadelphia Foot Patrol Experiment suggested a more positive view of intelligence-led targeting of foot patrol officers to violent crime hot spots.
On the invitation of the Philadelphia Police Department, police and academic researchers worked together to plan the Philadelphia Foot Patrol Experiment as a randomized and controlled field experiment. With the resources to patrol 60 locations, researchers identified the highest violent crime corners in the city, using data from 2006 to 2008. Police commanders then designed 120 foot patrol areas around these corners, and stratified randomization was used to assign pairs of foot patrols with similar crime rates as either a control or a target area.
Officers patrolled in pairs with two pairs assigned to each foot patrol. They worked from Tuesday to Saturday in two shifts (10am to 6pm, 6pm to 2am) during the summer of 2009. After three months, relative to the comparison areas, violent crime decreased 23%. Official records of police activities during the intervention period reveal the following in the target areas: Drug‐related detections increased 15%, pedestrian stops increased 64%, vehicle stops increased 7%, and arrests increased 13%. Even with some crime displacement to nearby locations, analysis indicated that the foot patrols prevented 53 violent crimes during the summer. This project won the 2010 Excellence in Law Enforcement Research Award from the International Association of Chiefs of Police and the Outstanding Experimental Field Trial Award from the American Society of Criminology’s Division of Experimental Criminology.
The experiment results were reported in the journal Criminology. The full citation is: Ratcliffe, J. H., Taniguchi, T., Groff, E.R., & Wood, J. (2011). The Philadelphia Foot Patrol Experiment: A randomized controlled trial of police patrol effectiveness in violent crime hotspots. Criminology, 49(3), 795-831.
A three-page research summary is also available.
Follow-Up Research And Further Findings From The Experiment
Was there a long-term impact of foot patrol? Subsequent research by the team examined the long-term impacts of the Philadelphia Foot Patrol Experiment to determine what happened after the experiment was over. Results showed that beats that were in place beyond three months had diminishing effects during the experiment, an effect not seen with the shorter term beats. Foot patrol beats returned to their pre-experiment crime levels once the foot patrol experiment was concluded and the foot patrols were largely withdrawn. There was no evidence that the benefits from the Philadelphia Foot Patrol Experiment lasted beyond the time when the officers were assigned to the beats. These findings were published in an article in Criminology.
Did the presence of foot patrol change the way car patrols were used? The question of how foot patrol affected the car patrol officers in which the foot beats were embedded was also examined by the team. Official data describing the activities of foot and car patrol officers was analyzed. We found noticeable differences in the activities of the two types of patrol. Foot patrol was more likely to conduct pedestrian stops and deal with disorder and drug offenses while car patrol handled the vast majority of reported crime incidents and calls from the public. As a result, police managers and researchers should consider the impact of new strategies on the dominant patrol style. Co-production of community safety among officers assigned to different patrol styles is an under-researched area with potential for improving the success of crime reduction efforts through better internal coordination of police resources. These findings were published in an article in Policing: An International Journal of Police Strategies and Management.
What was the experience of foot patrol officers? During the experiment we conducted field observations alongside the foot patrol officers. The observations were designed to capture officers’ perceptions of and experiences with the foot patrol function. Officers developed extensive local knowledge of their beat areas, and were what we call ‘reflective agents’ with varying styles and approaches to their foot patrol role. They had to negotiate the tension between what they perceived to be ‘real police work’ (arresting offenders) and the ‘reassurance’ function of foot patrol. They exerted spatial control of their beats through a repertoire of techniques which depended in part on officer style. We also learned that in some ways, the experimental nature of the intervention clashed with the common sense judgment of officers, including the need to adapt policing practices to changing criminal behavior. This research reinforces the need to integrate line officer knowledge in the design of place-based interventions. These findings can be found in an article in Policing and Society.
Did the officers remain in their assigned beats? Not entirely. During focus groups conducted with foot patrol officers after the experiment, we gave officers maps of their beats and asked where they actually patrolled. In general, the areas they actually patrolled were about 0.13 square miles greater than the originally assigned patrol zones. Officers left their assignments for a number of reasons, including because they perceived that offenders had adapted to their patrol areas and moved to nearby locations, because they felt that areas just out side their beat should have been included in the area because specific locations caused community problems, and sometimes to add some variety when they became bored with patrolling the same area every day. More details of these findings can be found in our article in the Journal of Research in Crime and Delinquency.
What public health challenges did officers face on their beats? While the officers worked to establish rules and exercise some control over the areas they policed, they spent considerable time dealing with populations of people on the verges of society. On a daily basis, foot patrol officers assigned to small areas come face-to-face with not only traditional issues of crime, but also addition, mental illness, and homelessness. They struggled to see addicted drug users as vulnerable people at higher risks of morbidity and mortality; however, officers were more inclined to view people affected by mental illness as more vulnerable than threatening. They also had to deal with ‘microplaces of harm’ such as abandoned houses used for prostitution and drug use. In the end, officers, and foot patrol officers in particular, are ‘public health interventionists’. See our article in Police Practice and Research.
Newspaper accounts suggest that CCTV cameras are being implemented at a rate never seen before. Yet there has been a lack of high quality, independent evaluation studies, and only one significant study in the US, conducted over a decade ago. Drs Ratcliffe and Groff are currently working on an NIJ-funded study to evaluate the crime reduction impact of over 100 CCTV cameras in Philadelphia, PA, – an ongoing NIJ-funded large-scale, multi-method, quasi-experimental research study. Faculty: Jerry Ratcliffe, Elizabeth Groff
In a 2006 referendum, about 80% of Philadelphia voters indicated a desire to change the city charterand to allow for CCTV cameras to be deployed within the city .That year a pilot project involving 10 pan,tilt and zoom cameras, and 8 static cameras was implemented. Researchers from Temple University’sCenter for Security and Crime Science found that after building in controls for long-term trends andseasonality, the introduction of the cameras was associated with a 13% reduction in overall crime,though the violence rate near the cameras was too low to identify a reliable violence reduction. Theevaluation suggested that while there appeared to be a general benefit to the cameras, there were asmany sites that showed no benefit of camera presence as there were locations with a positive outcomeon crime*.
Since then over 200 public CCTV cameras have been erected across Philadelphia since late 2007.Therewas clearly a need for a larger study.On the invitation of the Philadelphia Police Department, and with grant support from the NationalInstitute of Justice, we report here the preliminary results of a statistical evaluation of the impact ofthose cameras on various crime types. We say preliminary because we are still in the process ofcompleting a range of other analyses, which when combined with the work reported here, will allow usto better determine the overall impact of the cameras. This further work will include propensitymatching for control sites and a test for displacement to non-camera sites.
At present we can report preliminary results of a time series analysis of the impact of the CCTV camera violence, disorder, narcotics incidents, vehicle crime and burglary. Preliminary results of crime impact of CCTV cameras (pdf) .
For more details contact- Dr Jerry Ratcliffe or Dr Elizabeth Groff.* Details of this pilot study can be found in Ratcliffe, JH, Taniguchi, T, and Taylor, RB (2009) The crimereduction effects of public CCTV cameras: A multi-method spatial approach, Justice Quarterly, 26(4):746-770.
This ongoing project will create a free software tool that will enable police departments to use their geocoded crime data in combination with freely-available census data to create micro-spatial estimates of future criminal activity at the local block level. Working with Azavea, an innovative Philadelphia-based GIS company, Drs Ratcliffe and Taylor are developing a methodology to combine long-term risk prediction from underlying socio-demographics with event-created near-repeat risk. Faculty: Jerry Ratcliffe, Ralph Taylor
The Philadelphia Predictive Policing Experiment was a collaboration between Temple University’s Center for Security and Crime Science (housed in the Department of Criminal Justice) and the Philadelphia Police Department. This National Institute of Justice funded research project has been the first place-based, randomized experiment to study the impact of different police strategies on violent and property crime in predicted criminal activity areas.
Predictive policing is an emerging tactic relying in part on software predicting the likely locations of criminal events. Predictive policing, while sometimes applied to offenders, is most frequently applied to high crime places. In this context, it involves ‘the use of historical data to create a spatiotemporal forecast of areas of criminality or crime hot spots that will be the basis for police resource allocation decisions with the expectation that having officers at the proposed place and time will deter or detect criminal activity’ [Ratcliffe, J. H. (2014). “What is the future… of predictive policing?” Translational Criminology, 2014 (Spring): 4-5 (definition on page 4)].
At present, the law enforcement field lacks robust evidence to suggest the appropriate policing tactic in predicted areas. That has been the subject of this timely study. The aim has been to answer the question of whether different varieties of theoretically informed, but also operationally realistic, police responses to crime predictions estimated by a predictive policing software program can reduce crime.
The research team from Temple University and the Research and Analysis section of the Philadelphia Police Department randomly assigned 20 Philadelphia Police Department (PPD) districts into one of four experimental conditions. Five districts acted as controls, with a business-as-usual patrol strategy. In five districts, officers were made aware of the predicted high crime activity area at roll call and asked to concentrate there when able (a simple awareness model). Five districts received the awareness model treatment as well as an additional patrol car solely dedicated to the predicted crime area. Finally, five districts received an intelligence-led, investigative response with an unmarked unit dedicated to the predicted area. A three-page pdf has a fuller description of the research methodology.
When examining both predicted high-crime grid cells and the grids cells immediately surrounding them, the marked car patrols resulted in a 31% reduction in property crime counts, or a 36% reduction in the number of cells experiencing at least one crime. This translates to a reduction in three crimes over three months for an average city district patrolling around three grids. There were also signs of a temporal diffusion of benefits to the eight hours following the property crime marked car patrols. While the percentages were substantial, the results were not statistically significant due to floor effects.
There were no crime reduction benefits associated with the violent phase of the experiment, nor were there any benefits with the property crime awareness or unmarked car interventions. In summary, it appears that marked police cars dedicated to predictive policing areas were effective at reducing property crime. Unmarked cars and efforts to combat violence were not shown to be effective in the Philadelphia Predictive Policing Experiment. A two-page pdf has a more detailed description of the experimental results.
The predictive policing software employed was the HunchLab program designed by Azavea. HunchLab is a web-based predictive policing system that accesses real-time Philadelphia Police data to produce crime forecasts for the city. It incorporates statistical modeling that considers seasonality, risk terrain modeling, near repeats, and collective efficacy. Azavea adapted the software at the request of the Philadelphia Police Department and researchers from Temple University to generate three predicted 500 feet square grids per district per shift. They also included a slight randomization component to reduce the possibility that the same grid cells were predicted every day. It is important to note therefore that the experiment artificially reduced the efficiency of the software, because it forced the software to choose grids in low crime districts, and limited the number of grids it could assign in high crime districts.
The software was able to predict twice as much crime as we would expect if crime were spread uniformly across the districts, even when artificially constrained by our experiment to be less effective than designed. A two-page pdf has more details of the software efficacy.
This project has developed technology that will depict and predict current and future crime potential. In doing so, it operationalizes two grounded theoretical approaches to understanding localized spatial crime patterns. This combination of a long-term crime potential map surface with a short-term crime spike surface creates the opportunity for law enforcement and other criminal justice agencies to apply a theoretical understanding to the business of crime prediction. The resulting map of predicted crime will enable police departments to take a proactive approach to crime prevention, disruption and reduction, and will provide a foundation for predictive policing and crime prevention.
The project team of researchers from Temple University’s Center for Security and Crime Science (housed in the Department of Criminal Justice) and technical experts from Azavea (a Philadelphia-based company that specializes in the creation of geographic web and mobile software, as well as geospatial analysis services to enhance decision-making) has created a custom software tool. This program will enable police departments and other agencies across the country to use their geocoded crime data in combination with freely-available census data and create micro-spatial estimates of future criminal activity at the local level.
As part of this ongoing project, one piece of research has been published already. We asked the question: Do fundamental demographic correlates of crime, proven important in community criminology, link to next year’s crime levels, even after controlling for this year’s crime levels? If they do, it would imply that shifting ecologies of crime apparent after a year are driven in part by dynamics emerging from structural differentials.
For Philadelphia (PA) census block groups, 2005 to 2009 data from the American Community Survey and 2009 crime counts were used to predict spatially smoothed 2010 crime counts in three different models: crime only, demographics only, and crime plus demographics. Models were tested for major personal (murder, rape-aggravated assault, and robbery) and property (burglary and motor vehicle theft) crimes.
We found that for all crime types investigated except rape and homicide, crime plus demographics resulted in the best combination of prediction/simplicity based on the Bayesian Information Criterion. Socioeconomic status (SES) and racial composition linked as expected theoretically to crime changes.
We concluded that intercommunity structural differences in power relationships, as reflected in SES and racial composition, link to later crime shifts at the same time that ongoing crime continuities link current and future crime levels. The main practical implication is that crime analysts tasked with long-term, one-year-look-ahead forecasting may benefit by considering demographic structure as well as current crime.
This research has been published here as: Taylor, R. B., Ratcliffe, J.H. and Perenzin, A. (2015) Can we predict long-term community crime problems? The estimation of ecological continuity to model risk heterogeneity. Journal of Research in Crime and Delinquency 52(5): 635-657.
This National Institute of Justice funded research project is ongoing, however the software is now available as of October 2016. Please visit the following website (you will leave the Temple University site) to access the software downloader, manual, and quick start guide.
A significant body of evidence exists that police are most effective at reducing crime when deployed to small, high crime areas known as hot spots. In the summer of 2010, the Philadelphia Police and researchers from Temple University’s Center for Security and Crime Science (housed in the Department of Criminal Justice), with support from the Bureau of Justice Assistance, set out to better understand the impact of different policing tactics deployed in hot spots. Three different tactics were tested problem oriented policing, offender focus policing and foot patrol.
The first step in the experiment was to identify the highest crime areas in Philadelphia using spatial analysis. We gave the Philadelphia Police Department (PPD) a map showing those hot spots and asked for their input in two important. One was in defining hot spot boundaries that were operationally sound and the other was in identifying which type of tactic they thought best suited the problems at that hot spot. For example, if there were a few people that were causing the problem then it made sense to apply offender-focused policing. If the problem was street robbery, then a problem-oriented policing approach to address the why that place was so amenable to street robbery would be appropriate. Regional Operations Commanders worked with District Captains to identify 27 areas suitable for foot patrol, 27 suitable for problem-solving, and 27 where police would focus enforcement on violent repeat offenders. The PPD returned a new map with 81 hot spots defined and the most appropriate tactic for each hot spot listed. We applied a random selection process so that 20 areas of each type were selected for additional police activity, and seven of each area type would receive the normal police response.
District officers in collaboration with members of the community and the support of personnel from police headquarters from the PPD2020 team conducted the problem-oriented policing tactic. Local initiatives to address the causes of violence varied across districts as problems were unique to each area.
Criminal intelligence officers and district personnel identified repeat violent offenders and they informed command staff at the district level. The role of focusing enforcement activities on the identified individuals generally fell to officers assigned to a unit out of the normal shift pattern in each district.
District Captains assigned foot patrol officers to each site and decided both the shift times and the operational tactics applied. Foot patrol officers usually (though not in one case) worked in pairs and were volunteers. The general pattern was two officers, for 8 hours a day, five days a week.
We employed repeated measures multilevel modeling using contrast coding to analyze the results because these types of models describe changes in an outcome measured at multiple time points for a given unit of analysis – ideal for this type of complex problem. We also controlled for trends over time and temperature (as violence is known to increase as it gets warmer).
We found that offender focus areas were successful in reducing all violent crimes by 42% compared to the equivalent control areas. These violent incidents included homicide, robbery, and assaults – both aggravated and misdemeanor. The offender focus sites were even more effective on violent felonies, reducing them by 50% compared to the equivalent control areas. Beyond the crime reduction, additional potential benefits of a targeted enforcement strategy are that it is less intrusive for law-abiding citizens because it avoids the wholesale increases in pedestrian and traffic stops that are so damaging to police community relations and that produce large numbers of arrests and flood the criminal justice system. Depending on implantation, the tactic may also increase the perception of the police as more procedurally just and improve community satisfaction with the police.
The foot patrol areas were not successful in reducing violence during the experimental period, nor were the problem-solving areas.
In sum, by focusing police efforts on the problem people associated with the problem places, police can achieve significant crime reductions while potentially avoiding negative community perceptions of their actions. However, we need additional research that more precisely measures what police officers do while in hot spots if we are to develop greater insight into why some crime reduction tactics are more successful than other ones.
More details are available in a research brief here for practitioners.
The full study is published here as: Groff, E. R., Ratcliffe, J. H., Haberman, C. P., Sorg, E. T., Joyce, N. M., & Taylor, R. B. (2015). Does What Police Do At Hot Spots Matter? The Philadelphia Policing Tactics Experiment. Criminology, 53(1), 23-53.
Although it is not their primary mission, law enforcement officers serve as mental health interventionists. In this role, they intervene with vulnerable people in spaces of the city that may be considered “hotspots of vulnerability.” This ongoing project is devoted to strengthening theoretical and practical linkages between law enforcement and public health. Central to this agenda are insights from the literatures on environmental criminology and problem-oriented policing which can help provide for a twin emphasis on "case management" and "place management" in efforts to enhance public health and safety. Visit Jennifer Wood's faculty page for information about a research monograph, policy brief and recent scholarly article.
Near Repeat Calculator
- The near repeat calculator software is currently unavailable.
Additional Research Projects and Resources
- Links in Space and Time between Firearm Arrests and Shootings
- Related Publications
- The Impact of Philadelphia’s Public CCTV Cameras: PRELIMINARY FINDINGS FROM A TIME SERIES ANALYSIS