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Anti-graffiti law enforcement, real estate value and corporate

gentrification in NYC: Challenging the broken windows theory*

Yael Berda

Department of Sociology

Paper presented to the Center for Arts and Cultural Policy Studies, Woodrow Wilson School of Public and International Affairs

Princeton University

December 2009

Abstract: This paper, the first quantitative study of anti-graffiti law enforcement,

asserts that studying police “stop-and-frisk” practices offers insights into the distribution

of policing as a government resource, particularly municipal administrative discretion

and selective enforcement, showing that the influences on the distribution of law

enforcement diverge from those claimed by the New York City government. The study’s

findings challenge the claims that the NYPD employs its resources based on general

crime rates, based on the broken windows theory and shows that police practices

regarding graffiti are associated with economic interests.

Using Poisson regression and GIS maps of graffiti enforcement as well as

demographic and real estate development parameters, I test a battery of hypotheses

regarding the effects of general law enforcement patterns, gentrification of

neighborhoods through changes in population characteristics and gentrification

instigated by corporate capital investment in real estate. My findings show that, contrary

to the broken windows theory of zero tolerance policing, anti-graffiti policing is most

affected by corporate real estate residential development or corporate gentrification.

Anti-graffiti policing is more associated with measures of real estate development than

measures of population change, pointing to the influence of elite economic interests

rather than popular influence on municipal decision-making. These findings show a

disturbingly uneven distribution of policing resources in the public space, demonstrating

* I thank Oscar Torres and Pier Antoine Kremp for their incredible help with the statistical analysis,

Tsering Wangyal Shawa for teaching me GIS and the geographical library for obtaining maps, Ray Carrera from the Graffiti removal project in the Mayor’s office for the data and information, Tomer Chen for

helping me understand some about real estate in NYC, for the great ideas and for the data from the

department of buildings. I thank Paul DiMaggio for his teaching and patience. Richard Lachmann for

sharing his important insights and to the Center for Arts and Cultural Policy Studies at Princeton University

for their support.

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the influence corporate capital has on patterns of policing in the urban environment and

the role of land use interests on the political economy of law enforcement.

Background

Since the late 1970’s graffiti is a major feature of the urban experience and plays

a central role in the debate over city governance, crime, culture, identity and

development. For some, graffiti is the vibrant, pluralistic self-expression of a generation,

a visual symbol of urban democratic culture. For municipalities, business leadership and

corporations, it is a growing hazard, an assault on private property and a destruction of

public space. For the police, graffiti is another set of disruptions to law and order,

demanding separate strategies and responses. Proponents of the broken windows theory

posit that the presence of graffiti is an indicator of crime levels and disorder in a

neighborhood.

Sociologists have been fascinated by the graffiti phenomenon, exploring graffiti

as a subculture or as a particular form of adolescent deviance, usually linking graffiti to

gang activities. This article views graffiti from a different angle, focusing on the political

economy of anti-graffiti law enforcement. I use the contested issue of graffiti to explore

the uneven distribution of policing as a public resource. I use Molotch’s framework of

“the city as a growth machine” to decipher the spatial patterns of law enforcement on

graffiti offences in New York City. The findings show the uneven spatial distribution of

law enforcement resources, represented by the amount of stop-and-frisk activity.

Consistent with Molotch’s theory, that political choices and administrative allocations are

influences by coalitions of property owners, the findings show through two mechanisms,

that the interests of real estate corporate development drive the policing. But before

turning to the study and the findings, a short outline of the sociological research on

graffiti as an urban phenomenon is in order.

Richard Lachmann’s (1988) groundbreaking article joined the literatures on

subcultures, deviant careers, and the art world, offering tools for understanding graffiti as

a complex intersection of these three axes. Lachmann showed that graffiti making was a

skill taught and learned during the short life cycle of a graffiti career, usually spanning 2

to 5 years during adolescence. Lachmann’s was the first study that acknowledged the role

of anti-graffiti law enforcement as an influence on groups of graffiti makers, both curbing

and inciting graffiti activities.

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Scholars of Law and Society employed a different approach to the research of

graffiti and focused primarily on the differentiation between graffiti as art and graffiti as

crime (Gomez, 1993) and the public policy responses to it in the urban arena. This

scholarship has formed various models for understanding the urban graffiti battleground -

some have used the lens of the First Amendment and freedom of speech, while Critical

Race Studies scholarship has interpreted the battle against graffiti as yet another example

of racially biased policy (Goldberg, 1993) against minorities, primarily blacks and

Latinos. While this could have been correct in the 1980’s and 1990’s, contemporary

research indicates that that the population of graffiti makers is no longer predominantly

black or Latino, it is mostly white (Snyder, 2006).

While graffiti, it’s makers and their “subculture” has been heavily investigated,

little research has been conducted about municipal responses to graffiti as a particular

urban phenomenon. This gap is due to the prevailing viewpoint that graffiti is a subset of

offences affecting quality of life that includes loitering, soliciting, vandalism, public

lewdness and other offences of this nature. To challenge this view, in this article, I

combine and data from 5 administrative sources. I find that graffiti is a separate

phenomenon, and therefore the influences on decision-making regarding law enforcement

resources dedicated to graffiti diverge from the influences on quality of life policing, and

are primarily associated with corporate real estate development interests.

New York City’s “broken windows” based policing

In New York City, a highly charged debate concerning graffiti, it’s place in the

urban environment and the public response to it, has persisted since the official adoption

of the broken windows theory in the early 1990s. At the time, mayor of New York, Rudy

Giuliani and world renowned former NYPD chief William Bratton transformed urban

crime management to a “zero tolerance” policing policy (Green, 1999; Mcardle,

2001;Vital, 2008). Since than, political debate has focused on the distinctions between

private and public space, specifically on freedom of expression in the public space. The

official stance of the NYC government was that unregulated expression in the public

space was primarily regarded as an indicator of crime and disorder. Flowing from that

classification, it was regarded as a social and economic hazard by those who profit

materially from the city’s properties value. This viewpoint propagated a growing political

economy of anti-graffiti law enforcement. This economy includes administrative

initiatives, development plans, zoning, real estate values, and enforcement and prevention

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methods, including a multi billion-dollar industry geared towards graffiti detection,

removal and prevention1.

Since the late 1980’s, graffiti “transformed from a minor form of vandalism and

youth mischief into a significant crime engaging substantial police resources” (Vitale,

2008). New York City, the epicenter of graffiti in the 1980’s and 1990’s, continues its

role as the core of political, economic and executive innovation for finding solutions for

the graffiti “problem”. Since 1996, multiple graffiti directed task forces, enforcement

campaigns, and enforcement organizations have proliferated in New York City, and the

City has sponsored programs for graffiti removal, including a rewards program to

encourage the public to report on graffiti offenders. Since 2003, the annual number of

police stops and arrests for graffiti related offences has risen continuously.

Despite this rich field of interaction between municipal government, elected

officials, entrepreneurs, and graffiti artists, the sociological engagement with graffiti has

focused solely on the graffiti writers or artists, on “the intricacies of graffiti culture, from

the perspective that graffiti is a sub cultural activity performed by a sub cultural group,

rather than as a significant aspect of the negotiation of contemporary social space”

(Young & Halsey, 2002: 166). While graffiti ethnographies have flourished, some

viewing graffiti as deviance and part of “gang culture” and others viewing as a form of

public expression, the organizational, administrative, and economic aspects of the “war

on graffiti” have yet to be explored. This study contributes to multiple fields of study: to

urban sociology, in discovering the political economy of anti-graffiti law enforcement,

primarily new associations between urban land-use and law enforcement. In the field of

socio-legal studies, it contributes to structures of governance, enforcement and

administrative discretion, as well as to the understanding of mechanisms of unequal

distribution of law enforcement and their relationship to political and economic factors

(Zukin, 1982; Harvey, 2001).

This paper provides the first quantitative analysis of graffiti2 while focusing on

policing practices, in an attempt to discover the politics of graffiti law enforcement. The

1 The Anti-graffiti industry has grown extensively in the last fifteen years. Since 1982, 36 patents have

been registered for a range of anti-graffiti paint, removal equipment, and construction materials. 75% of these patents have been registered since 1996. [US Patent & Trademark Office, Patent Full Text and Image

Database] Quarry: May 22, 2009. With municipalities in North American cities as their primary clients,

graffiti removal companies have proliferated in the last decade as cities spend more or graffiti removal.

Philadelphia’s anti-graffiti budget for 2009 is $1.125 million, Ottawa increased it’s budget from $400,000

to $ 2.3 million in 2008 and Chicago’s “graffiti blasters’ foster a budget of over $1 million in 2009.

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study makes two conceptual shifts, addressing administrative discretion of law

enforcement in the urban environment:

1. Studying up: I study policing practices on graffiti and quality of life offences

following Howard’s Becker invitation in The Outsiders (1963) to sociologists to include

in their field of research the categorizers of deviance, and not only the categorized, the

“deviants” themselves. “We must study those in the upper levels of the social structure -

the moral entrepreneurs who not only shape new definitions of the acts which they

criminalize, but establish and grow formal rules and formal organizations as part of this

criminalization”(P.163). The moral entrepreneurs Becker refers to are not law enforcers.

Traditionally, the “growers” of organizations and rules that criminalize actions or groups

are public officials, politicians, corporate figures, or community leaders. However,

studying the practitioners of law enforcement, who control space through their daily

practices, provides a gateway to view the associations between urban street art or

vandalism (depending on who is classifying it), urban real estate development interests

and administrative discretion in metropolitan law enforcement.

Shifting the focus from the graffiti makers, the people that engage in graffiti as

part of their daily life, to patterns of police discretion and enforcement is crucial for

understanding the complex urban microcosm in which communities, businesses,

developers and politicians negotiate the use of public space. The police constitute the

“most potent and symbolic form of governance in the modern city” (Herbert, 2001), and

police officers are officials whom are granted the widest breadth of executive discretion.

The influences on this discretion, and in turn on policing practices, serve as indicators for

political and administrative mechanisms that govern enforcement. As Max Weber

suggests, we can “look over the shoulder” of the bureaucrat to decipher what are the

driving forces of graffiti law enforcement.

2.The political economy of law enforcement and gentrification: Policing is a

spatial field of action in which enforcement is directly linked to territory (Herbert, 1997).

Due to a chronic lack of resources, policing demands discretion in setting the priorities

for deployment of urban resources. This discretion is a function of the strategy and style

(Skolnick, 1968) of policing. Moloch argues that city maps are “interest mosaics” and

each locality represents an aggregate of land-based interests (Molotch, 1967, 1975). The

2 This paper is the first quantitative analysis of graffiti, excluding audit studies of graffiti, which have been

conducted in Australia alone.

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land-use interests of each community will shape their interaction with government

powers to gain resources that can enhance the growth potential of the land area. From

this viewpoint, quality of life policing and graffiti policing are governmental resources

that communities mobilize and use in order to enhance their land-use values. The practice

of police “stop-and-frisk” provides an occasion for police to have contact with persons

who have been involved in (or presumed so) in low-level criminality (including “quality

of life” offences) without having to make a formal arrest (Spitzer, 1999). This

“spontaneous” from of policing differs locally based on spatial priorities and enforcement

practices that target neighborhoods, maintaining certain socioeconomic characteristics or

“hotspots” of suspected crime (Green, 1999). In studies of policing practices, especially

regarding racial biases, sociologists have focused on the population composition and

demographics in various neighborhoods as an explanation of variation in policing.

However, since policing is a territorial practice, and graffiti is an offense that is

dependent on access to urban space, in this study I use parameters that measure the

characteristics of space. As opposed to the traditional demographic variables, I use

administrative data that provides variables such as building permits and land-use.

Observing the differences in the spaces that are policed, rather than the populations,

matches the unit of analysis to the territorial nature of the phenomenon studied.

The Puzzle

What are the forces that drive graffiti enforcement? What is the spatial

distribution of graffiti enforcement in New York City? How do the inequalities in the

spatial pattern of graffiti enforcement reveal the interests that drive law enforcement? Is

graffiti simply a subset of quality of life, or “zero tolerance” policing, guided by the

broken windows theory (as the NYC government claims), or are other forces informing

what spaces will be policed more than others? What is the relationship between

gentrification, the changing nature of neighborhoods and graffiti policing, and the

interests that drive enforcement?

The structure of the paper is as follows: I will first introduce conflicting theories

regarding the forces driving law enforcement, offering hypotheses to test the possible

forces driving the spatial pattern of anti-graffiti policing. I will then refer to the history

of “zero tolerance” and quality of life policing in New York City and show the different

spatial distribution of quality of life policing and general enforcement rates. I will offer

the results of empirical tests showing that graffiti enforcement is not a subset of quality of

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life enforcement, and that the forces that drive graffiti policing differ from those that

drive quality of life policing. Than, I turn to exploring the mechanisms driving graffiti

enforcement. I focus on the theory that posits that elites influence graffiti policing. I

explore the relationship between gentrification and graffiti policing examining different

possible mechanisms and discuss the findings that while quality of life policing is directly

linked to local business and population interests, particularly middle class ones, results

suggest that the amount of policing resources against graffiti is influenced by the land-use

prospects of the neighborhood and the prospects for economic gain through real-estate in

it. In the conclusion, I revisit the to broken windows and neighborhood disorder theory,

and suggest that these findings imply a different set of relationships between corporate

real estate interests and policing practices in the metropolis, one that has not been

addressed by the literature supporting the broken windows theory. I elaborate on the

description of graffiti enforcement hotspots, which are predominantly neighborhoods in

the early stages of development of “corporate gentrification.”

In order to situate the analysis in the context of the organizational and political

climate of graffiti policing, I offer a brief history of graffiti policing in New York City.

A brief history of graffiti policing in New York City

In 1992, the legislation that categorized graffiti writing as a crime was enacted.

Articles 145 & 146 in the New York state penal code defined graffiti as a criminal act of

the un-commissioned marking of property, constructing graffiti as an offense based on its

spatial characteristics. In 1995, the sale of aerosol spray paint to teenagers was inscribed

as a criminal offence in title 10-117 of the New York Administrative Code. Yet more

consequential than the actual legislation of anti-graffiti laws was the law’s

implementation and administration: the bureaucratic and professional practices, public

opinion and reaction to the law, and the involvement and engagement of social,

economic, political and geographic communities effected by the law.

Two types of regulatory processes have developed since the legislation

criminalizing graffiti was first enacted. One is “hard” regulation by government; the other

is “soft” regulation by the real estate and development construction market. The latter has

propagated the emergence of a multibillion-dollar industry geared to the research and

development of anti-graffiti paint, apparatuses and surveillance gear. The former resulted

in a multi million-dollar administrative reorganization delegated to combat graffiti, above

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ground in NYC3. Simultaneously, in the last 15 years, graffiti has been granted

recognition and power as a legitimate and sought after art form, as graffiti art is featured

in major art museums, used in advertisements of major companies, and distinguished by

large coffee table books as the authentic art form in a globalized world (Ganz, 2004,

Banksy, 2007, Ket, 2006, Gastman, Neelon & Smyrski, 2007). Later in this article, I

revisit the issue of graffiti as a legitimate art form

The first organization formed to specialize in anti-graffiti enforcement was the

Metro Transit Agency’s vandal squad in 1989, designated to combat the graffiti makers

whose main canvass was the body of the subway trains (Austin, 2001). In 1996, the

NYPD launched its anti-graffiti vandalism unit within the special operations division. In

1998 Rudolph Giuliani, created the first anti-graffiti drive. In September 2004, Mayor

Bloomberg formed the contemporary anti-graffiti task force, a body designated to

coordinate the anti-graffiti enforcement efforts in the city. Since 2004, there has been a

steady rise in the number of stop-and-frisk activities, in which police officers stop and

report persons suspected as committing graffiti–related offence. In this article I refer to

each stop-and-frisk-event as a “graffiti stop”.

The graph above shows the steady rise in graffiti stop between the years 2003 –

2007. The interpretation of this significant rise in graffiti stops remains a contested issue

in city politics and a source of conflict between different enforcement agencies. City

council members and business improvement districts (BIDs), as well as anti-graffiti

community groups, complain that there is rise in graffiti. On the other hand, the NYPD

argues there has not been a rise in graffiti and assert that the rise is a product of better

measurement, including use of the NYPD’s mapping and statistical database, which has

3Graffiti “below the ground”, in the subway system, is persecuted by the Metro Transit Authority, which

have a separate administrative structure, which was also the first one in New York city (since 1982).

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been praised an important technological aid to the drop in general criminal activity in

New York City. NYPD Assistant Chief Michael Collins blames the statistical surge on a

new policy requiring officers to fill out written report for every graffiti complaint. “We

believe the increase in graffiti incidents is due to increased reporting, not an upsurge in

the crime itself” (Belenkaya, 2008). In response to the alleged rise in graffiti events in the

city, in 2005, Mayor Bloomberg increased the number persons employed by the anti-

graffiti initiative to 80 and designated graffiti coordinators in the police precincts

(Bloomberg, 2005) in order to re-motivate precinct responsibility for graffiti

enforcement, which had dwindled since the 2004 centralization of enforcement.

Theory and hypotheses

The politics of enforcement

This article is concerned with the politics of law enforcement, particularly the

influences on the decision to allocate resources to enforce anti-graffiti laws. I will test

hypotheses based on three different theories, each theory predicting a different set of

interests that may drive law enforcement. First, I use the broken windows framework

since the city of New York adopted it and enacted “zero tolerance policing”. In order to

test the effects of broken windows theory based policing I test how general enforcement

rate 4and crime rate5 affect graffiti policing. Second, I use political scientist Katherine

Beckett’s theory on political forces that influence law enforcement through the

constitutive and definitional practices of elites. I test the relationship between population

characteristics and the amount of graffiti enforcement. Third, I use the insights of

Molotch and Logan, who view metropolitan land-use as a map of the political economy

of financial and property interests. Based on their theory of “ the city as a growth

machine” I test the ways in which gentrification is a primary driving force of anti-graffiti

enforcement and generate hypotheses testing the associations between “old”

gentrification by changes in population composition and “new” gentrification by

corporate developers and anti-graffiti law enforcement.

Broken windows and “zero tolerance policing”: is graffiti a quality of life offence?

Based on the classic article by Wilson and Kelling (1982), broken windows

policing is often trumpeted as the cause of the reduction of crime in the last two decades,

4 I measure general enforcement rate by the amount of police stops made in a sub borough, when

controlling for the population in that area. 5 I measure crime rate by a count of reported index crimes: Murder, rape, robbery, grand larceny and

aggravated assault, controlled by the population in the area.

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in New York City and nationwide (Herbert, 2001:446). Empirical evidence supporting

the broken windows theory has been collected in urban metropolises across the nation

(Skogan, 1990; Samson, 1993). However, others have contested the logic of the broken

windows theory, critiquing its empirical claims as well as its normative effects on

profiling discrimination practices by enforcement agencies. Order-maintenance policing

uses a variety of methods to target minor disorders and low-level crime as a way of

establishing a “zero tolerance” climate of law and order. This emphasis on disorder can

be characterized as “quality of life policing” because it aims to eliminate the daily

annoyances to the urban public as the method through which serious crime is reduced

(Vitale, 2005:100).

This mode of policing is still the basis of policing politics and practices. Police

officers, mostly through increased “stop – and- frisk” methods, focus their attention on

offences such as loitering and prostitution as much as they do on robbery and murder.6 In

the New York 2005 state of the city address, Mayor Bloomberg referred to quality of life

policing, which includes anti-graffiti enforcement: “We’re going to continue to prevent

quality of life crimes. Because whether it's jumping turnstiles, aggressive panhandling,

or other "broken windows" offences - some may say they're petty crimes, but if left

unchecked, they permit more serious crimes to flourish. That's why we're launching a

major new initiative to stop graffiti. It will include an 80-member NYPD anti-graffiti task

force, with coordinators in each police precinct.”

Graffiti is considered to be one of the most potent indicators of neighborhood

disorder and is one of the main offences that considered a “quality of life” offence by

both public officials and scholars (Kelling & Coles, 1998; Katz, Webb & Schaefer, 2001;

Fagan & Davies, 2001, Harcourt and Ludwig, 2006). Based on the broken windows

driven zero tolerance policing strategy, I generate two hypotheses comparing the policing

of quality of life offences and graffiti offences, in order to test if graffiti is in fact a

“quality of life offense”.

Hypothesis 1a:Broken windows: in neighborhoods where there is a higher

general enforcement rate for all offences and a higher crime rate, there will be more

quality of life policing.

6 In his 2009 state of the city address, Mayor Bloomberg declared he intended to propose legislation

deeming a person’s 7th Quality of life offense a felony. (Bloomberg state of the city address, January 16th,

2009, city university of New York.)

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Hypothesis 2a Broken windows: The higher the general enforcement rate and

the higher the crime rate, there will also be a higher amount of police stops for graffiti

offences.

A major critique that refutes broken windows assumptions is one that claims

that law enforcement rates are about “policing poor people in poor places”. In other

words, law enforcement is higher in neighborhoods that have poor populations and more

minorities. This critique offers a theory and convincing empirical evidence that suggest

that neighborhood characteristics (racial composition and poverty) are stronger predictors

of stops than general crime rates and disorder (Fagan and Davies, 2001, Gelman &

Davies 2001). Fagan and Davies demonstrate that there is little evidence to support

claims that there is more policing in places where there are signs of physical disorder. As

an alternative, they show how stop-and-frisk practices are higher minority

neighborhoods. Based on their findings, refuting broken windows assertions, I generate

two hypotheses testing the association between poverty levels7 and amount of quality of

life and graffiti policing.

Hypothesis 1b: policing poor people in poor places: The higher the poverty level,

the more quality of life policing in a given neighborhood.

Hypothesis 2b: policing poor people in poor places: The higher poverty level in a

given neighborhood, the higher the number of anti-graffiti police stops.

A deeper exploration of the politics of law enforcement in New York City shows

that community level political action plays an important role in shaping police activity

(Zhao, 1996; Bass, 2000). Vitale (2005, 2008) shows that the driving forces behind the

institutional innovation that drove the NYPD’s shift to quality of life policing, were

“business improvement districts” (BID’s) that forced the NYPD into policing public

annoyance offences (see also Duneier, 1999). “ The GCP (Grand Central Partnership)

put direct pressure on the police and the city to take disorder more seriously. …They

engaged in a discursive shift that changed the nature of the debate about the relationship

between homelessness, disorder, crime and neighborhood stability. Stepping around

homeless people was no longer an unpleasant annoyance, it was now the central problem

facing midtown Manhattan, and by extension, the rest of the city” (Vitale, 2005: 111-

112). Based on these accounts, we could predict, that if businesses and white middle class

people were the driving force behind enforcement policies, they would have a vested

7 As an indicator of the poverty level in a neighborhood, I use the percentage of the population in a

neighborhood receiving income assistance

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interest in policing middle class areas. Contrary to broken windows predictions, quality

of life policing would not take place in the most heavily crime stricken areas but rather in

more gentrified areas.

The influence of elites on law enforcement resources

A widely accepted theses on the causes of increases in law enforcement is the

“democracy – at – work” thesis, which asserts that “the increasing threat of criminal

victimization and the anxiety that it engenders explain the adoption of law and order

policies” (Beckett, 1997) and that “public opinion was well ahead of political opinion in

calling attention to the rising problem of crime (Wilson, 1975).

Katherine Beckett challenges this public pressure thesis by estimating the degree

of association between reported incidents of crime and levels of public concern about

crime. Beckett (1997: 15 – 23) found no association between reported crime rates and

corresponding public concern. Her results suggested a close relation between political

initiative and public concern about crime. Beckett argues that the complex relationship

between crime rates, public concern and political initiative indicates “popular attitudes

about crime … have been shaped to an important extent by the definitional activities of

political elites.” (Beckett, 1997: 27). I use Beckett’s findings that enforcement decisions

and resource allocations are shaped by political elites, to generate hypotheses testing

sources of influence on allocation of enforcement resources toward quality of life

policing and anti-graffiti policing in NYC. If elites shape decision-making, then we

would expect neighborhoods where populations are “stronger”, that have higher levels of

income, education and property ownership, to have higher levels of quality of life

enforcement.

Looking at the phenomenon from a different approach, Molotch and Logan

conceptualize the city as “a growth machine”. They argue that city maps are projections

of interests of property owners, who affect government decisions in order to increase

their resources and raise their property values. These communities of interests form

political coalitions in order to influence government actions. But how can we quantify

and measure political and economic land-use interests?

In this case, nature of graffiti as offence against property and public space is

helpful, in the context of the spatial transformation of the city termed gentrification.

While enforcement agencies and scholars both treat graffiti as a quality of life offence,

graffiti offences differ particularly in that graffiti does not directly threaten individuals or

individual safety, nor public wellbeing and environment, but, rather, urban walls and real

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estate. If graffiti is an offence against public space, gentrification can be a powerful

indicator of the conditions that increase anti-graffiti law enforcement. Graffiti is a

battleground of claims over public space. Therefore, focusing on the land-use and real

estate characteristics of neighborhoods and precincts provides insights into the influences

on administrative discretion regarding the allocation of policing resources in this

contested field.

Gentrification is “the production of urban space for progressively more affluent

users(Hackworth, 2002)8; a phenomenon that influences law enforcement practices in a

particular neighborhood, although the relationship between gentrification and crime

remains complex and inconclusive (McDonald, 1986). Spearheaded by small-scale

homeowner occupiers prior to the 1990’s (a period I call “old gentrification”), in the last

decade, gentrification has been propelled by corporate developers, highly integrated with

finance capital and in many cases by transnational corporations (Logan, 1993). This is a

significant change in the gentrification phenomenon because the behavioral patterns of

homeowner occupiers and profit-seeking seeking land - development firms differ greatly,

especially in term of their power and influence over urban governance bodies. Wyly and

Hammel (1999) argue that changing urban policy, geared toward transforming the city’s

social and economic topography through this process, now fuels that gentrification.

Gentrification has multiple definitions in sociology, geography and criminology,

which are important for the following analysis. Sociologists view gentrification as a

process that focuses on the changing population of a neighborhood, usually studying the

displaced population. Geographers have viewed gentrification as a process of change in

land-use, housing values, and zoning. I incorporate the two types of definitions into the

research design in order to link associations that have been overlooked previously, due to

disciplinary differences. The definition of gentrification is also important in order to trace

influences on administrative decision-making, particularly the time of the influence.

While population changes will influence decision-making after the population has

changed, land-use changes serve as indicators for decision-making before the population

change, based on development interests in a neighborhood. The definition is important

for the periodization of gentrification, since corporate gentrifies begin to act in a

neighborhood years before the gentrifying population inhabits it. In other words,

8 This definition is an updated version of the previous agreed upon definition geographers and sociologists

held for gentrification which was 'the rehabilitation of working- class and derelict housing and the

consequent transformation of an area into a middle-class neighborhood.' (Smith and Williams, 1986)

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observing a population or observing the physical space of a neighborhood will reveal

different mechanisms of influence on allocation of policing sources, which occur at

different times. Most of the recent sociological work on gentrification focuses either on

the displaced population (Freeman 2006) or on the sought-after populations, phenomena

labeled “studentification” (Smith, 2005) or “Super –gentrification,” referring to historic

neighborhoods geared to draw Wall Street executives (Lees, 2003). Incorporating

multiple aspects of gentrification, those focusing on land–use interests and those focusing

on population changes, facilitates our understanding of the mechanisms influencing the

allocation of policing resources.

Based on Beckett’s insight on the influence of elites on law enforcement, and

Molotch and Logan’s theory that maps the city according to land-use interests of property

owners that pressure city government to allocate resources toward their financial

interests, with hypotheses 3a though 3d I test the associations between the two different

types of gentrification and the enforcement of quality of life offences and graffiti

offences in order to determine which mechanism better describes influence on police

stop-and-frisk activity.

Hypothesis 3a: gentrification through population: the higher the upwardly

mobile change in population demographics in an area the higher the amount of police

stops related to graffiti offences. Simply put, if a neighborhood is more gentrified, it will

have more anti-graffiti policing. (I define gentrification as an increase in the percentage

of persons that have higher income, professional occupations, and are predominantly

white.)

Hypothesis 3b: gentrification through population: the higher the upwardly

mobile change in population demographics in an area the higher the amount of police

stops related to quality of life offences.

Hypothesis 3c: The city as a growth machine: corporate gentrification: the higher

the number of residential buildings with plans under construction by development

companies in an area, the higher the level of graffiti enforcement. Implementing the

thesis that capital investment and powerful economic actors define and prioritize crime

and enforcement, this hypothesis posits that the political pressure on enforcement

agencies will stem from development corporations that have a profit making interest in

graffiti policing. An area will be more heavily policed for graffiti in if it is a prospective

neighborhood for gentrification.

15

Hypothesis 3d –The city as growth machine: the higher the number of entire

residential buildings with plans under construction by development companies in an area,

the higher the level of graffiti enforcement.

Data and methodology:

Using Poisson regression and Geographical Information Systems (GIS) software,

I explore the relationships between graffiti law enforcement, neighborhood demographic

characteristics,9 and development and construction information. I use GIS in order to

describe the spatial pattern of enforcement and as a tool for interpretation of the

associations found in the Poisson regressions. I use Poisson regression because the

dependent variables I am testing are counts10: the number of police stops for quality of

life offences and the number of police stops for graffiti offences. The Poisson model is

most appropriate when using the NYPD data, which provides a complete count of stop-

and-frisk police reports, by police precinct, a demarcated geographical unit, during the

year 2006.

For the analysis I used five data sources:

1. The NYPD stop-and-frisk survey of 2006, which documented all reported stops

made by police officers in New York City in 2006, using stops as an indicator for ground

level law enforcement.11

2. Summary statistics of graffiti removals from the graffiti removal initiative in

the quality of life department in the community assistance unit in the New York City

mayor’s office for the years 2006 – 2007, as an indicator for the number of graffiti in a

given neighborhood.12 The number of graffiti removals provides an estimation of the

prevalence of graffiti, because by a local law homeowners are required to remove graffiti

9 I am using the term “neighborhood” for simplification purposes. The unit of analysis is a community

board, a political boundary that indicates the smallest geographic area bearing a political body viz a vis the

New York City government and administrative bodies.

10 Poisson regressions are most appropriate when each observation is a positive and independent integer.

The model is justified when the variable considered describes the number of occurrences of an event in a

given, consistent time span 11 The geographic area of the Stop-and-frisk survey is 77 precincts in 5 boroughs. To match this data with

other sources, I aggregated to the next smallest geographic area, community board, of which there are 55.

12 Graffiti removals seem to be the closest indicators for the prevalence of actual graffiti in a given

neighborhood. While there is no objective way to know how much graffiti exists at any given moment, The only possibility for assessment of the number of graffiti exists by proxy alone since as a quality of life

offense graffiti does not have, as index crimes do, direct victims and therefore the use of victim reports as a

measure of crime rate is not possible. The measurement of enforcement alone as an indicator of crime rate

has been deemed ineffective since it reflects an official bias and discretion toward events Warner & Pierce,

1993).

16

within 60 days of its appearance. The New York City government’s mode of

implementation of the of the law is by providing the costly removal service free of

charge, requiring homeowners to sign a liability waiver due to the possible damage

graffiti removal can cause building structures, or to remove it themselves and notify the

city. Failure to sign such a waiver may result in a $ 300 fine.

3. The New York Housing and Vacancy Survey (NYHVS) of 1999 & 2005 were

merged to provide indicators of the economic and demographic changes within a given

neighborhood.13 The NYHVS includes various data. Data collected on persons

(approximately 37,000) including race, occupation, and level of education was matched

with data collected on their matching households (approximately 15,000). In the analysis

I included the following variables: median household income, gross rent, and gross rent

per room, variables identifying owner occupation of the household and rentals under rent

stabilization. The matched data were aggregated to sub-boroughs, the smallest geographic

unit possible using this survey. Finally, I created a dataset in which the variables used

were percentage changes in demographic characteristics such as racial and occupational

composition of the population and percentage changes in housing variables including

housing value, rate of rent per room, and rent stabilization.

4. As a measurement of corporate gentrification, I used the New York City

Department of Buildings database, which documents building permits approved in

2006.14 As independent variables I use only permits given to for profit development

corporations to build or demolish whole buildings.15 These include all Planning

Department permits that were approved in 2006.16 In order to have a permit approved in

2006 a development corporation had to have financed and bought the land lot at least one

year prior to obtaining the permit. This lag in time serves as an indicator for the intention

to invest in an area, usually prior to the rise in real estate value in an area.

13 The variables used were percent changes in a given sub – borough between 1999 – 2005: population

composition by race; median income; type of occupation; level of education; housing value; median rent.

While the findings were not significant, this proved highly informative as to the unit of analysis to be used

n order to measure corporate gentrification.

14 The database includes all requests for building permits. For the purpose of using construction and

development permits as a measure of gentrification, I selected only cases in which permits were given for

entire buildings and were approved in 4 categories: Demolitions after acquisition, New buildings, Zoning

change from residential to commercial and major renovations. This should give a conservative estimate of development since permits, which were not approved for demolition, or construction of new buildings may

also serve as indicators of development intentions.

15 Demolitions of buildings after a land purchase are a clear indicator of intention to develop because of the

high cost of the land. 16 See descriptive statistics of issued permits for 2006 in appendix 1

17

5. Maps and geo-codes: The focus of this paper is on the spatial policing of graffiti.

Therefore, maps based on the aforementioned data were produced using GIS (Geographic

Information Systems) to show the spatial pattern of law enforcement, particularly graffiti

enforcement,17 based on the New York City department of planning Pluto maps. GIS was

also used to standardize the geographic unit used in the data set, using zoning boundaries

from 2008 and census blocks as defined by the 2000 census. For the NYPD data, the

geographic unit is the precinct; for graffiti removal data and building permit data the unit

is community board. The NYHVS data enabled me to match households and persons and

aggregate them by sub-borough. A demonstration of the spatial aggregation (by census

block centroids) of data available in different geographic units is located in Appendix 4.

Dependent variables

The analysis includes two dependent variables. For hypotheses related to quality

of life policing, I use the number of police stops for quality of life offences (loitering,

public lewdness, and vagrancy, vandalism (non-graffiti). I subtract the stops for graffiti

policing18. For hypotheses related to graffiti policing, I use the number of police stops for

graffiti offences, controlled by the number of graffiti removals, which I use as a proxy for

quantifying the number of graffiti in a neighborhood. A simple functional explanation

would have been that the number of graffiti in an area would affect the number of graffiti

enforcement in the neighborhood. However, I found no correlation19 between the number

of graffiti and the number of police stops for graffiti offences. An institutional

explanation for this counter-intuitive result is the lack of administrative coordination.

Two separate low - tiered bureaucratic agents carry out each task. The graffiti removal

project is a subdivision of the Department of Quality of Life in the Community

Assistance Unit in the Mayor’s office. The 77 police precincts of the NYPD carry out

stop-and-frisk enforcement. The practitioners rarely communicate and the organizations

use separate databases to track the graffiti removals and anti-graffiti law enforcement.20

Because of this lack of association between the number of graffiti and the number of anti-

17 The zoning boundaries of precincts, community boards and sub boroughs matched geographically to the

data are based on 2008 geocodes, while the data refers to earlier time periods 2006 and 2007.

18 I subtracted the amount of graffiti policing from the total in order to test the predictors of graffiti

policing and other types of policing 19 No significant correlations were found between the number of graffiti removals and the number of police

stops for graffiti offences using both raw numbers of graffiti removals as well as in reference to

neighborhood population.

18

graffiti police stops, an effective way of measuring anti-graffiti enforcement is by using

the count of stops for graffiti offences when controlling for the number of graffiti and the

population in a neighborhood.

Map 1 Anti-graffiti stops and number of

graffiti21

Independent variables22

I use three sets of independent variables in the analysis:

1. Enforcement variables: general enforcement, measured by the number of stops

(for all offences, excluding quality of life offences), and crime rate, measured by the

number of grand felonies (index crimes: Murder, rape, robbery, aggravated assault and

grand larceny). These are used to control for the level of crime in a neighborhood. Two

other variables are used as controls: the total population in a neighborhood and the

number of graffiti in a neighborhood (using the number of graffiti removals as a proxy.)

2. Demographic variables: Percentage of the population receiving income

assistance. This includes AFDC (TANF), income support, and Medicaid and is used as a

21 Each dot signifies 15 graffiti removals 22 See descriptive statistics for independent variables in appendix 2.

19

proxy for poverty levels in a neighborhood. The percent change in whites is the percent

change in the number of Caucasian individuals in a neighborhood in 1999 and their

number in 2005. Percent changes in professionals includes lawyers, doctors and

managers. Percent changes in other occupations are included, namely occupations related

to finance and real estate and to “creative class” professions, which includes artists,

engineers and architects (based on findings (Florida, 2002) that this group may be an

important gentrifying force.) Percent changes in levels of education are measured based

on categories for some high school, high school graduates, college graduates and

graduate, those with more than a bachelor’s degree.23

3. Real estate variables: percent change of the number of owners living in their

building serves as an indicator of population involvement, since owners are more likely

to have vested interests in property values. It may also indicate corporate gentrification,

because new condominium projects are marketed as live-in properties rather as properties

for investment. Percent change in rent - stabilized apartments indicates the change in the

number of apartments that enjoy the protection of rent control and rent stabilization24.

The percent change in total house value is the change the market value of the house

between 1999 and 2005 as perceived by the surveyor’s assessment. (It is as aggregated

value for all houses in a given neighborhood. Percent change in gross rent per room is

the change in the mean number of money paid per room in a given neighborhood.

4. Land-use variables: percentages of residential, industrial and transportation

land-use in a given neighborhood. Another set of land-use variables is captured through

the number of approved building permits given by the Department of Buildings to private

corporations in 2006, permits for the demolition of existing buildings after the purchase

of a lot, for the construction of new buildings, for major changes to existing buildings,

and for changes in building use from commercial use to residential.25

Robustness tests:

23 A series of independent variables from the NYHVS indicating the percentage change in population

characteristics were tested. Some of these demographic variables were highly correlated and were therefore

excluded from the analysis. These were community related occupations, other occupations, and percentage

of the population with some college education. 24 The decline of rent stabilization occurred in all neighborhoods across the city, to varying degrees. This

decline is due to a fairly simple mechanism: development corporations offer persons living in rent

stabilized housing a lump sum in order to relinquish their contracts to enable the demolition or renovation

of the building by the corporation. 25 All building permit independent variables had high correlations between them. The strongest

associations were predicted by the permits given to private corporations for the demolition of buildings,

and therefore this variable was used and other permit variables excluded to prevent multi – co linearity.

20

While the Poisson model is best fitting to the research design of this study, the

small sample of 55 community boards or neighborhoods in New York City raises

statistical concerns, particularly regarding multi-collinearity. Robustness tests were

conducted using the VIF (variance inflation factor) tests. The variables used in the

analysis were those with a tolerance closer to 1 than to zero and with VIF scores under 3.

The tolerance rate of land-use variables was higher than the population variables in

general. Please see appendix 2 for selected results of VIF scores.

Findings and analysis

We begin the analysis of the findings with the broken windows based hypotheses

1a and 1b, for which the dependent variable is the number of police stops for quality of

life policing, and hypotheses 2a and 2b, for which the dependent variable is the number

of stops for anti – graffiti policing. Hypothesis 1 tests the broken windows theory, the

there will be more policing in area with higher crime rates and general enforcement rates

while hypothesis 2 tests the assertion that enforcement is due to the effect of “policing

poor people in poor places”.

The Broken windows hypothesis posits that the adoption of the broken windows

theory by the NYPD and the use of zero tolerance policing predict that the number of

stops for general enforcement in a neighborhood, will be associated with the number of

police stops for quality of life offences. Table 1 affirms the theory, showing a positive

Table 1. Broken windows/Zero tolerance policing hypothesis :

Comparison of associations between enforcement variables and quality of life and graffiti stopsthe number of NYPD stops

for quality of life offences and graffiti offensesgraffiti offences (poisson regressions)

Model 1 Model 2

quality of life Anti graffiti

stops stops

Coef.

general enforcement 0.0000419 *** -0.0000419 ***

amount of felonies 2006 0.0001073 *** -0.0004256 ***

% receiving income assistance -0.0181263 *** 0.0065174 ***

amount of graffiti 0.0017661 *** 0.0011476 ***

population -1.42E-07 7.95E-06 **

constant 4.839605 2.92E+00

log pseaudolikelihood -1206.1908 -1.21E+03

Chi square (wald) 16.93 17.06

21

association between both the number of general enforcement stops and the number of

grand felonies (murder, robbery, Burglary rape and grand larceny) and the number of

stops for quality of life offences. In other words, the higher the crime rate and general

enforcement rate, the higher the number of stops for quality of life offences. For every

stop in a given neighborhood for all offences (excluding quality of life offences) there

was a .004 percent rise in the number of quality of life stops.26 And for every grand

felony reported in a given neighborhood in 2006 there was a .011 percent rise in the

number of quality of life stops (both are significant at the P< .001). Given that the NYPD

has adopted a zero tolerance policing strategy, this finding resonates well with the

institutional priorities stated by NYPD officials.

Yet hypothesis 2a, predicting that anti-graffiti enforcement will also be positively

associated with the general rates of enforcement and crime, is rejected in the model

presented in table 1. For each additional NYPD stop for any offence in a given

neighborhood, there was a .004 percent decline in stops for graffiti offences, and for each

additional grand felony crime reported in the neighborhood there was .043 percent

decrease in the number of graffiti stops in the neighborhood. This finding indicates that

while quality of life policing follows the pattern expected by the adoption of zero

tolerance policing, neighborhoods where there are higher crimes rates and higher rates of

general policing see a decline in graffiti enforcement. A key point for our analysis is this

finding that shows that anti-graffiti policing is not a subset of quality of life policing.

Contesting the broken windows theory, Fagan and Davies predict that more

policing of quality of life offences will take place in lower income neighborhoods;

however, hypothesis 1b, predicting that the poverty level of the population in a

neighborhood will effect the amount of quality of life policing, is rejected. As model 1

shows, when measuring poverty levels by the percentage of population receiving income

assistance, for each additional percent of the population receiving income support there is

a 1.8 percent decrease in the number of stops for quality of life offences in the

neighborhood.27 In other words, model shows that higher amounts of quality of life

policing exist in neighborhoods where there are lower poverty levels.

26 When interpreting Poisson regression results, a degree change in the independent variable, is associated

with a percent change in the dependent variable. 27 This finding is consistent when using the relative change between 1999 - 2005 in median income per

person in a given neighborhood and controlling for the number of whites in the neighborhood.

22

Yet testing these variables on graffiti enforcement, hypothesis 2b in upheld. As

shown in model 2, an increase in 1 percent of the population receiving income assistance

is associated with a 0.65 percent increase in the number of graffiti stops. There is more

anti-graffiti policing in areas where poverty levels were higher. This finding raises an

important question regarding the relationship between types of police enforcement and

population characteristics. Refuting the broken windows hypothesis further, it leads to

the next set of hypotheses oriented toward determining what units of analysis govern the

policing of graffiti: characteristics of the population or characteristics of the urban space.

Map 2 provides a description of the spatial pattern of general enforcement rates

and poverty levels. It shows an interesting set of relationships: the general rate of

enforcement is significantly associated with the percentage of the population receiving

income assistance. More specifically, for every additional percent of the population

receiving income assistance, there will be a 2 percent rise in the number of stops for all

offences (this result is significant at the p <. 001 levels), and as model 1 on table 1 shows,

while the general enforcement rate has a large and significant effect on the likelihood of

quality of life stops, there is a negative relationship, shown in model 1, between the

percentage of the population receiving income assistance and the number of quality of

life stops.

Crime rates and the general enforcement rate predict the amount of quality of life

law enforcement stops. Yet, refuting the broken windows theory, these variables are

negatively associated with the number of graffiti stops.

23

Map 2 General enforcement rate and percentage of the population receiving

income assistance

Map 3. Spatial distribution of quality of life policing by sub borough

24

Quality of life policing hotspots in NYC

Manhattan and Staten Island are boroughs with the highest number of stop-and-

frisk activity for quality of life offences. Manhattan is heavily policed for quality of life

offences: financial district, Greenwich Village, Chinatown, Lower East Side, city hall and

the two bridges encounter the heaviest amount of policing. Yet only Chinatown and the

Lower East Side have both very high poverty levels and high general enforcement rates.

In Brooklyn Bedford Stuyvesant and downtown Brooklyn are the most heavily

policed for quality of life offences, and in Queens Elmhurst and Corona have the heaviest

quality of life policing. These neighborhoods have seen sharp increases in percent of the

population receiving income assistance in the last decade, and they border on the wealthy

and privately policed neighborhoods of Forest Hills and Rego park.

Tables 2 and 3 below show the findings from tests of the effects of two types of

gentrification on the amount of law enforcement. Hypotheses 3a and 3b test the effects of

percentage changes in various population characteristics on the number of anti-graffiti

stops and quality of life stops, respectively. These hypotheses assert that the social

mechanisms influencing allocation of policing resources are related to the power of the

neighborhood population and predict that the wealthier and socially mobile the

25

population, or the more an area is gentrifying, there will be a higher number of stops for

quality of life offences. Hypotheses 3c and 3d test the effects of land-use variables and

the number of permits given to corporations for private development and construction on

the number of police stops for anti-graffiti and quality of life policing, respectively.

These hypotheses posit that the mechanisms influencing allocation of policing resources

are related to capital and real estate interests of development companies. They predict

that the more permits for development granted to corporations by the city in a

neighborhood, the higher the number of anti-graffiti and quality of life police stops,

respectively.

These two sets of hypotheses define the temporal effect of gentrification

differently. The “gentrification through population” hypotheses predict that the allocation

of policing resources is influenced after the population has moved in and changed the

neighborhood, while the “gentrification through corporate development” hypotheses

predict that the effect on policing occurs prior to the construction and re-population of a

neighborhood, at the time when developers express the intention to gentrify a

neighborhood.

Models 3 and 4 test the relationships between demographic and occupational population

Characteristics and the amount of quality of life and anti-graffiti enforcement. When

controlling for occupations, the association between poverty levels and quality of life

policing remains consistent with the finding in table 1. The larger the population

receiving income assistance, policing of quality of life will decline. However, in model 4,

poverty levels are insignificant for anti-graffiti policing. Growth of population with

professional occupations does not provide consistent predictors for quality of life

policing. However, the percentage change in the number of professionals (doctors,

lawyers and top management) showed a consistently positive relationship with anti-

graffiti police stops. In model 4, 1 % change in the number of professionals in the

neighborhood will lead to an 18.5% rise in police stops for graffiti offences. In model 6,

when controlling for percent changes in levels of education and land-use percentages, the

number decreases to a 9% rise in anti-graffiti police stops. This compares to quality of

life stops, which are negatively associated with the percentage change of the number of

professionals in a neighborhood. One of the explanations for the negative association

with quality of life stops may be found in the history of quality of life policing. Quality of

life is traditionally policed in commercial areas; public places that attract loiterers,

26

solicitors, vagrants and persons with a higher likelihood of committing public annoyance

offences. Prestigious professionals are less likely to inhabit these commercial areas.

Model 4 shows a strong association between graffiti policing and the percent

change in the number of people belonging to “the creative class,” (Florida, 2007) which

includes artists, students, and engineers working for high tech industries. The effect goes

down slightly when controlling for education and land-use.

Models 5 and 6 test the effects of education levels of neighborhood population on

the amount of law enforcement for quality of life and graffiti offences, but these do not

provide a significant contribution for the analysis.

Comparing models 7 and 8, which use the full range of population variables and

land-use variables, we find a consistency with the finding in table 1.The poverty level in

a neighborhood is negatively associated with quality of life stops. For every percent of

population receiving income assistance, there will be a decline of 1.6 % of stops for

quality of life, significant at the p< .001 levels, and a positive association with graffiti

enforcement. For every additional percent receiving income assistance there will be an

increase of 2.8% in graffiti stops.

In models 7 and 8, we see that the percentage of land-used in a given

neighborhood for transportation is positively associated with both quality of life stops and

anti-graffiti stops. A rise in one percent land-used for transportation purposes is

associated with a 2.6% rise in the number of stops for quality of life and with stops for

graffiti offences (a rise of 4.5%). Land-use for transportation includes train stations, ports

and highways. The literature on quality of life policing posits that around train and bus

stations there will be a rise in quality of life enforcement, and highways, ports and

subways invite graffiti enforcement. Notwithstanding, this is a strong finding regarding

quality of life policing because the numbers reflected here do not include the numerous

stops for quality of life offences committed inside subway stations, since these are

governed by the metro transit authority and not by the NYPD. Following a similar

pattern, the percentage of land-used for industrial purposes will be negatively associated

with quality of life stops (A decrease of 3.4%, significant at the P< .001 level), because

industrial areas have little or no commercial activity, and positively associated with anti-

graffiti enforcement (3.8%, significant at the p<. 001 level). Land-use variables are

further explored in table 3, which focuses on comparisons between land-use, home-

ownership characteristics, and real estate parameters. Population variables do not show

distinct and consistent associations with anti-graffiti policing, and while we cannot reject

27

hypothesis 3a and 3b, we cannot conclude that there are strong associations between

population characteristics and graffiti enforcement

Table 2. Gentrification by population hypothesis: selected results of associations between

Population charachteristics and quality of life/ anti graffiti enforcement (outcome: number of stops)

model 3 model 4 model 5 model 6 model 7 model 8

Quality of Anti graffiti Quality of Anti graffiti Quality of Anti graffiti

life stops stops life stops stops life stops stops

% receiving income assistance -0.0192411 *** -0.003676 -0.021241 *** -0.0068985 *** -0.0161587 *** 2.81E-02 ***

% change in whites -0.0122034 *** -0.070035 *** -0.02055 -0.0652818 *** -0.0080797 *** -0.05708 ***

Occupations:

% change in professional -0.0221503 ** 0.16932 *** -0.0597379 *** 0.092042 ***

% change in finance -0.0234881 ** -0.120939 *** -0.1009779 *** 0.1743048 ***

% change in creative class 0.0941954 *** 0.061513 *** -0.0054674 0.0461662

% change in Comm. Occ 0.0228755 ** -0.036422 0.0455547 ** -0.047236

Education:

% some high school -0.036119 *** -0.0195687 -0.0171818 ** -0.0310898 **

% highschool 0.009197 ** 0.0781208 *** 0.009658 ** 0.010512

% change some college 0.004118 *** 0.0260879 0.0162459 ** -0.0492689 **

% change college -0.038969 0.0131228 -0.0060274 -0.0716816 ***

% change graduate -0.007714 -1.59E-03 0.0435669 *** -0.099501 ***

-0.009306 *** -0.0008451

-0.0347769 *** 0.0377291 ***

0.0266032 *** 0.0449292 ***

demolition permits 2006 0.006005 *** 0.0123621 ***

amount of felonies 2006 0.0000767 *** -0.000285 *** 0.000109 *** -0.0001937 *** 0.000125 *** 0.0123621 ***

general enforcement 0.000047 *** -6.16E-06 4.04E-05 *** -2.43E-05 *** 0.0000493 *** -0.0003296 **

amount of graffiti 0.0017262 *** 0.003285 *** 0.001964 *** 0.0026771 *** 0.0017622 *** 0.0014836 ***

population 9.27E-07 ** 2.978163 *** 9.54E-08 3.25E-06 *** -1.14E-06 ** 7.40E-06 ***

constant 4.782481 2.978163 5.010141 3.404161 5.242179 1.09955

log pseudolikelihood 953.1 -823.43 -899.22 -792.87 -669.05 -700.21

chi aquare (wald) 158.98 141.98 237.82 89.86 372.92 182.71

percent residential land use

% industrial land use

% transportation land use

28

Real estate and housing variables

Models 9 – 16 test hypotheses 3c and 3d, the association between real estate

variables and quality of life and graffiti enforcement. Corporate gentrification is

measured by the number of permits issued to corporations in 2006, and housing

variables include measurements of percent change in the number of owner – occupiers

living in the building they own, the change in the number of rent stabilized units in a

neighborhood, the change in the median house value, and the change in rent paid per

room. Model 10 tests and map 4 describes the relationship between the numbers of

permits issued to private corporations for demolitions of buildings in 2006. For every

new demolition permit in an area there will be a 1.3 % increase in stops for graffiti

offences. This is an extremely significant association, since the mean for demolition

permits is 33. This variable, an indicator of the intent to gentrify, serves as an indicator

for gentrification that is yet to take place, because of the bureaucratic process that takes

years to obtain the permit and the lag in time between the demolition, building

development and the actual change in population composition.

Table 3. Gentrification hypothesis - real estate and land use: Selected results (poisson regression)

association between Land use, home ownership and corporate development charachteristics and quality of life/ graffiti enforcement

model 9 model 10 model 11 model 12 model 13 model 14 model 15 model 16

quality of life Anti graffiti Quality of life Anti graffiti quality of life Anti graffiti Quality of life Anti grafffiti

stops stops stops stops stops stops stops stop

Demolition permits 0.0035514 0.0132662 *** 0.00273665 0.011266 ***

% residential land use -0.0106224 *** 0.014978 *** -0.008464 *** 0.0135813 *** -0.0096046 *** 0.0171103 ***

% industrial land use -0.0236616 *** 0.013327 *** -0.0254739 *** 0.0333006 ***

% transporation land use 0.0293548 *** 0.063038 *** 0.0148933 *** 0.0661548 *** 0.0229463 *** 0.0589206 ***

% change in renstabalized units 0.0052998 ** 0.0200769 ***

% change owners living in unit -0.008857 *** 0.0268103 *** -2.18E-03 0.0312058

% change in total house value -0.0005591 0.0028157 ***

% change in rent per room 0.0041353 *** -0.013422 ***

% receiving income assistance -0.016131 *** 0.0039665 -0.016697 *** 0.0083213 ***

General enforcement 0.0000381 *** -3.21E-05 0.0000314 *** -1.53E-05 ** 0.0000446 *** 0.0661548 ***

Amount of felonies 2006 1.14E-04 *** -0.000212 *** 0.0000145 -0.000323 *** 0.0000147 -0.000316 *** 0.0000812 *** -0.000441 ***

amount of graffiti 0.00177 *** 0.0016124 *** 1.29E-03 *** 0.001264 *** 0.0013958 *** 0.0014165 *** 0.0022091 *** 0.0009002 **

population -5.38E-07 3.99E-06 *** 2.28E-06 *** 9.07E-06 *** 1.51E-06 *** 0.0000104 *** 1.44E-06 *** 0.0000127 ***

constant 4.81469 2.967367 4.816094 1.914576 5.189029 1.561533 4.894636 5.189029

log pseaudolikelihood -1021.95 -1117.13 -971.56 -1151.55 -910.49 -1130.12 -1125.95 -1051.97

chi square (wald) 173.15 24.45 110.99 28.8 151.93 38.42 98.58 49.17

sources: NYPD stop and frisk survey 1999, NYHVS 1999& 2005, NYC government dept. of planning * p<0.05 **p<0.01 *** p<0.001N = 55

ResidentialDevelopment Land use Housing Values

29

Hypothesis 3d is confirmed, and we can assert that areas that are residential, have

a larger proportion of land-use for transportation, and have been issued more permits for

demolitions will be hotspots of graffiti policing. In the models tested, demolition

permits28 are consistently significant.

Adding Housing variable as controls, models 12 and 14 show that the number of

owners in the building is positively associated with higher stops for graffiti offences. For

every percent change in the number of owner occupiers in a neighborhood there will be

2.1% more stops for graffiti policing, significant at the p <. 001 level. The number of

owner-occupiers is negatively associated with stops for quality of life offences, even

when controlling for levels of enforcement and the poverty levels. This can be explained

by the different nature of quality of life policing and graffiti policing. Since graffiti is

directly linked to property values, the presence of owner occupiers, who have a vested

interest in keeping property values has a positive effect of the policing of graffiti.29

Quality of life offences are policed less frequently in residential areas and more often in

areas that have commercial public spaces. This finding resonates well with the idea that

it is gentrification by population that drives graffiti law enforcement.

Map 4 below demonstrates demolition permits as powerful predictors of graffiti

enforcement. As the map shows, the higher the ratio of graffiti stop-and-frisk police

activity to the number of graffiti in the area (indicated by darker areas), the higher the

number of demolition permits issued by the city of New York in 2006 (indicated by large

red circles). This relationship is relevant for most of the graffiti enforcement hotspots,

which I will describe in the conclusion. An interesting exception to the phenomenon is

the community boards of Williamsburg and Green Point, which are undergoing vast

corporate-led gentrification. A possible explanation for this exception may lie in the trend

to view graffiti as an art form, and the fact that many of the graffiti murals that line the

gentrified Bedford Avenue in Williamsburg are commissioned work by local business

owners and advertisers.

28 As shown in the appendix, there is a strong correlation between the various permit variables. However,

the demolition variable captures the effect of all types of permits and therefore is used here as an indicator

of corporate gentrification. 29 I thank Attorney Michael Brovner from the Queens District attorney’s office, for pointing out the

copious involvement of owner-occupiers in the prosecution of anti-graffiti case.

30

Map 4: Graffiti enforcement rate and the number of demolition permits

Graffiti enforcement hotspots in New York City

Brooklyn, Queens and Staten Island are the boroughs with the highest ratio of

graffiti policing to the number of graffiti (the number of removals used as a proxy for the

number of graffiti), depicted above in map 4. Exploring this map, we can see the

association between the rate of graffiti enforcement and the number of demolition permits

issued by the Department of City Planning to private corporations. In Queens, the

neighborhood hotspots are Flushing, Jamaica, Jamaica Hills and Kew Gardens. Within

the last decade, peaking in 2007, these first three neighborhoods have become diversified

and partly gentrified. New developments of condominiums are erected beside

government subsidized “section 8” housing projects. This diversification of the

neighborhood, which a crucial stage in the process of gentrification, can mean a mix of

persons who write graffiti and those who desire to enforce its removal. Kew gardens

demands a different explanation, since it does not have section 8 housing. A possible

31

explanation for the focus on graffiti enforcement is that it is home to the Borough Hall

and Queens County district attorney’s office30.

In Brooklyn, Bensonhurst, and Sheepshead Bay police precincts 61 and 62 have

the highest ratio of NYPD stops for graffiti to the amount of graffiti in the entire city.

Bensonhurst has a very low level of quality of life policing, and Sheepshead Bay has a

moderate level of quality of life policing. The general enforcement rates for both areas

are very low, and Bensonhurst has a fairly high percentage of population (38.9) receiving

income assistance. BensonHurst saw a rise of 400% in building permits between the

years 2000 and 2003 and had been steadily gentrifying until 2007. Sheepshead Bay has

30 percent of its population receiving income assistance and King’s Highway, a major

traffic artery for Brooklyn running through it, where graffiti is regularly made.

Sheepshead Bay is also a center of residential gentrification, where during the last decade

the number of building permits for apartment buildings rose from eight permits in 1997 to

one hundred and fifty building permits for apartment buildings in the area in 2006.

Staten Island is the borough where graffiti is a major source of political conflict

and civic action, where over 8 community groups engage in anti-graffiti campaigning and

removal projects. Sociologist Gregory Snyder claims that in Staten Island graffiti is made

by white, middle class teenagers, as opposed to Queens graffiti which is mostly done by

Latinos and graffiti in Brooklyn, mostly done by black young people (Snyder, 2006).

South Shore has the highest rate of graffiti enforcement, and little corporate demolitions.

Discussion and conclusion: the political economy of anti-graffiti law enforcement

As the findings show, graffiti law enforcement is a strange phenomenon. Contrary

to official classification, and sociological scholarship, anti-graffiti enforcement is not a

subset of quality of life enforcement. Graffiti is viewed as one of the main indicators of

neighborhood disorder by both scholars and administrative officials whom have adopted

the broken windows and zero tolerance policing, yet in practice, predictions regarding

graffiti enforcement were refuted in this study. While zero tolerance policing, the policy

instigated by the broken windows theory, does predict the level of enforcement of quality

of life offences, based on crime rates and general enforcement rates (since the theory

posits that all crimes are tackled similarly, large or small), it does not predict graffiti

policing.

30 I thank Richard Lachmann for this insight.

32

Turning to the set of hypotheses on the political economy of law enforcement,

testing the neighborhood characteristics of the population and real estate values, a more

complex set of relationships between population and graffiti enforcement is revealed.

Molotch's concept of land use interests as the driving force of politics in the metropolis is

upheld in the analysis. The variables with most explanatory power were those of land-use

and those defining the relationship of the population to the property. The owner-

occupiers have the strongest predicting effect on the amount of graffiti policing, second

only to the variable measuring amount of permits to demolish buildings given to

corporations in 2006. This latter variable is a strong indicator not of gentrification, but

also of the corporate intention to gentrify. While in this paper the mechanism remains

clandestine, this finding has significance on both theoretical and empirical levels. On the

theoretical level, for students of administrative discretion and the political influences on

it, the finding that the unit of analysis that needs to be tested is the land-use of the space

that is being policed and not the population points to the importance of collaboration

between sociologists and geographers researching city governance in general and

policing in particular. From the standpoint of public policy, the relationship between

corporate gentrification and graffiti policing is a disturbing one that not only confirms the

idea of the city as a growth machine but also reiterates the selectivity of law enforcement

and its conflation with the political interests of strong economic actors. The maps

showing the uneven distribution of policing resources and it’s relationship to corporate

development power, are a challenge to those interested in democratic city governance,

accountable municipalities and participating citizens, whether they appreciate graffiti as

an art or see it as vandalism.

33

Appendix 1

The following correlations table shows that the ratio of graffiti enforcement stops

to the amount of graffiti in a neighborhood is highly correlated with all types of permits

issued for the demolition, construction or zoning changes from commercial to residential

real estate of entire buildings in 2006.

Correlations between graffiti enforcement rates and building permits 2006

Graffiti stops

permits for

new buildings

permits for

demolitions

Permits for

zoning changes

Ratio of

Graffiti stops to

amount of

Graffiti

# of Graffiti stops 0.244 .397** 0.089 .690**

permits for New Buildings 0.244 1 .637** .495** .469**

Permits for Demolitions .397** .637** 1 .456** .505**

Permits for zoning changes 0.089 .495** .456** 1 .324*

Ratio of graffiti stops to amount of

graffiti.690** .469** .505** .324* 1

N =55 ** P< .01

34

Appendix 2: Descriptive statistics, law enforcement, housing variables

Minimum Maximum Mean Std. Deviation

# of police stops for all offences

2006

1995 29631 9195.6 6363.38661

# of stops for Quality of life

offences (excluding graffiti)

59 660 189.5273 123.45487

# of graffiti removals 2006 (proxy

for estimation of graffiti)

10 430 121.6 104.159

# of stops for graffiti offences 0 306 39.8364 53.48096

ratio of graffiti police stops to

graffiti removals

0 3.5 0.5893 0.84864

ratio of total stops to population 0.01 0.31 0.0661 0.05526

N = 55 (community boards)

Descriptive statistics of selected law enforcement Variables

Min. Max. Mean

Std.

Deviation

% population receiving income assistance * 4.9 60.3 32.2018 13.71218

percentage of INDUSTRIAL land use 0 34.4 4.5727 6.66551

percentage of RESIDENTIAL land use 5 75.9 47.34 17.21211

percentage of TRANSPORATATION land use 0.4 29.1 4.7564 5.97912

# of stops for quality of life offences (excluding graffiti) 59 660 189.5273 123.45487

Amount of graffiti removals 10 430 121.6 104.159

# if whites in the neighboorhood in 1999 0 1052 260.82 230.862

% change in creative class occupations + -0.03 0.06 0.0058 0.01765

% change in median rent per room+ 0.14 0.62 0.3577 0.11482

% change # of owner - occupiers in the building + -0.24 0.09 0.001 0.06393

% change # of rent- stabalized units + -0.17 0.08 -0.0232 0.05751

% change in house value + -0.67 6.59 1.3665 1.05429

% change in whites + -0.26 0.15 -0.0133 0.08357

T percent change in numbers of variables in a subborough, from 1999 to 2005, NYHVS.

Descriptive statistics: Population, Land use and housing variables

* Income assistance includes AFDC (TANF), homerelief, supplemental security income, medicaid. Summary statistics from the NYC

dept. of city planning.

35

Appendix 3

Prevalence of graffiti: Measuring crime or measuring enforcement?

Crime measurement has been the subject of scholarly controversy for sociologists and criminologists for decades. Social disorganization theory in criminology was prevalent in emphasizing the geographical distribution of crime and the structural characteristics of neighborhoods related to this distribution (Warner & Pierce, 1993).

In the 1970’s it was criticized for its reliance on official measures of crime, since it was difficult to discern if the measurement was of crime or crime control, the amount of offences or the amount of enforcement. Studies conducted failed to arrive at adequate conclusions about the relationship between neighborhood characteristics and crime rates, because areas with higher levels of policing registered as higher crime rate area. In the 1980’s criminology’s measure for crime rate became victimization rates, as measures that were independent of practice biases of law enforcement agents and organizations (Sampson, 1983, 1985). In the 1990’s in order to reduce underreporting, scholars used calls to the police (calls for service) as a measure of crime.

Studies using calls for service as a measure for crime have been conducted to measure crime at the address, neighborhood and city level. These spatial studies mapped calls to 911 in Minneapolis (Sherman et. al., 1989), Boston (Warner & Pierce, 1993) and in multiple American cities (Bursik & Grasmick, 1993). In the field of graffiti enforcement in NYC, one of the possible predictors of law enforcement are calls made to 311 for requests for removal of graffiti that are directed at the Community Assistance Unit in the Mayor’s office, which offers free graffiti removal services31. While serious doubts have been cast on the measurement of crime through calls for service (Klinger & Bridges, 1997), few have questions the relevance of the measure as an indicator of enforcement. I decided not to measure calls to 311 about graffiti based on interviews I conducted with members of the graffiti removal project in the community assistance unit. They thought that 311 calls would measure the level of nuisance and participation of the community, but not the prevalence of graffiti. They also worried about outliers, since some graffiti pieces would instigate multiple calls. I finally decided on graffiti removals as a proxy for the amount of graffiti in an area.

31 Calls to 911 would be an ineffective measure due to the fact that since 2004, municipal anti-graffiti

campaigns were directed at encouraging callers about “graffiti vandalism” to call 311, at times with the

prospect of a $500 reward to information that would lead to the arrest of graffiti offenders.

Variance inflation factor (VIF) and tolerance scores

for selected variables (models 1, 2, 12)

Variable VIF Tolerance

% receiving income assistance 1.62 0.61

General enforcment rate 1.8 0.55

Number of stops for quality of life offences 2.19 0.45

number of graffiti in 2006 1.4 0.71

number of felonies in 2006 1.6 0.62

number of demolition permits 2006 1.35 0.74

36

Appendix 4: Using GIS to match data in different geographical units

Sources: maps of precincts, community boards and sub boroughs, NYC dept. of city

planning, Zoning 2005.

The Map above shows the method I used in GIS in order to match different geographical units in

Lower Manhattan. Precinct borders are in red, Community boards drawn in blue and sub borough borders

in purple. Using the centroids of census blocks, we chose what census blocks to include in the aggregated

geographic area, when the zoning boundaries did not match.

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