The New York City Police Department (NYPD) has made enforcement of laws against disorder and quality-of-life offenses a central part of their policing strategy. Concomitantly, New York City (NYC) experienced a renaissance in orderliness, cleanliness, tourism, real estate value, and crime reduction, although other problems such as poverty, unemployment, drug abuse, racial tensions and homelessness persist. This paper examines quality-of-life policing practices in NYC, describes the philosophical underpinnings, explores the critical response to the program and presents lessons of potential relevance to other policing organizations in the U.S. and around the world.

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This research reports the relationship between serious crime, drug arrests, and nuisance abatement seizures in New York between the years 1995 and 2001. Over the last decade, New York City experienced a dramatic decrease in crime. One of the more prominent explanations of this crime decrease is a variant of the “Broken Windows” theory posited by James Q. Wilson and George L. Kelling in 1982. This research tests this theory in that it uses drug arrests and nuisance abatement closings as a proxy for “broken windows” and FBI Part I Index crimes as a measure of serious crime. The results of the analyses showed that the rate of marijuana arrest and the closing of drug locations through nuisance abatement statutes are inversely related to the crime rate, and that the rate of controlled substance arrest is directly related to crime rate.

In the mid-1990s, the New York City Police Department (NYPD) developed a new approach to address drug conditions called the narcotics initiative. Centered on a three-prong enforcement strategy, the initiatives were concentrated in specific clusters of precincts and successively deployed over a period of several years throughout New York City. This study examines the impact of two initiatives deployed in Queens County, NY, and examines the effectiveness of the initiatives based on the decrease in crime and increase in enforcement associated with their deployment. Hierarchical linear modeling (HLM) is used to examine the data, and the results showed limited impact in community conditions after the initiatives were deployed.

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