John E. Eck
Place management theory—a part of routine activity theory—explains why a relatively few places have a great deal of crime while most places have little or no crime. The explanation is the way place managers carry out their four primary functions: organization of space, regulation of conduct, control of access, and acquisition of resources.
Place managers are those people and organizations that own and operate businesses, homes, hotels, drinking establishments, schools, government offices, places of worship, health centers, and other specific locations. They can even operate mobile places such as busses, trains, ships, and aircraft. Some are large—a multi-story office tower for example—while others are tiny—a bus stop, for example. Place managers are important because they can exercise control over the people who use these locations and in doing so contribute to public order and safety. Consequently, it is important to understand place management, how it can fail, and what one can do to prevent failures.
Place management has implications beyond high-crime sites. When crime places are connected, they can create crime hot spots in an area. The concentration of high crime places can inflate crime in a neighborhood. Moreover, place management can be applied to virtual locations, such as servers, websites, and other network infrastructures.
There is considerable evaluation evidence that place managers can change high crime locations to low crime locations. Research also shows that displacement to other places, though possible, is far from inevitable. Indeed, research shows that improving a high crime place can reduce crime at places nearby places. Although much of this research has studied how police intervene with place managers, non-police regulatory agencies can carry out this public safety function.
Anthony Petrosino, Claire Morgan, and Trevor Fronius
Systematic reviews and meta-analyses have become a focal point of evidence-based policy in criminology. Systematic reviews use explicit and transparent processes to identify, retrieve, code, analyze, and report on existing research studies bearing on a question of policy or practice. Meta-analysis can combine the results from the most rigorous evaluations identified in a systematic review to provide policymakers with the best evidence on what works for a variety of interventions relevant to reducing crime and making the justice system fairer and more effective. The steps of a systematic review using meta-analysis include specifying the topic area, developing management procedures, specifying the search strategy, developing eligibility criteria, extracting data from the studies, computing effect sizes, developing an analysis strategy, and interpreting and reporting the results.
In a systematic review using meta-analysis, after identifying and coding eligible studies, the researchers create a measure of effect size for each experimental versus control contrast of interest in the study. Most commonly, reviewers do this by standardizing the difference between scores of the experimental and control groups, placing outcomes that are conceptually similar but measured differently (e.g., such as re-arrest or reconviction) on the same common scale or metric. Though these are different indices, they do measure a program’s effect on some construct (e.g., criminality). These effect sizes are usually averaged across all similar studies to provide a summary of program impact. The effect sizes also represent the dependent variable in the meta-analysis, and more advanced syntheses explore the role of potential moderating variables, such as sample size or other characteristics related to effect size.
When done well and with full integrity, a systematic review using meta-analysis can provide the most comprehensive assessment of the available evaluative literature addressing the research question, as well as the most reliable statement about what works. Drawing from a larger body of research increases statistical power by reducing standard error; individual studies often use small sample sizes, which can result in large margins of error. In addition, conducting meta-analysis can be faster and less resource-intensive than replicating experimental studies. Using meta-analysis instead of relying on an individual program evaluation can help ensure that policy is guided by the totality of evidence, drawing upon a solid basis for generalizing outcomes.