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Summary: This is a place-based intervention that uses closed-circuit television and signage at high-crime addresses to deter or reduce crime and improve public safety. The program is rated Ineffective for reducing reported disorder and violent crime. (Review the full program description).
| Title | Rating | Details | Outcome Category | Study(ies) |
|---|---|---|---|---|
| Disorder crime |
Ineffective |
Overall, Project Green Light Detroit had no statistically significant impact on reported disorder crime compared with the control group based on multiple measures from two studies. |
Crime/Delinquency; Public Order Offenses | Circo, Giovanni, and Edmund F. McGarrell. 2021. “Estimating the Impact of an Integrated CCTV Program on Crime.” Journal of Experimental Criminology 17:129–50. See evaluation methods.Circo, Giovanni, Edmund F. McGarrell, June Werdlow Rogers, Julie M. Krupa, and Alaina De Biasi. 2023. “Assessing Causal Effects Under Treatment Heterogeneity: An Evaluation of a CCTV Program in Detroit.” Journal of Experimental Criminology 19:1033–1051. See evaluation methods. |
| Violent crime |
Ineffective |
Overall, Project Green Light Detroit had no statistically significant impact on reported violent crime compared with the control group based on multiple measures from two studies. |
Crime/Delinquency; Violent offenses | Circo, Giovanni, and Edmund F. McGarrell. 2021. “Estimating the Impact of an Integrated CCTV Program on Crime.” Journal of Experimental Criminology 17:129–50. See evaluation methods.Circo, Giovanni, Edmund F. McGarrell, June Werdlow Rogers, Julie M. Krupa, and Alaina De Biasi. 2023. “Assessing Causal Effects Under Treatment Heterogeneity: An Evaluation of a CCTV Program in Detroit.” Journal of Experimental Criminology 19:1033–1051. See evaluation methods. |
Program Goals
The Detroit (Michigan) Police Department noticed that certain environmental features of the city were disproportionately contributing to crime opportunities, as many of the gas stations, liquor stores, and convenience stores generated large numbers of calls for service and were often the locations of street disputes, drug sales, armed robberies, and gang activity (Circo and McGarrell 2021). In 2016, the level of violence at many of these places prompted the police department, with the support of the mayor’s office, to begin a new, place-based initiative, Project Green Light Detroit, to supplement other person-based violence reduction programs already occurring in the city. In 2019, implementation of the program expanded to include retail establishments (e.g., gas stations, liquor stores, bars, restaurants), service-based businesses (e.g., auto-repair shops, car washes, coin-operated laundries), and residential properties (e.g., rental properties, subsidized housing) [Circo et al., 2023].
The initiative established a formal partnership between the city of Detroit, the Detroit Police Department, and small business owners and entails the installation of visible lighting, deterrent signage, and high-definition closed-circuit television (CCTV) cameras at businesses, and direct integration with the police department’s real-time crime center. The goal of Project Green Light Detroit is to establish a proactive partnership between police and businesses to prevent, detect, and deter crime, and to improve case clearance rates.
Program Components
Project Green Light represents a multifaceted approach to improving safety at businesses in Detroit by increasing police response, improving identification of individuals committing crimes, and increasing cooperation between business owners and the police. As part of the program, business owners purchase high-definition surveillance cameras, lighting, and signage that identifies their location as a participant in the initiative. Each business is mandated to purchase a minimum of four cameras that are positioned to monitor all areas accessible to the public on and near the business’s property. Cameras are installed both inside and outside businesses, with inside-facing cameras monitoring within-business activity and outside-facing cameras monitoring activity immediately outside the location. Outside-facing cameras are focused primarily on the businesses’ property, but also capture footage from nearby streets and intersections. The cameras are monitored by the police department’s real-time crime center, allowing crime analysts to evaluate surveillance footage. All participating businesses are required to have high-speed internet to maintain a high-definition livestream monitored at the crime center (City of Detroit 2022). Exterior ambient lighting at participating businesses is also required to meet a certain level of brightness, depending on the business type. Businesses are also required to install and maintain two exterior signs and a door or window decal featuring a “Project Green Light Detroit” logo, along with an external steady-burn green light visible from passing vehicles.
To improve police responsiveness at participating businesses, all calls for service are considered “priority 1”, meaning 911 calls from Project Green Light businesses are prioritized over other similar calls from non-Project Green Light locations. However, the most serious crime incident always takes priority. For example, a theft at a Project Green Light business would not be prioritized over a shooting at a non-Project Green Light business.
Further, Project Green Light supports existing person-based violence reduction programs in the city (for example, Detroit Ceasefire) as these programs can use information from Project Green Light businesses and leverage partnerships with business owners to develop a comprehensive solution to violent crime.
Program Theory
Project Green Light Detroit is primarily rooted in two theories: deterrence and situational crime prevention (Circo et al. 2020). Deterrence theory asserts that individuals with the potential to commit crimes are rational actors who weigh the potential benefits of a criminal act against the potential costs of being arrested and punished (Nagin 2013). Through proactive camera monitoring, improved lighting, deterrent signage, and proactive police response at participating businesses, Project Green Light works to show individuals who may commit a crime the increased risk of being arrested and punished.
Further, situational crime prevention (Clarke 1995) seeks to reduce opportunities for specific types of crime through strategies that make the crime more difficult to complete, increases the risks of committing a crime, reduces the vulnerability of potential victims, and reduces the rewards for individuals who may commit crimes. Project Green Light’s use of cameras linked to the Detroit Police Department’s real-time crime center demonstrates the increased risks of committing a crime, communicates a message about these increased risks, and reduces the vulnerability of potential victims. Situational crime prevention also suggests that strategies should focus on vulnerable locations where individuals with potential to commit crimes may encounter potential victims. Project Green Light’s implementation in identified high-crime businesses in Detroit (specifically gas stations, convenience stores, bars and liquor stores, and areas where illicit drug sales occur), reflects a situational crime prevention approach where high-risk locations implement place-based crime prevention strategies (Weisburd 2018).
Study Title: Estimating the Impact of an Integrated CCTV Program on Crime (which is associated with outcomes Disorder crime and Violent crime)
Research Design
Circo and McGarrell (2021) used a quasi-experimental design with propensity score matching to assess the effectiveness of Project Green Light on crime in Detroit, Michigan after 1 year of implementation. The first phase of Project Green Light, which included 88 businesses that were operational as of December 31, 2016, was evaluated.
Sample
Businesses included gas stations, liquor stores, bars and restaurants, retail and service stores, and other commercial and community outlets. Potential businesses were identified for participation by the Detroit Police Department and the city of Detroit based on a number of factors, such as the number of police calls for service, a history of crime reports, and noted community concerns about the business. Participating businesses were mandated to meet a series of requirements to enter into the program and were subject to inspection to ensure that cameras were operational and that adequate lighting and signage were present.
Data Collection
Crime data were obtained from the Detroit Police Department’s records management system for 1 year prior to Project Green Light (2015) through the implementation period (2016) and for 1 year following implementation (2017).
Outcome Measure
The primary outcomes of interest were the number of monthly crime incident reports. Crime incidents were categorized into two outcome variables: 1) violent crimes (serious violent crime, including aggravated assault, armed and unarmed robbery, and felony homicide) and 2) disorder crimes (misdemeanor assault, possession of drugs, open liquor citations, illegal gambling, public drunkenness, and disorderly conduct). To capture only crime incidents that occurred directly in and around the business, all crimes evaluated occurred within 200 feet of each business. Constructing the final observational units for analysis involved merging crimes with businesses, which was performed in several steps: 1) circular catchment buffers of 200 feet were drawn around each business, 2) all crimes falling within a buffer were retained, while all crimes outside the buffers were eliminated, and 3) crimes were merged with the nearest business within each buffer. Information about each crime included the time, date, location, crime type, and category, and the business where or near it occurred.
Statistical Analysis
To generate the propensity score, a logistic regression was used to estimate the probability of a given business receiving the Project Green Light treatment. This was based on a set of pretreatment covariates, including the annual number of violent crimes and disorder crimes reported at the business in 2015, and census tract-level variables relevant to crime outcomes that reflected the characteristics of the neighborhood in which the business operated: the percentage of the population that included Black individuals, male individuals, unemployed individuals, households with low income, households in poverty, households renting, households with rent greater than 30 percent of their income, households receiving Supplemental Nutrition Assistance Program, and vacant housing units. Optimal full matching was used to create matched sets with one treated unit and one or more control units that minimized the global distance between all matched pairs. Treated Project Green Light businesses could be matched with up to 5 untreated control businesses. After matching, there were 87 treated businesses and 201 untreated control businesses. There were no statistically significant differences between the treated and untreated businesses on any of the pretreatment covariates or outcomes of interest at baseline.
A hierarchical growth-curve modeling strategy was used to model the effect of the Project Green Light intervention on crime from the preintervention period to 1-year postimplementation. Specifically, separate Bayesian negative-binomial growth-curve models were fit, one for each crime type (disorder occurrences and violent crime). The estimates for the effect of Project Green Light were adjusted for residual pretreatment covariate differences, monthly seasonal effects (relative to January), and mean differences in crime reporting by business types (relative to gas stations).
Subgroup analysis was conducted by the number of calls for service at treated businesses, compared with matched untreated control businesses.
Citation:
Circo, Giovanni, and Edmund F. McGarrell. 2021. “Estimating the Impact of an Integrated CCTV Program on Crime.” Journal of Experimental Criminology 17:129–50.
Study Title: Assessing Causal Effects Under Treatment Heterogeneity: An Evaluation of a CCTV Program in Detroit. (which is associated with outcomes Disorder crime and Violent crime)
Research Design
Circo and colleagues (2023) used a quasi-experimental design with a difference-in-difference model to assess the effect of Project Green Light Detroit on crime at individual city parcel addresses in Detroit, Michigan.
Sample
The intervention group (n = 560) included all city parcels enrolled in the intervention between January 2017 and December 2019. Intervention addresses were divided into 11 distinct group-time categories based on the year-quarter in which they enrolled during the 2017 to 2019 intervention period. These intervention addresses included 318 retail establishments, 155 service-based businesses, and 87 residential properties. The comparison group (n = 1,172) consisted of addresses not currently enrolled in or never enrolled in the intervention that had reported at least one crime between 2017 and 2019 as determined by the Detroit Open Data parcel database. Vacant addresses were omitted from the study.
To establish equivalency, the covariates collected included the parcel size, the premise type, and block-level census variables (i.e., the block-level population, the proportion of households receiving Supplemental Nutrition Assistance Program benefits, the proportion in poverty, the proportion renting, the proportion of residential properties vacant, and the proportion of the residents who identified as Black and Hispanic). On average, the intervention and comparison city parcel addresses were similar; however, the intervention group included larger mean parcel sizes than comparison parcel sizes and had a larger proportion of residential properties enrolled in the later cohorts.
Data Collection/Outcome Measures
Crime data were obtained from the Detroit Police Department’s record management system, which contained information on crime incident types, addresses, dates, and geographic coordinates. Owing to a switch in providers of the police department’s record management system, historical data were only available on crimes from December 2016 onward.
Statistical Analysis
A “did” package in the R statistical software was applied to allow the fitting of models able to estimate treatment effects that occur over multiple time periods or have the presence of treatment heterogeneity. Using this method, 2x2 comparisons were made between intervention parcels and comparison parcels for each time period, adjusting for differential group sizes and varying treatment effects. A “doubly robust” estimation procedure was used to estimate the propensity score in the first stage and weight least-squares regression in the second stage. Treatment effects were estimated by aggregating group-time treatment effects based on the time of group assignment, then averaging a treatment effect proportional to each group’s size.
The study did not conduct subgroup analyses.
Citation:
Circo, Giovanni, Edmund F. McGarrell, June Werdlow Rogers, Julie M. Krupa, and Alaina De Biasi. 2023. “Assessing Causal Effects Under Treatment Heterogeneity: An Evaluation of a CCTV Program in Detroit.” Journal of Experimental Criminology 19:1033–1051.
The following outcomes were considered in the scored studies, but CrimeSolutions Study Reviewers determined the evidence was insufficient for a rating to be assigned:
- Measures of property crime
Subgroup Analysis
Circo and McGarrell (2021) examined the change in calls for service (both officer and non-officer initiated) at treated Project Green Light businesses and matched untreated control businesses, from the beginning of the initiative (January 1, 2016) to 1-year postimplementation. They found that officer-initiated calls for service increased at treated Project Green Light businesses, but remained stable at matched untreated control businesses, from the beginning of the implementation period to 1-year postimplementation. However, citizen-made calls for service remained similar at both Project Green Light and matched untreated control businesses, from the beginning of the implementation period to 1-year post-implementation.
These sources were used in the development of the program profile:
Clarke, Ronald V. 1995. “Situational Crime Prevention.” Crime and Justice 19:91–150.
Circo, Giovanni, June Werdlow Rogers, Edmund F. McGarrell, Julie M. Krupa, Alaina De Biasi, Juli Liebler, Shannon Cartwright, and Travis Carter. 2020. Project Greenlight Detroit: Evaluation Report. East Lansing, Mich.: Michigan State University.
City of Detroit. Costs to Get Involved. 2022.
McGarrell, Edmund F., Stephen Oliphant, Alaina De Biasi, and Julie M. Krupa. 2022. Detroit Project Safe Neighborhoods: Final Evaluation Report. East Lansing, MI: Michigan State University.
Nagin, Daniel S. 2013. “Deterrence in the Twenty-First Century.” Crime and Justice 42(1):199–263.
Weisburd, David. 2018. “Hot Spots of Crime and Place-Based Prevention.” Criminology and Public Policy 17(1):5–25.
Following are CrimeSolutions-rated programs that are related to this practice:
Public surveillance systems include a network of cameras and components for monitoring, recording, and transmitting video images. Public surveillance cameras are designed to reduce both property and personal crime. This practice is rated Promising for reducing overall crime, property crime, and vehicle crime, and rated Ineffective for impacting violent crime.
Evidence Ratings for Outcomes
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Crime & Delinquency - Multiple crime/offense types |
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Crime & Delinquency - Property offenses |
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Crime & Delinquency - Vehicle crime |
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Crime & Delinquency - Violent offenses |
A crime prevention strategy that aims to improve the lighting on streets to reduce crime through modifying and improving environmental measures. The practice is rated Promising for reducing crime and property offenses but rated Ineffective for violent offenses.
Evidence Ratings for Outcomes
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Crime & Delinquency - Multiple crime/offense types |
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Crime & Delinquency - Property offenses |
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Crime & Delinquency - Violent offenses |
This program was originally rated Ineffective. It has been re-reviewed based on the change in the program rating instrument. Under the new instrument, CrimeSolutions now rates individual program outcomes and no longer assigns an overall rating.
Rating Process
Program Status
This program is Active.