Managerial Decision-Making

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Police decision making: an examination of conflicting theories Scott W. Phillips and James J. Sobol

Criminal Justice Department, Buffalo State College, Buffalo, New York, USA

Abstract

Purpose – The purpose of this paper is to compare two conflicting theoretical frameworks that predict or explain police decision making. Klinger’s ecological theory proposes that an increased level of serious crimes in an area decreases the likelihood an officer will deal with order-maintenance issues, while Fagan and Davies suggest an increase in low-level disorder will increase order maintenance behavior of police officers. Design/methodology/approach – Using a vignette research design, the authors examines factors that may contribute to police officers’ decision to make a traffic stop in four jurisdictions with varying levels of serious crime. Ordered logistic regression with robust standard errors was used in the analysis. Findings – Analysis of the findings demonstrates that officers who work in higher crime areas are less likely to stop a vehicle, as described in the vignettes. Additional predictors of police decision to stop include vehicles driven by teenaged drivers and drivers who were speeding in a vehicle. Research limitations/implications – The current research is limited to an adequate but fairly small sample size (n¼204), and research design that examines hypothetical scenarios of police decision making. Further data collection across different agencies with more officers and more variation in crime levels is necessary to extend the current findings. Originality/value – This paper adds to the literature in two primary ways. First, it compares two competing theoretical claims to examine a highly discretionary form of police behavior and second, it uniquely uses a vignette research design to tap into an area of police behavior that is difficult to study (e.g. the decision not to stop).

Keywords United States of America, Police, Policing, Decision making, Workload, Traffic stops, Vignettes

Paper type Research paper

Introduction Police work requires officers to deal with a substantial amount of non-criminal activity, such as resolving disputes (Johnson and Rhodes, 2009) or dealing with problems or very low-level offenses that fall into the broad description “order maintenance activities” (Walker and Katz, 2005). There are potential benefits when officers deal with these low-level problems or offenses, such as reducing the chance of further crime or increasing the officer’s environmental knowledge to improve problem solving (Walker and Katz, 2005). One of the most common types of order maintenance activities takes place in the form of a traffic stop (Walker and Katz, 2005), which could be seen as “a form of order maintenance where the officer has taken action against a suspected individual in order to prevent crime” (Vito and Walsh, 2008, p. 93).

Many traffic stop studies were conducted in the past decade to determine if police officers were using race in their decision to stop a vehicle (e.g. Gaines, 2006; Meehan

The current issue and full text archive of this journal is available at www.emeraldinsight.com/1363-951X.htm

Received 25 February 2011 Revised 21 June 2011 Accepted 7 July 2011

Policing: An International Journal of Police Strategies & Management

Vol. 35 No. 3, 2012 pp. 551-565

r Emerald Group Publishing Limited 1363-951X

DOI 10.1108/13639511211250794

The authors would like to thank Sean P. Varano for his invaluable assistance in the vignette construction process.

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and Ponder, 2002a, b; Mosher et al., 2008; Petrocelli et al., 2003; Schafer et al., 2004; Smith and Petrocelli, 2001; Withrow, 2004a, b). Some of these studies included neighborhood characteristics in their examination of police decision making, such as an officer’s perception of the racial makeup of a patrol area (Albert et al., 2005) and the crime rate of a neighborhood (Petrocelli et al., 2003; Withrow, 2004a, b). Where many studies of traffic stop decision making were unguided by theory (Engel et al., 2002), the work of Klinger (1997) and Fagan and Davies (2000) provide theoretical guidance to predict or explain how patrol area can impact an officer’s decision to stop a person. Both theoretical frameworks, however, offer different predictions based on the type of criminal activity in the patrol area. A postulate within Klinger’s (1997) ecological theory assumes that workload influences when formal legal authority is applied. That is, police officers reserve their attention for more serious crimes in areas with higher-crime rates or more serious criminal behavior. Conversely, Fagan and Davies (2000) theory asserts that officers are more aggressive in response to low-level order maintenance problems.

This research sought to examine the relationship between the work location of a police officer and its impact on a police officer’s judgment to stop a vehicle to determine which theoretical framework is supported. There were at least two justifications for this study. First, because police department policy is often based on theoretically framed research (Engel et al., 2002), it is important to assess components of these two competing theoretical frameworks to determine which is empirically sound when explaining police behavior. Further, if theories are necessarily incomplete (Bernard and Ritti, 1990), the present study may uncover conditions unique to each so they can be appropriately adjusted.

Theory Researchers argued that studies of traffic stop decision making should not be viewed as scientific research because they failed to explicitly state the guiding theory of their research (Engel et al., 2002). To address this concern, the present inquiry attempted to shed light on police officer behavior during their routine patrol duties using two conflicting theoretical perspectives. One suggests that low-level offenses increase the likelihood that police officers will stop a person in an effort to deal proactively with bigger problems. The second proposes that officers are less likely to deal with low-level offenses and reserve their limited time and resources to deal with more serious crimes.

Order maintenance policing Fagan and Davies (2000) provide a detailed discussion of police decision making, explaining why the 1982 Broken Windows theory of Wilson and Kelling, which focussed on police response in disorderly places, morphed into a policing tactic that focussed on people. It had been theorized that social disorganization in the form of an increased poverty rate, predominately decreased age distribution (i.e. younger population), and population turnover lead to increased crime rates across neighborhoods. Fagan and Davies (2000) explained that while social disorganization predicted rates of disorder in an area (e.g. loitering, public drinking), social disorganization does not predict homicide rates and only weakly predicted robbery rates. Therefore, efforts to control serious crime via disorder policing are unlikely to be effective.

Based on the notion that proactive enforcement of minor crimes and disorder would reduce serious crime, the New York City Police Department (NYPD) increased their use

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of tactics dealing with order maintenance issues in neighborhoods with the highest levels of disorder crime. Order maintenance policing was intended to focus on “quality of life” issues, such as public drinking or panhandling, under the assumption that police enforcement of laws against these types of crime would reduce more serious criminal behavior. Fagan and Davies (2000) reported that the NYPD order maintenance policing policy was intended to address gun-crimes as one of the more serious criminal behaviors that could be deterred through aggressive enforcement of disorder crimes[1]. A successful order maintenance policing approach would require a “pro-active interdiction” (Fagan and Davies, 2000, p. 475) of anyone suspected of violating even minor offenses. This tactic, however, led to an increased use of “pretextual” stops, where police officers would scrutinize a person for any type of minor offense in order to establish a minimal level of reasonable suspicion to stop and frisk the person in the hopes of discovering a more serious offense (Fagan and Davies, 2000).

Ecological workload A neighborhood attribute that likely has a direct impact on police officers’ decision making is the actual workload of the officers who patrol a neighborhood. Klinger (1997) suggested that as the number of calls-for-service and deviance levels of a work location increase, officers have less time to deal with citizens’ complaints. When an officer has less time available for dealing with the work in their patrol area, officers must manage their time by prioritizing the tasks they focus on. This formula pushes the officer’s “towards leniency as deviance increases” (Klinger, 1997, p. 293). When a police officer works in a location that has fewer calls-for-service or lower levels of deviance, the officer is free to use as much time as needed to deal with an incident (Klinger, 1997).

Klinger (1997) relies on the work of Donald Black to build his discussion of “leniency,” which Klinger described as the amount of law a police officer applies to an incident. For example, a police officer could spend a substantial amount of time stopping vehicles but never issue a citation. Strictly speaking, not issuing a ticket would be considered a lenient response by the officer. Still, the workload aspect of Klinger’s (1997) ecological theory clearly implies that “leniency” is the actual attention or effort that a police officer devotes toward a problem. As a result, when Klinger stated police officers will be lenient “for increasingly serious crimes as levels of district deviance increases” (Klinger, 1997, p. 293), it is reasonable to assume that police officers who patrol areas with more serious crime would be less likely to focus their attention on traffic stops.

Klinger’s work has yet to receive consistent empirical support. For example, Sobol (2010) examined postulates of Klinger’s theory and conceptualized workload as the amount of time officers had “assigned” vs “unassigned” to explain the vigor with which the police used their formal authority. Surprisingly, Sobol found that workload and district crime were negatively correlated (r¼�0.16) and that workload did not significantly affect the vigor with which the police used their formal legal authority. Other research shows that neighborhood characteristics influence an officer’s decision to “translate” a call-for-service into an official crime report; however, “neighborhood influences vary by crime type” (Varano et al., 2009, p. 560). Looking at studies on traffic stop specifically, to date, no study has included a workload variable in their analysis, but a few studies offer what might be considered reasonable surrogates that help build a foundation for this approach. Contrary to what might be expected within Klinger’s (1997) ecological theory, Roh and Robinson (2009) reported that patrol beats with more crime (i.e. hot spots) are related to an increased likelihood of a traffic stop. In addition,

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Phillips (2009a) found that sheriff’s deputies were less likely to stop a vehicle than officers in two small township police agencies. Although Phillips does not speculate, it may be that sheriff’s deputies have substantially more area to cover and are more likely to conserve their time resources by engaging in fewer traffic stops.

Literature review Background: traffic stop research A number of different factors might influence the decision to stop a vehicle: neighborhood aspects, characteristics of the driver, organization influences, and legal factors. Each will be briefly discussed below in order to frame an understanding of the present research.

Scholars have advised that a greater understanding of traffic stop behavior is limited because many studies rely on data from one large police department or jurisdiction (Mosher et al., 2008; Novak, 2004; Parker et al., 2004). Police behavior often occurs in a beat or neighborhood context and the use of race in the decision to stop a vehicle “could possibly be more prevalent in racially homogeneous communities” (Novak, 2004, p. 73). Smith and Petrocelli (2001) found that the Part-I crime rate of an area was not related to the police decision to stop a vehicle. Later, Petrocelli et al. (2003) examined multiple neighborhood characteristics in the decision to stop a vehicle, including percent black population of the neighborhood, percent of families below poverty line, percent unemployed in neighborhood, mean family income, and Part-I crimes per 1,000 population. They found that police tended to make more stops in neighborhoods with higher-crime rates. Alpert et al. (2007) examined the racial makeup of neighborhoods where traffic stops occurred and found no connection between racial composition and police stops. Withrow (2004a) found that drivers stopped during the night and driving in higher-crime areas were more likely to be black drivers. Similarly, when using in-car computer queries as a measure of surveillance, Meehan and Ponder (2002b) found that officer scrutiny “significantly increases as [African Americans] travel farther from ‘black’ communities and into whiter neighborhoods” (p. 422).

Some research has found that a driver’s race is related to the police officer’s decision to stop a vehicle. Several studies reported a relationship between black drivers and the decision to stop a vehicle (Miller, 2008; Warren et al., 2006), while others have found only a weak (Novak, 2004) or no relationship (Phillips, 2009a) between black drivers and the decision to stop a vehicle. Driver age, however, was found to be related to the decision to stop (Miller, 2008). Further, the driver’s gender (i.e. male) was significantly related to police decision to stop a driver (Miller, 2008; Warren et al., 2006).

Early research into the influence of police organizations on an officer’s decision making suggested management style and agency size may impact traffic stop behavior. Wilson (1978) posited that officers who worked in agencies with a legalistic management style “will issue more traffic tickets at a higher rate” (p. 172). Others (Brown, 1981; Mastrofski et al., 1987) found that police officers working in agencies of differing size behave differently in traffic stop situations. More recently, Mosher et al. (2008) reported that most prior research of police decision making in traffic stop situations takes place in only one jurisdiction. This drawback does not allow researchers to determine if organizational characteristics influence the decision making of police officers. Phillips (2009a) analyzed the responses of police officers in two small agencies against sheriff’s deputies and found that sheriff’s deputies were significantly less likely to stop a vehicle. His study is limited because he collected data in only three law enforcement agencies and the number of officers in this study was small.

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When legal considerations were included in the research, Withrow (2004b) stated most traffic stops occur when a driver commits a more serious traffic offenses (e.g. moving violations) than for less serious traffic offenses (e.g. equipment violations). Others suggest that drivers who are speeding (Phillips, 2009a), commit moving violations (Warren et al., 2006), or equipment violations (Alpert et al., 2007) are likely to be stopped. Novak (2004) reported that white drivers are more likely to be stopped for moving violations, unsafe driving, and speeding.

It has been suggested that a measure of vehicle characteristics or quality that is involved in a traffic stop should be studied because some cars may be customized in a manner the draws the attention of police officers (Batton and Kadleck, 2004; Ramirez et al., 2000). While vehicle quality has never been clearly operationalized in prior studies, it is suggested that “car effect” (Batton and Kadleck, 2004) could include a poor quality vehicle (Engel and Calnon, 2004) or an older vehicle (Miller, 2008; Warren et al., 2006), Alpert et al. (2007) found that vehicle age had no impact on the decision to stop a vehicle; other research indicated older vehicles were related to the decision to stop a vehicle (Miller, 2008). Phillips (2009a), however, found that a newer vehicle was related to the decision to stop the vehicle.

This study As the literature review demonstrated, the decision making of street-level police officers in traffic stop incidents may be influenced by different factors. The few studies that incorporated a neighborhood crime-rate variable (Petrocelli et al., 2003; Withrow, 2004a) found a positive relationship between this dimension and the decision to stop a vehicle. These results tended to support the framework provided by Fagan and Davies (2000). Such findings, however, may be difficult to generalize since their data were collected from one large urban police department (e.g. NYPD). In addition, Klinger’s (1997) discussion provides a general theoretical framework for police behavior, but does not consider the other variables that may mediate the influence of area, such as organizational size, the agencies management style, or the type of law enforcement agency (i.e. local, county, or state).

This study sought to examine assumptions from the two competing theoretical models to explain police decision making in traffic stop situations. It offers an empirical examination of the influence of “neighborhood,” as suggested by both Fagan and Davies and Klinger, on the judgment of police officers in traffic stop situations while controlling for various aspects of the incident, including driver characteristics and legal aspects. Two features of this study contribute to our understanding of police decision making. First, data were collected in multiple police agencies of varying sizes, which can help minimize the problem of “aggregation bias” in most other studies of only one large jurisdiction (Mosher et al., 2008, p. 46). Like other studies, however, the respondents do comprise a convenience sample. Second, a vignette research design is used (Rossi, 1979; Rossi and Anderson, 1982), allowing the inclusion of multiple variables into vignettes to examine the decision making of a police officer to stop a vehicle. An additional benefit to the vignette research design is that it may minimize. Withrow (2004b) stated “because there is no record of the individuals not stopped,” most designs cannot determine the influence any variable on getting stopped (p. 229, emphasis in original). The vignette research design minimizes this problem because the design allows for the inclusion of multiple variables and can control for those cases where a person is not stopped by officers.

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Data and methods Study location Data used in this study were collected from police officers in four police agencies in New York State. Table I provides general information on the agencies and jurisdiction. The study locations can be roughly divided into two groups. One is the work district of a large urban police agency with neighborhoods of concentrated population and higher levels of serious crime and disorder, while the other three study locations consist of two small township agencies and a county sheriff’s department with very low crime levels. Including officers from two small agencies and a county sheriff’s department distinguishes this research from other studies of the police and traffic stop decision making because the studies cited in this paper used data primarily collected in large agencies or suburban areas near larger cities.

The Lower Town Police Department and the Upper Town Police Departments (all department names are pseudonyms) serve townships and employ part-time and full-time police officers. These townships border each other, as well as a city of approximately 50,000 people (not part of this study). Police officers in the townships furnish routine patrol services, are dispatched to calls by the county sheriffs’ department, and provide no special services, such as detectives. The township police agencies offer a fairly diverse working environment for officers, with traditional style neighborhoods laid out in a grid pattern that include single family and apartment housing, shopping plazas with department stores, grocery stores, small shops, secondary highways with extensive commuter and commercial traffic, and rural areas with farms and rural housing. The third agency is the Lake County Sheriff’s Department. Deputies provide patrol services for a sizable rural area as well as several small towns and villages that employ no other police services. All three agencies serve a fairly homogenous population, and have few violent index crimes.

The large police agency that participated in this study was the River City Police Department, specifically the North District (River City has five patrol districts). This agency is also located in Upstate New York. As indicated in Table I, North District is densely populated and is considered fairly common as large city areas go.

Jurisdiction Square miles

Patrol officers

Violent index crimes (2007)

Property crimes (burglary, larceny,

car theft) Population

served

Race (white, African

American, Others)

Lower Town P.D.

64 14 17 (2 rapes, 1 robbery, 14 aggravated assaults)

177 8,978 93, 3, 4

Upper Town P.D.

9 17 16 (4 robberies, 12 aggravated assaults)

334 19,038 97, 1, 2

Lake Co. 552 60 79 (15 rapes, 14 robberies, 50 aggravated assaults)

1,336 108,714a 90, 6, 4

North District 9.6 96 1,063 (14 murders, 53 rapes, 533 robberies, 462 aggravated assault)

5,230 78,700 44, 34, 7b

Notes: aDoes not include the population (111,134) of three cities within the county that employ their

own police agencies; bUS Census data for 2000 for all of River City; cdepartment data

Table I. Description of research locations (US Census data and New York State Division of Criminal Justice Services crime data, US Census Bureau)

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The population of North District is racially diverse compared to the smaller jurisdictions, and has a substantially higher number of violent index and property crimes than the other agencies.

Research design A vignette research design employ aspects of a random experiment by incorporating each variable as a unique dimension within the vignette, and randomly vary the level of each dimension between vignettes (Rossi, 1979; Rossi and Anderson, 1982). Vignettes are then randomly assigned to respondents. This design measures respondents’ judgment or decision making as the level of each dimension changes. That is, as the level of one dimension changes, its influence in the judgment or decision-making process may shift in relation to another dimension. The vignettes used for this study were constructed along several variables (discussed below), and vignettes have been successfully used to examine police opinion and decision making in other work situations (Eterno, 2003; Hickman et al., 2001; Phillips, 2009b; Phillips and Sobol, 2010).

Vignettes possess aspects of a controlled, random experiment and, therefore, provide a benefit in studying the judgment of police officers in traffic stop incidents: collecting data on vehicles not stopped. When there is an absence of data regarding citizens not stopped, as is the case in almost all prior traffic stop research, untangling the significant aspects of those who are stopped from those who are not is unworkable, making it impossible to discover which dynamics explain variations in police officer decision making. Further, using vignettes provided a unique opportunity to study multiple factors that may influence a police officers’ decision to stop a vehicle prior to actually stopping a vehicle. Most studies of traffic stop decision making collects data after the stop has occurred.

Data collection A total of 100 survey packets, each of which included randomly constructed vignettes exploring different activities police officers’ encounter (domestic violence incidents, use of force incidents, traffic stop incidents), were constructed. Each packet contained two randomly selected vignettes describing a driver and vehicle that they encounter during routine patrol. Police officers in the sample agencies were provided with a randomly selected survey packet. Several methods were used to improve the validity of responses because police officers may be reluctant to respond to outsiders who ask questions about their behavior. A cover letter informed the respondents that their answers would not be seen by police management. Second, officer identities would be kept anonymous.

Two methods were used to collect data in the smaller agencies during the summer of 2005. First, survey packets were passed out to patrol deputies in the Lake County Sheriff’s Department during all roll-call periods over the course of several days. Deputies completed the surveys during that time and returned them in a sealed envelope to the researcher. In total, 39 surveys were passed out and 38 were returned completed. The Upper Town Police Department does not have a routine roll-call period; however, during the data collection period the department had scheduled a department staff meeting. The police chief allowed the researcher to distribute surveys to police officers during this meeting. A total of 13 survey packets were distributed to the available officers and all were returned completed. The second method for collecting data was used in the Lower Town Police Department because Lower Town does not

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have a routine roll-call period. Survey packets were left for the officers in their departmental mailboxes. Officers returned the surveys to the police chief in a sealed envelope, and they were returned in bulk to the researcher. In total, ten surveys were distributed and nine were completed.

The second data collection period occurred during the summer of 2006. A graduate student who works as an officer in River City distributed newly constructed survey packets to patrol officers in North District during all roll-call periods where they were completed and returned in a sealed envelope. Other than a brief verbal explanation of the study and the anonymity of the respondents, the graduate student had no interaction with the officers. The packets contained traffic stop vignettes constructed in an identical fashion as those used in the smaller agencies. In total, 45 survey packets were distributed and 42 were completed. A total of 102 police officers completed two vignettes and each completed vignette represented a case in the data file. The total number of complete vignettes from all respondents in the four police agencies thus was 204. Table II provides a description of the variables used in this study.

Dependent variable Many studies of traffic stop decision making use multiple dependent variables, such as the original decision to stop a vehicle, the decision to search the vehicle, and how the stop ended (i.e. no action, warning, citation) (Engel and Calnon, 2004; Petrocelli et al., 2003). One deficiency when using a vignette design is that it is difficult to include “contingency” questions that would elicit subsequent decisions as an incident progresses through time. As a result, this study used only one dependent variable: a police officer’s self-reported likelihood of stopping a vehicle on a five-point Likert scale (1¼very unlikely to stop traffic; 5¼very likely to stop traffic).

Independent variables – vignette dimensions and officer characteristics The following is a review of the vignette dimensions used in this study. For a detailed discussion of the justification for these dimensions, see Phillips (2009a). Research vignettes described three driver characteristics. The first dimension was the driver’s

Variables Range M SD

Dependent variables Stop 1-5 3.61 1.01 Independent variables Sheriff 0-1 0.37 0.48 Upper Town 0-1 0.12 0.33 Lower Town 0-1 0.08 0.28 Black 0-1 0.34 0.47 Hispanic 0-1 0.32 0.46 Sex 0-1 0.53 0.49 Age teen 0-1 0.36 0.48 Age_20 0-1 0.30 0.46 Vehicle type 0-1 0.50 0.50 Tint 0-1 0.50 0.50 Cell phone 0-1 0.33 0.47 Speeding 0-1 0.39 0.48 Experience 0-35 10.17 6.78

Table II. Variable description

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race: white, black, and Hispanic. The second dimension was the driver’s gender and a third dimension is the driver’s age. The driver’s age is an ordinal-level variable describing a driver who appears to be in their late teens, late 20s, or late 30s (the reference category). This description is intentionally vague because police perception of a driver, not the actual age of the driver, is considered important to a police officer’s decision to stop a vehicle (Ramirez et al., 2000). These age categories were selected because it was believed that police officers would be much less likely to stop older drivers (i.e. those who appear at least 40 years old), and a pre-teen driver would almost certainly be stopped.

The first vehicle characteristic was type of vehicle: a “new SUV” or an “old 4-door sedan.” A second vehicle characteristic that might draw the attention of a police officer is window tinting (Batton and Kadleck, 2004). This dimension was dichotomized here: the vehicle had tinted windows, or the dimension will be left blank in the vignette, an acceptable method for varying the level of a dimension ( Jacoby and Cullen, 1999).

A specific traffic violation was included in all vignettes in order to establish a legal justification for the stop. Ramirez et al. (2000) argued that it may be helpful to include different types of violations to understand the role traffic offenses play in police decision making. Three traffic violation levels were used here in the vignette dimensions. First, a traffic violation will be indicated as “speeding.” A specific speed was not included. Not all police vehicles are equipped with a RADAR system to determine the exact speed of a car, and it is anticipated that simply indicating to a police officer that a person is speeding will satisfy the amount of information necessary to establish probable cause for a stop. Second, the 2002 legislation in New York State made it a traffic offense to talk on a hand-held cell phone while driving a vehicle. This offense was included as an intermediate-level violation. The third dimension described a broken tail light, a minor equipment violation. A sample vignette and dimension levels can be found in the Appendix.

Because the small police agencies involved in this study employed almost no female or minority officers, it was decided that asking additional questions of a personal nature in these agencies would threaten confidentiality and might result in a reduced response rate. The only officer characteristic that was collected was the years of experience.

Analytic strategy Because each police officer completed two vignettes, the data may have a clustered structure. Clustering of observations may violate the assumption of independence in the variables, causing an artificially deflated standard error and making it easier to find significance effects (Williams, 2000). For this reason the “cluster robust standard error” option in STATA was utilized. This option provides a more robust estimate of the standard error because it adjusts for the potential clustering of observations.

Findings As seen in Table III, police officers serving in the two smaller townships were significantly more likely to report stopping a vehicle described in the vignettes compared to officers who worked in the larger city area (North District was the reference group in the analysis). Although patrol deputies who worked for the county sheriff’s department were not significantly different in their responses to vignettes than officers in North District, these findings suggest that workload dimensions may shape police decision making in traffic stop incidents. That is, the police officers working in

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North District, an area with higher levels of serious crimes when compared to the other jurisdictions in this study, do not appear very concerned with stopping vehicles for traffic violations. Klinger’s (1997) suggestion that officers who work in higher- workload neighborhoods focus less on minor offenses appears to be supported when examined in the context of traffic stop situations described in the vignettes.

Two other vignette dimensions were also related to the decision to stop a vehicle. First, if the vehicle was speeding, police officers were significantly more likely to stop the vehicle. This was the most serious traffic offense described in the vignettes, and the finding is interesting because the offense was simply described in the vignette with no supporting information (i.e. the speed was not confirmed with RADAR). Second, officers were more likely to indicate they would stop a teen-aged driver when compared to a driver who appeared to be in their 30s. None of the other driver or vehicle characteristics described in the vignettes were related to the officer’s decision to stop a vehicle.

Conclusion and discussion This study was constructed in response to the body of research suggesting that neighborhood context may influence police decision making, and the fact there are two conflicting theories to explain variation of police behavior across those contexts. Klinger’s (1997) ecological theory posits that police officers respond to components of their work environment, including the area workload, and that they must manage their time more effectively. Fagan and Davies (2000) explained that officers are more aggressive when dealing with a neighborhood’s order maintenance issues in order to address more serious crimes in those areas. The findings from this investigation suggest that officers assigned to high-crime areas would be less likely to deal with low- level traffic violations described in vignettes, lending support to Klinger’s framework.

Fagan and Davies (2000) order maintenance explanation of police officer decision making should not be dismissed. They described police behavior that was influenced not simply by the environment, but also the police organization. The New York City Police Department administration expected aggressive street intervention by street officers. A second latent component of their study, which was never explicitly

Variable Coefficient Robust SE Odds ratio

Sheriff 0.20 0.49 1.22 Upper Town 1.02* 0.43 2.77 Lower Town 1.96** 0.30 7.09 Black 0.00 0.37 1.00 Hispanic 0.10 0.20 1.10 Sex �0.38 0.33 0.68 Age teen 0.35* 0.17 1.42 Age_20 0.33 0.21 1.39 Vehicle type 0.25 0.15 1.28 Tint 0.49 0.38 1.63 Cell phone 0.58 0.33 1.79 Speeding 0.78** 0.12 2.18 Experience 0.00 0.02 1.00 Pseudo R2 0.05

Notes: *po0.05, **po0.01

Table III. Ordered logistic regression for likelihood of traffic stop (N¼204)

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discussed, is that order maintenance policing appears to include a heavy “foot patrol” element. Foot patrol officers may be able to focus their attention more heavily on order maintenance tasks because it is a slower method of patrol and is concentrated in urban areas where officers are expected to deal with order maintenance offenses. Further, foot patrol officers might answer fewer calls-for-service, thus they would not have the same workload considerations of the officers described by Klinger (1997).

The order maintenance explanation of Fagan and Davies also bears further examination because the crime values provided in Table I are raw numbers, suggesting North District has the more substantial crime problem than the other study locations. If crime rate is used (in this study, violent index crime plus property crime/population) for comparison purposes, Upper Town and Lower Town have higher-crime rates than Lake County. Because the results indicate officers in the townships are more likely to stop a vehicle described in the vignettes than deputies in the sheriff’s department, this seemingly supports the assertion of Fagan and Davies.

Readers should be cautioned not to extend these findings too far. While officers in higher-crime areas may be less likely to stop a vehicle described in the vignettes, this may be a general response to the vignettes alone. It is unknown if real-world situations would result in the same response. Similarly, we are unable to determine how a police officer would respond, in reality, if they had to choose between a simultaneous call-for-service or traffic stopping incident. Furthermore, there may be a temporal component in an officer’s decision making that was not part of the vignettes, nor is it a consideration in the two theoretical frameworks. A police officer who is on patrol during the slower times of a shift, for example, 3-4 a.m. may stop a vehicle because of boredom, and this may occur regardless of the characteristics of the patrol area (Barthe and Stitt, 2009). If this is the case, both theoretical frameworks require adjustment.

Before discussing directions for future research, several research limitations should be acknowledged. First, this study does not have specific data on the workload of the officers. Where Varano et al. (2009) used calls-for-service as an indicator of workload, this study used raw violent crime and property crime levels as proxy measures for the workload of the police officers who patrol in the different police agencies. Second, while the sample size in this study is adequate, future scholars should attempt to increase the number of officers studied. Third, large jurisdictions, such as River City, may have intra-jurisdictional variations that should be explored, as carried out by Varano et al. (2009) when they used census tracts to examine police decision making. Data collected in only one district missed this possibility. Third, the use of data from jurisdictions with clearly different characteristics is not the same as measuring officer’s behavior when working in small areas or neighborhoods. It is believed, however, that the divergent jurisdictions used in this study provided an acceptable surrogate for further researchers to build upon. Finally, there are limits to the use of vignettes in a study, in that they only mimic reality. For example, where this research was able to specify driver characteristics in the vignettes, this is not often the case in reality (Phillips, 2009a; Waddington et al., 2004). This consideration must be balanced against the benefits of a vignette research design, such as the ability to increase the sample size in small police agencies, the ability to integrate and control multiple dimensions, and their ability to control for those cases where a person is not stopped by officers.

This study has theoretical and policy implications. First, both theoretical frameworks discussed in this study appear to need adjustments. Klinger’s (1997) argument may not apply well to sheriff’s deputies who patrol expansive rural areas.

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Further, he may have to consider smaller “beat” sized areas as an ecological unit so as to evaluation whether police decision making varies. Fagan and Davies (2000) position may pertain to a narrow patrol tactic used in higher-crime area. With respect to policy implications, if police officers in higher-crime areas minimize their attention on low-level offenses, this may actually feed into the continued disorder that contaminates a neighborhood. Police administrators may have to find ways to shift an officer’s attention to low-level problems in order to reduce the conditions that feed more serious crime (Lurigio and Rosenbaum, 1994). Police administrators might want to focus on additional training for those officers assigned to particular high-crime areas or at least reconsider officer preference and seniority when it comes to officer deployment. The placement of officers in particular districts or areas could have significant ramifications for the control of crime (Sobol, 2010). Using officer preference or seniority as factors that determine officer assignment may not be the most organizationally efficient way to implement and sustain police efforts to combat crime or implement various community policing initiatives. Finally, results from the current study also shed light on the necessity to consider the number of officers assigned within a particular district or jurisdiction. If indeed officer workload is a vital precursor to officer decision making, then one way to offset the amount of workload for any one officer is to have more on duty during any particular shift. Future research might wish to consider this dimension in the development of their vignettes and assess the extent to which it influences the police officers decision to stop a vehicle.

Note

1. Where the social disorders described in the Fagan and Davies (2000) discussions are inherently non-traffic in nature, they never specifically describe the patrol type, whether foot or motor patrol, being used by the NYPD’s order maintenance policing. The impacts of patrol type on the results of this study are reviewed in the discussion section.

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