Quality-of-life policing Do offenders get the message?

Abstract

In the 1990s, the New York City Police Department expanded its focus on reducing behaviors that detract from the overall quality of life (QOL) in the city. Many have credited this effort for the decline in the city’s overall crime rate. They often cite the fixing broken windows argument, which maintains that reducing disorder sets off a chain of events leading to less crime. However, systematic research has not yet documented this chain of events. Looks at one of the first linkages, whether QOL policing sends a message to offenders not to engage in disorderly behaviors in public locales. The project interviewed 539 New York City arrestees in 1999. Almost all of them were aware that police were targeting various disorderly behaviors. Among those that engaged in disorderly behaviors, about half reported that they had stopped or cut back in the past six months. They reported a police presence was the most important factor behind their behavioral changes. These findings support the idea that QOL policing has a deterrent effect.

Introduction

In the 1990s, the New York City Police Department (NYPD) sought to send a message that it would not tolerate disorderly activities that detract from the quality of life (QOL) in the city[1. In the past, police officers often ignored many disorderly activities. If persistent or particularly annoying, an officer might have asked violators to move on, asked them to desist, or at most imposed a small fine. As part of QOL policing, the NYPD deployed patrols with a mandate to arrest persons committing disorderly offenses in the streets, parks, stores and other public locations (Bratton and Knobler, 1998; Kelling and Coles, 1996). The targeted QOL behaviors included aggressive panhandling, graffiti writing, sleeping on public benches, farebeating[2] and a wide range of other misdemeanors and violations (for one listing see McArdle and Erzen (2001, pp. 35-44)). The NYPD would then detain these alleged violators for about 24 hours pending arraignment. At arraignment, a judge would typically accept a guilty plea and impose a fine, a sentence to community service, or a sentence for time already served. In this manner, the NYPD imposed a swift and sure penalty of a day in jail for relatively minor disorderly behaviors. To help spread its message, the NYPD also ran public education campaigns.

The fixing broken windows perspective holds that reducing disorderly behavior can ultimately reduce crime (Kelling and Coles, 1996). During the 1990s, crime in New York City (NYC) plummeted, especially violent crime. Many have credited QOL policing as central to this transformation (Bratton and Knobler, 1998; Guiliani and Kurson, 2002; Karman, 2000; Kelling and Sousa, 2001; Maple and Mitchell, 1999; Silverman, 1999). However, some scholars contend that other historical events like the decline of the crack epidemic were the primary reasons for the crime drop (Blumstein and Wallman, 2000; Greene, 1999). Others have raised concern that the NYPD’s practices were too harsh (e.g. Amnesty International, 1996; Harcourt, 2001; McArdle and Erzen, 2001; Spitzer, 1999; but see Golub et al., 2001; NYPD, 1999). In a thoughtful review, Eck and Maguire (2000) concluded that policing innovations clearly contributed to the crime drop but that it was not yet possible to isolate the magnitude of the effect.

Ultimately, we would like to know whether QOL policing is effective, how effective, whether it would work if refined, and whether it would work in other locations at other times. The remainder of this introduction reviews the fixing broken windows perspective and the related empirical research. This paper presents new findings that contribute to that literature. The Arrestee Drug Abuse Monitoring (ADAM) Policing Study (hereafter, the Policing Study) asked NYC arrestees about their awareness of and response to QOL policing. These data indicate whether they got the message and whether they did anything about it.

This analysis represents an extremely limited impact assessment of QOL policing. The project could have derived more definitive conclusions if it also collected data before implementation of QOL policing. A before and after analysis would have measured how much QOL policing changed attitudes and behaviors. In a similar vein, the study lacked a control group, arrestees from a similar location not subjected to QOL policing. The use of arrestees further limits the study. The Policing Study sought to identify whether persons changed their behavior over time. However, the police would have been much less likely to arrests persons that had stopped or reduced disorderly and criminal behaviors. Lastly, the project studied only one city. Other locations’ experiences with QOL policing may differ depending on how they implement the program and the nature of their crime problems.

Despite these limitations, this analysis does provide new insight into the micro-processes by which QOL policing is reputed to work. Perhaps even more importantly, the analysis illustrates the potential for expanded use of the ADAM program for monitoring, evaluating, revising, and justifying the exportation of policing innovations. It would be straightforward to design similar analyses using ADAM to monitor and evaluate future policing innovations at modest expense.

Fixing broken windows

The fixing broken windows line of reasoning contends that physical decay (such as broken windows) and disorderly behaviors can start a downward spiral of events that cause a neighborhood’s decline (Kelling and Coles, 1996; Skogan, 1990; Wilson and Kelling, 1982). The argument proceeds as follows. Disorderly activities offend a community’s sensibilities, create a broad sense of disorder, and instill a fear of crime. This leads law-abiding residents and visitors to withdraw from public spaces. The lack of ordinary people going about their activities signals that deviant behavior is tolerated in public locations. Then under the cover of disorder and away from watchful eyes, criminals easily commit more serious offenses. As a neighborhood deteriorates in this manner, disorderly behavior increases, crime increases and the quality of life in the community declines even further. The fixing broken windows perspective contends that reducing disorder in public locations constitutes a critical early effort to control crime, restore neighborhoods, and facilitate economic revitalization (Wilson and Kelling, 1982; Kelling and Coles, 1996).

Prior research has used a variety of methodologies to study this proposition with mixed results. Several field experiments examined the extent to which expanded law enforcement, including QOL policing, reduced crime and disorder. Braga et al. (1999) found significantly larger reductions in both disorder and crime in the Jersey City high crime areas that received increased attention. On the other hand, Katz et al. (2001) found no substantial changes in disorderly conduct or crime in Chandler, Arizona, following a QOL policing initiative. Similarly, Novak et al. (1999) found that increased patrols for disorderly behavior in a section of a larger Midwestern industrial city did not reduce robbery or burglary rates. They did not measure changes in disorder. Novak et al. (1999) speculated that the study might have produced no measurable change because of several features of the intervention: its short duration, its limited size and scope, the limited visibility of police officers, and a lack of media coverage.

Other research has examined the relationship between disorder and crime. Skogan (1990) analyzed survey data from residents of 40 neighborhoods from six cities across the USA. He found that robbery victimization was higher in neighborhoods characterized by disorder, consistent with his thesis that disorder leads to crime. Harcourt (2001) disagreed with Skogan’s conclusions, raised numerous methodological concerns, and reanalyzed Skogan’s data. Harcourt (2001) observed that the highest levels of both robbery and disorder occurred in Newark. He reanalyzed the data from locations other than Newark and found no significant association between disorder and robbery. Harcourt also found no correlation between disorder and several other crime types measured by the study including burglary, assault, rape and purse snatching/pickpocketing. In another study, Sampson and Raudenbush (1999) set out to measure the relationship between physical disorder and crime by comparing videotapes of Chicago’s neighborhoods with crime rates. They found that the bivariate correlation between crime and disorder disappeared after controlling for other factors, especially concentrated poverty and collective efficacy (a neighborhood-level measure of cohesion, informal social control, and optimism). They suggested that the causes of crime are much deeper than disorder.

Harcourt (2001, p. 120) argued that, “[T]he policy analyst must do more than conduct statistical analyses of the relationship between [QOL policing and crime rates].” He argued that research must focus on understanding the process by which QOL policing might effect change and stated, “This kind of work, however, has not yet been done.” (Harcourt, 2001, p. 121). This paper seeks partially to address this gap in the empirical research. It examines whether NYC arrestees got the message that police were targeting QOL violations and how they responded.

Methods

The Policing Study fielded a supplemental survey in conjunction with the ADAM program in NYC (see Johnson et al., 2001, for further details). This section describes the sampling procedure, the characteristics of the sample, and the questions pertaining to QOL policing.

Sampling

Since 1987, ADAM (formerly the Drug Use Forecasting (DUF) program) has interviewed arrestees about their drug use and obtained urine samples in numerous police booking facilities across the USA. Participation in the ADAM survey is voluntary. Federal regulations control access to the ADAM data to maintain confidentiality and limit use to scientific research only. Starting in 1999, the ADAM program instituted procedures designed to obtain a representative sample of all arrestees (NIJ, 2000). At most sites in 1999, more than 80 percent of arrestees approached agreed to participate (NIJ, 2000). To facilitate comparisons across gender, the ADAM program purposefully oversamples females, who usually account for about 15 percent of NYC arrestees. For this analysis, we employed simple weights so that females would constitute 15 percent of the weighted sample.

During the third and fourth quarters of 1999, the Policing Study asked a subsample of ADAM-NYC adult arrestees to complete a supplemental interview. The project also asked for written informed consent to obtain respondents’ New York State (NYS) criminal histories. As an incentive, the project promised respondents $15 after their release. Nearly everyone (97 percent) approached agreed to participate, yielding an initial 470 respondents. To obtain a larger sample, the project collected data for an additional week after the official ADAM data collection period. This increased the sample to 892 arrestees.

We limited this analysis to the 539 arrestees who had a prior arrest record and disclosed it. We excluded 189 arrestees who had no official record of arrest and 164 who did not disclose a prior arrest record. A preliminary study suggested who arrestees who did not disclose having a prior arrest generally did not provide other information about their criminal history (Golub et al., 2002). They were also less likely to disclose recent marijuana use. We were concerned that their reports about committing disorderly behaviors might be inaccurate, too.

Sample demographics

Table I presents the characteristics of the sample analyzed. The average age of the arrestees was 33 years. The sample was predominately black (65 percent) and Hispanic (24 percent); only a modest percentage was white (11 percent). The sample included more arrestees from Manhattan (44 percent) than other NYC boroughs (3-19 percent). Arrest charges were broadly distributed between drug (34 percent) index (27 percent)[3] and other offenses (39 percent) that included mostly less serious charges like trespassing, farebeating, forgery, simple assault and disturbing the peace.

Table I.

Characteristics of the ADAM-New York City policing subsample analyzed

Demographics
Average age	33
Black	65%
Hispanic	24%
White	11%
Source
Manhattan	44%
Bronx	17%
Brooklyn	19%
Queens	17%
Staten Island	3%
ADAM sample	56%
Supplemental sample	44%
Current charge
Drug possession/sales	34%
Index offense	27%
Other	39%
Education
No HS degree	37%
In HS	3%
HS degree	44%
Attended college	16%
Marital status
Single	59%
Separated/widowed/divorced	11%
Lives with someone	16%
Married	13%
Primary income source
Full-time job	27%
Part-time job	12%
Other legal	16%
No income	3%
Welfare	20%
Illegal activities	22%
NYS criminal history
Average number of lifetime arrests	13
Arrest past six months	57%
Drug arrest	83%
Index arrest	74%
Served time in jail	72%
Served time in prison	33%
Recent drug use (based on urinalysis)
Cocaine/crack	52%
Heroin	16%
Marijuana	46%
Any of the tliree	83%

Notes: n = 539 Estimates weighted to control for overrepresentation of females

These NYC’s arrestees appeared to exist on society’s margins as evinced by their low ratings on several measures of mainstream attainment, their considerable criminal justice histories, and their use of illicit drugs. Many respondents (37 percent) had not completed high school, exceedingly few (13 percent) were currently married, and just over a quarter (27 percent) had a full-time job. On average, respondents’ NYS criminal histories were substantial (13 prior arrests)[4]. Most of the arrestees had a previous arrest for a drug offense (83 percent), had a previous arrest for an index offense (74 percent), and had been to jail (72 percent) but not prison (only 33 percent had). Urine tests indicated that nearly all of them (83 percent) had recently used an illicit drug, especially cocaine and marijuana.

Questions on QOL offending

The Policing Study questionnaire included a series of questions about various QOL behaviors. The list was based on the QOL policing literature and developed in consultation with NYPD staff. It included: behaviors the NYPD had been explicitly targeting as part of QOL policing (e.g. farebeating, smoking marijuana in public); disorderly behaviors the NYPD had not been targeting (e.g. littering); traffic offenses; and several behaviors that do not violate any statute but that arrestees might feel were the subject of enforcement efforts (e.g. hanging out in the street). This study did not analyze offenses by minors regarding alcohol, tobacco products, and truancy because too few Policing Study respondents were under the age of 18.

The project asked respondents up to four questions pertaining to each behavior: whether they perceived that police were targeting the behavior for warnings, tickets or arrests; whether they had engaged in the behavior during the past 12 months; if yes whether they had reduced or stopped their involvement in the behavior during the previous six months; and if yes the reason for the reduction. The project allowed respondents to choose from several possible reasons for any reduction:

• police presence (hearing or seeing that the police target the behavior);

• contact with police or courts regarding the behavior (such as a warning, ticket, arrest, jail, probation/parole);

• drug treatment or other social services;

• job duties or employment;

• family or a relationship; and

• other.

Pilot testing revealed that virtually no arrestees reported increased involvement in any of these QOL behaviors. Accordingly, the final questionnaire asked about reductions but not increases.

Results

This section examines the respondents’ participation in QOL behaviors, awareness of NYPD’s QOL policing efforts, recent reductions in QOL behaviors and reasons for reductions. For ease of presentation, we divided the various QOL behaviors into five functional categories: substance use in public, disorderly public displays, illegal street businesses, unsanitary actions, and traffic violations (see Tables II-IV).

Table II.

Prevalence of QOL behaviors among NYC arrestees

Behavior	Percent committed in past year
Substance use
Smoking marijuana in public	36
Buying/carrying marijuana in public	34
Selling marijuana in public	16
Drinking alcohol in public	35
Smoking in non-smoking areas	21
Public display
Hanging out in street	47
Engaging in disorderly conduct	28
Making loud noises in public	16
Loitering w/o cause	25
Belonging to a gang	4
Trespassing	28
Failing to cooperate with police	13
Street business
Farebeating	44
Aggressive panhandling	7
Squeegee work	2
Vending w/o license	9
Selling counterfeit video/tapes	4
Buying/selling alcohol to minors	3
Buying/stilling cigarettes to minors	4
Gambling/numbers in public	13
Prostitution in public	5
Sanitation
Urinating in public	31
Writing graffiti	4
Littering	15
Failing to pick up after your dog	3
Failing to recycle garbage	5
Traffic
Driving while intoxicated	7
Driving w/o a license/registration	21
Ignoring red lights and stop signs	8
Speeding	11
Drag racing	3
Talking on cell phone while driving	4
Violating traffic laws while bicycling	9
Jaywalking	22

Note: Estimates weighted to control for overrepresentation of females

Table IV.

Impact of QOL policing on NYC arrestees

			Stopped/cut back on behaviora Reason (%)b
Behavior	%	A	B	C	D	E	F
Substance use
Smoking marijuana in public	48	68
Buying/carrying marijuana in public	50	67				12
Selling marijuana in public	50	74				10
Drinking alcohol in public	56	71					13
Smoking in non-smoking areas	40	81
Public display
Hanging out in street	55	58				13	20
Engaging in disorderly conduct	65	69				11
Making loud noises in public	56	68				12
Loitering w/o cause	53	67				14
Trespassing	60	72			10
Failing to cooperate w/police	55	65	11			17
Street business
Farebeating	69	66				11	13
Aggressive panhandling	29
Vending w/o license	62
Gambling/numbers in public	60	69					20
Prostitution in public	44	56				28
Sanitation
Urinating in public	49	71					13
Littering	66	65					31
Traffic
Driving while intoxicated	73	65		11
Driving w/o a license/registration	75	73	10
Ignoring red lights and stop signs	69
Speeding	65	72					12
Jaywalking	29

^aNotes: Among past-year doers that reported NYPD targets each behavior

^bAmong past-year doers that reported NYPD targets behavior that stopped or cut back. Reasons based on fewer than 25 respondents not shown. Percentages below 10 percent not shown Estimates weighted to control for overrepresentation of females Reasons: A) police presence, B) contact with criminal justice system, C) involvement with drug treatment program, D) job related, E) family/relationship, F) other

Participation in QOL behaviors

The two most common QOL behaviors were hanging out in the street (47 percent) and farebeating (44 percent) – see Table II. Substance use behaviors were also relatively common. More than a third of the sample reported smoking marijuana, buying/carrying marijuana, and drinking alcohol in public (34-36 percent). Fewer reported selling marijuana in public (16 percent) or smoking in a non-smoking area (21 percent).

Public display behaviors (in addition to hanging out) were also common. About a quarter of the sample reported engaging in disorderly conduct, loitering, and trespassing (25-28 percent). Making loud noises, failing to cooperate with the police and belonging to a gang were less common (4-16 percent). Other than farebeating, relatively few arrestees engaged in each of the street businesses (213 percent). Almost a third of the respondents reported urinating in public (31 percent). Other unsanitary behaviors like littering were uncommon (3-15 percent).

Just over one-fifth of the sample reported jaywalking (22 percent) or driving without a license or registration (21 percent). Exceedingly few reported violating any of the other traffic regulations (311 percent). This was not surprising. Many low-income New Yorkers drive infrequently. Many do not even own cars. Indeed, some lifelong New Yorkers never even learn to drive.

Perceptions of QOL policing activity

Arrestees were well aware of the QOL policing initiatives. Table III presents the percentages that perceived police were targeting each QOL behavior. The table also breaks down the percentages according to whether an arrestee reported engaging in each behavior in the past year (doers) or not (non-doers).

Table III.

Arrestee perception of NYPD QOL policing efforts

		Percent that perceive NYPD targets behavior
Behavior	Total	Doersa	Non-doersa
Substance use
Smoking marijuana in public	92	98**	88**
Buying/carrying marijuana in public	91	97**	88**
Selling marijuana in public	92	96	91
Drinking alcohol in public	93	96*	91*
Smoking in non-smoking areas	56	76**	53**
Public display
Hanging out in street	72	81**	66**
Engaging in disorderly conduct	86	98**	82TFN5
Making loud noises in public	77	87*	75*
Loitering w/o cause	86	92*	85*
Belonging to a gang	76
Trespassing	82	98**	76**
Failing to cooperate w/police	85	100**	83**
Street business
Farebeating	88	95**	84**
Aggressive panhandling	73	95**	72**
Squeegee work	60
Vending w/o license	83	99**	82**
Selling counterfeit video/tapes	78
Buying/selling alcohol to minors	72
Buying/selling cigarettes to minors	69
Gambling/numbers in public	77	86	77
Prostitution in public	88	100	87
Sanitation
Urinating in public	82	94**	77**
Writing graffiti	68
Littering	62	74*	60*
Failing to pick up after your dog	50
Failing to recycle garbage	42	64*	42*
Traffic
Driving while intoxicated	94	100	94
Driving w/o a license/registration	93	98*	92*
Ignoring red lights and stop signs	91	94	91
Speeding	89	89	89
Drag racing	70
Talking on cell phone while driving	45
Violating traffic laws while bicycling	59	62	59
Jaywalking	52	57	51

^aNotes: Prevalence rates not shown if there were either fewer than 25 doers or non-doers

^*ANOVA test comparing doers and non-doers was statistically significant at the α=0.05 level

^**ANOVA test comparing doers and non-doers statistically significant at the α = 0.01 level Estimates weighted to control for overrepresentation of females

Nearly all arrestees reported that police were targeting public marijuana use/purchase/sale and public alcohol use (91-93 percent). Many fewer reported that police were targeting smoking in a non-smoking area (56 percent). Most arrestees perceived that police were targeting each of the public display behaviors (72-86 percent). Farebeating (88 percent) and prostitution (88 percent) were the street business most often reported as targeted. Fewer arrestees perceived that police were targeting squeegee work (60 percent), the cleaning (often aggressively) of car windshields at traffic lights for tips. In the early 1990s, the NYPD had explicitly targeted squeegee work and nearly eliminated this activity. Almost none (2 percent, see Table II) of the Policing Study respondents reported engaging in squeegee work. Hence, the NYPD may not have been targeting this behavior because they had already brought it under control. Many arrestees reported that police were targeting public urination (82 percent, Table III). Fewer (42-68 percent) reported engaging in other unsanitary behaviors. Arrestees perceived that police were targeting several traffic violations, including driving while intoxicated, driving without a license or registration, ignoring a stop, and speeding (89-94 percent).

We were surprised by the substantial number of arrestees that reported they perceived the NYPD was targeting failure to pick up after your dog (about 50 percent). During questionnaire development, NYPD officials told the Policing Study they were not targeting this violation. We decided to leave this violation in the questionnaire. However, we expected that nearly all of the respondents would report they perceived the NYPD was not targeting this behavior. We offer two possible explanations for the unexpected result – a baseline and a diffusion effect. Some persons might honestly but incorrectly perceive that the NYPD targets these behaviors. If this were true, then we might consider 50 percent to be an approximate baseline level. It identifies the percentage of arrestees that will perceive the police were targeting a behavior, even if they were not. Accordingly, we might conclude that QOL policing increased arrestees’ perception that the NYDP was targeting behaviors like smoking marijuana in public from about 50 percent to 92 percent. Alternatively, some of the respondents might have inferred that the NYPD targeted a very wide range of behaviors because they observed NYPD targeting some of them. This would represent a diffusion of the benefit from patrolling for some behaviors toward the reduction of a wider range of disorderly behaviors. If this were true, then we might conclude that QOL policing increased arrestees’ perception that the NYPD was targeting offenses like smoking marijuana in public from 0 percent to 92 percent and offenses like failing to pick up after your dog from 0 percent to 50 percent. The Policing Study data provide little insight into the extent to which either the baseline effect, diffusion effect, or both occurred. The Policing Study would have had a strong basis for distinguishing between these two interpretations had the project also collected data prior to the implementation of QOL policing. Additionally, such data could have also identified the extent to which arrestees perceived that the NYPD targeted various behaviors as part of their prior policing practices.

Overall, these findings suggest that arrestees got the message. Perhaps even more importantly, the right subset of arrestees was even more aware of each behavior the NYPD targeted. Those arrestees that engage in each QOL behavior were more likely to report that police were targeting it (see Table III). A total of 17 of 25 differences between doers and non-doers were statistically significant. Presumably, doers were more likely to spend time in locations where police patrolled for a QOL behavior. Doers also have a greater personal stake in noticing any police enforcement. Arrestees that smoke/buy/sell marijuana in public or drink in public were virtually unanimous in their perception that police were targeting these behaviors (96-98 percent). Similarly high rates of awareness (94-100 percent) occurred among doers of several other behaviors including disorderly conduct, trespassing, failing to cooperate with police, farebeating, aggressive panhandling, vending without a license, prostitution in public, urinating in public, driving while intoxicated, driving without a license or registration, and ignoring red lights and stop signs.

Reductions in QOL behaviors

Many arrestees that were aware of QOL policing initiatives reported stopping or cutting back in the past six months. Table IV presents the variation in reduction across QOL behaviors. The table also displays the variation in reasons given. Overall, about half of the arrestees stopped or cut back on each QOL behavior. The most reductions were in farebeating (69 percent), disorderly conduct (65 percent) and traffic violations (65-75 percent) other than jaywalking. The fewest reductions were in jaywalking (29 percent) and aggressive panhandling (29 percent). Jaywalking (walking against traffic lights) is endemic in NYC among most segments of the population – yet this traffic rule is actively enforced and obeyed in many other parts of the USA.

Consistent across the various QOL behaviors, about two-thirds of those reporting reductions listed police presence as their main reason (56-81 percent, Column A in Table IV). The importance of a police presence stands in stark contrast with the relative unimportance of direct contact with criminal justice agents (011 percent, Column B in Table IV). With regard to most QOL behaviors, fewer than 10 percent of the respondents who indicated reducing their involvements listed a direct criminal justice contact as the reason for their behavioral change. Family or relationship (0-28 percent, Column E in Table IV) was often the second most common reason given.

Discussion and conclusion

In practice, a policy may fail because its theoretical basis is unsound or because it is incorrectly implemented. In two previous field tests, QOL policing had no measurable effect on crime rates (Katz et al., 2001; Novak et al., 1999). These prior studies however provided little beyond informed speculation as to whether these were implementation or theoretical failures. This study illustrates how real-time monitoring with ADAM can provide feedback regarding the process of crime reduction. The fixing broken windows perspective suggests that QOL policing starts a complex chain of events starting with sending a message that the police will not tolerate disorderly behavior. The Policing Study provides empirical evidence that as of 1999 NYC arrestees had gotten the message. Of note, those that had engaged in disorderly behaviors were significantly more likely to be aware of the QOL policing initiatives.

These findings had been expected. The NYPD had initiated QOL policing years before this study took place, they had arrested thousands of persons, and the program had received much media attention. It would have been useful to have monitored changes in arrestees’ perceptions over time to observe how many arrestees thought that the NYPD was already targeting disorderly behaviors before QOL policing began and to identify how long it took before arrestees became aware of it. However, the study provides clear evidence that by 1999 arrestees knew that the NYPD did not tolerate various QOL behaviors.

The next question is whether this awareness led them to change their behavior. About half of those that engaged in each behavior in the past 12 months reported having stopped or reduced their involvement in the past six months. We found this finding complicated to interpret. In one respect, it is not clear why these persons engaged in any disorderly behaviors given that QOL policing had already been implemented in NYC for years. Optimistically, these offenders may have become more aware of QOL policing after they engaged in various QOL behaviors. This awareness may have been what led them subsequently to change their behavior. Two-thirds of the respondents reported that a police presence was the primary reason for their reduction. This suggests that QOL policing had served as a general deterrent to these respondents; they had either observed the police enforcement or word had gotten around.

Less optimistically, Harcourt (2001) suggested that QOL policing should ideally change community norms for behavior. From this perspective, it may be a disappointment that persons had still engaged in QOL behaviors years after implementing QOL policing. It is further disappointing that about half of them continued to do so despite their awareness of QOL policing. However, this finding may be partially an artefact of having interviewed arrestees, a highly selected population. These are the persons still sustaining arrests, despite any changes caused by QOL policing. A survey of NYC residents, even in inner-city neighborhoods, might have found much lower rates of participation and continuation of QOL behaviors.

It is interesting that so many arrestees were deterred from continuing QOL behaviors (or at least reduced their frequency of involvement). However, this deterrent affect may be short lived. Studies of deterrence have found that extralegal motivators are typically much stronger motivators than fear of legal consequences (Foglia, 1997; Grasmick and Bursik, 1990; Meier and Johnson, 1977; Nagin and Pogarsky, 2001). Based on a literature review, Nagin (1998, p. 20) concluded that, “[I]ndividuals who report higher stakes in conventionality are more deterred by perceived risk of exposure for law breaking.” Many individuals do not commit illegal acts because it would make them ashamed of themselves or they would suffer embarrassment if their families and peers found out. Consequently, these persons exhibit a strong internal acceptance of prevailing social norms as a basis for their actions (Hechter and Opp, 2001; Johnson, 1973; Wolfgang and Ferracuti, 1967).

Unfortunately, the policing study did not ask arrestees whether engaging in each QOL behavior might cause them shame or possible embarrassment. Such questions would have identified whether they had internalized the behavioral change. We hypothesize that most NYC arrestees would not feel shame or embarrassment. Their demographics suggest that most of them had weak attachments to conventional society. They had committed a variety of crimes, engaged in various disorderly behaviors, been to jail, used illicit drugs, and lacked education, spouses, and jobs.

If arrestees were only weakly deterred, then QOL policing might only temporarily reduce disorder and crime. Hot spots research has found that the impact of intensive policing is often short lived and geographically limited (Sherman, 1995; Sherman and Weisburd, 1995). Highly concentrated police enforcement may cause offenders to move to another location or to employ a variety of concealment strategies. Once heavy enforcement ends and word spreads among street networks, offenders may return to their disorderly and criminal behaviors.

However, NYC has not implemented QOL policing as a one-time program. QOL policing has been a major and ongoing component of a complex strategy underlying NYC law enforcement efforts over time by Mayor Guiliani in the 1990s (Silverman, 1999) and continued by Mayor Bloomberg in the 2000s (New York Times, 2001a, b). NYC’s commitment to QOL policing is based in even earlier use of the approach. Starting in the 1980s, the NYC transit police developed QOL policing procedures to clean up the NYC subway system (Kelling and Coles, 1996; Maple and Mitchell, 1999). Perhaps as a long-term philosophy, QOL policing will have a larger, more enduring effect.

This important conjecture extends this discussion well beyond the scope of the current analysis. The Policing Study examined the first critical linkage in the QOL policing approach, whether offenders had gotten the message. It did not examine whether QOL policing had reduced disorder or crime overall. As described in the introduction, there has been little systematic analysis of the relationship between disorder and crime and the findings of that research was mixed. Certainly, this is an important topic for further research given NYC’s long-term commitment to QOL policing. Beyond that, establishing how QOL policing works, and how well, will facilitate the effective adaptation of the program to different times and places.

Even more broadly, contemporary policing involves use of numerous tactics, with assorted aims, based on multiple strategies. Sometimes these tactics, aims and strategies overlap and sometimes they are at cross-purposes. Recently, many police departments have emphasized problem-oriented (Goldstein, 1990) and community policing (Greene, 2000; McElroy et al., 1993; Skogan and Hartnett, 1997). In some respects, QOL policing overlaps with these approaches because it focuses on underlying problems, fear of crime and quality of life in public places (Ponsaers, 2001; Greene, 2000). On the other hand, QOL policing emphasizes arresting even minor offenders[5]. The community policing perspective maintains that the overuse of arrest alienates the police from the community (Greene, 2000; Rosenbaum et al., 1998; Walsh, 2001). In the face of the complexity of police practice, monitoring the effect of policing initiatives using programs like ADAM holds the promise of helping identify effective approaches and areas for potential improvement.