Biased Policing Research Pape

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Overview

This research paper will address the issues associated with police racial and ethnic bias, including research findings, research limitations, and policy issues related to reducing racial and ethnic disparities.

Introduction

Why are racial and ethnic minority citizens overrepresented at every stage of the criminal justice system? Answers to this reality are not clear or straightforward. While all criminal justice actors enjoy a degree of discretion in their decision-making, it is particularly important to determine whether bias is present in the early stages of the criminal justice process because initial biases can cause reverberations throughout the entire criminal justice process. The differential treatment patterns and practices of police in their decision-making have historically manifested itself in several ways (e.g., sexism, ageism) and garnered widespread attention. More specifically, a well of skepticism exists among citizens, scholars, legislatures, and the judiciary in response to the overrepresentation of racial and ethnic minorities at every stage of the criminal justice process. In response to the appearance of racial and ethnic animus in police decision-making, voluntary, legislative, and judicial data explorations of racial and ethnic biases in police discretionary decision-making have been encouraged.

The following manuscript addresses several issues associated with racial and ethnic bias among police. First, decision-making is contextualized as it relates to bias among policing discretion. Second, the difficulties of measuring bias-based policing are discussed within the context of future research endeavors. Third, research findings across various police decision-making points, including the use of force, the decision to arrest, and automobile stops, are presented. Fourth, commentary on contemporary manifestations of bias-based policing is set against a post-9/11 America. Fifth, bias-based policing results are tempered by some of the acknowledged limitations of prior research. Finally, a policy framework for reducing racial and ethnic disparities among officer discretionary decision-making is advanced.

Discretionary Decision-Making

Discretionary decision-making has been defined as “informal decision-making or [a] judgment by professionals based on unwritten rules, their training and their experience” (Samaha 2005, p. 10). Discretionary decision-making stands in opposition to mandatory acts, such as obeying the law and following departmental policies. Davis (1969) contextualized the relationship between law and discretion as “where law ends, discretion beings” (p. 3). Although this absolute dichotomy is false (see Walker 1993), law and discretion are related to the concept of procedural justice. Procedural justice refers to processes of fairness (Sunshine and Tyler 2003). Police discretionary decision-making is perceived to be fair when it is based on facts. Rarely is the legitimacy of fair outcomes called into question. Alternatively, discretionary decision-making is problematic when the judgments of police are seen as unfair, not based on law, and/or based on personal biases. This lead Walker (1993) to conclude that “[t]he problem is not discretion itself, but its misuse” (p. 4). More specifically to the topic at hand, bias-based policing or the selective/differential enforcement patterns and practices of police on minorities have the appearance of abuse.

Contrary to folklore, research indicates police receive overwhelming support from the public, and this support has been stable over time (Tuch and Weitzer 1997). There is, however, some variability in police support across races and ethnicities. These differences are most pronounced in African American and Hispanic communities (Withrow 2006). African Americans and Hispanics consistently report higher rates of dissatisfaction with police when compared with Whites (Ramirez et al. 2000). Although explaining the satisfaction gap between racial and ethnic groups is beyond the scope of this research paper, one source for the disparity may be police differential treatment of minorities during encounters. Minorities believe police are more punitive during their encounters with police (Lundman and Kaufman 2003; Eith and Durose 2011). Beckett and Sasson (2004) noted that perceptions of being singled out impact attitudes of procedural justice and may explain “African Americans’ growing alienation from the institutions of criminal justice” (p. 126).

When looking at the prevalence of actual police-citizen encounters, a disconnect between perceptual and actual disparities becomes apparent. The Bureau of Justice Statistics (BJS) has collected and reported on the racial and ethnic composition of police-citizen encounters every triennial since 1999. In the most recent report titled Contacts between Police and the Public, Eith and Durose (2011) estimated that 16.9 % of the population, 16 or older, will have some sort of face-to-face interaction with police (p. 1). Among the 40.0 million citizens who encountered the police through citizen-and police initiated contacts, 14.2 % were African American and 15.2 % were Hispanic (Eith and Durose 2011, p. 5). These statistics nearly mirror the proportion of racial and ethnic minorities in the general population.

Taken together, it appears as though the quality of interactions between police and racial and ethnic minorities may be the driving force behind differences in support. There are two observations on this issue. First, isolated instances of police misconduct usually have a bigger social impact than expected. For example, media sensationalism surrounding incidents like Rodney King, Abner Louima, and Amadou Diallo has the potential to generalize individual incidents of police misconduct to all law enforcement officials. Despite the isolated nature of events, racially and ethnically motivated events are, to a certain degree, vicariously experienced by all minorities. Second, bias-based policing may be more pronounced than these statistics indicate because contextual nuances are rarely expressed in national surveys. This is explored further in the following section (Walker and Meyers 2000).

Contextualizing Bias-Based Policing

Despite evidence of racial and ethnic neutrality among police, identifying race-and/or ethnicity-based police patterns and practices is a much more difficult task (Eith and Durose 2011). First, race and/or ethnicity are rarely absolute influencers of police behavior. Rather, bias typically manifests itself in other more subtle ways. The importance of race and/or ethnicity varies on a spectrum in which race and/or ethnicity is more or less influential among other exogenous factors (Higgins et al. 2008). Relevant factors have typically been found to fall within the following typologies: environmental, organizational, officer, and situational. Environmental factors suggest that the physical location in which the police-citizen encounter occurs has bearing on police decision-making. Organizational factors prescribe that departmental norms, culture, and structure differentially impact police decision-making. Officer factors charge that the characteristics of the officer, such as the age, race, ethnicity, experience, training, and rank of the officer, may influence decision-making. Situational factors, including citizen demographics and the reason(s) for police interaction, are also said to have pull in police decision-making. Finally, it is important to note that race and/or ethnicity may interact with each of these factors. Research found that minorities were significantly more likely to be arrested than nonminorities (Smith et al. 1984). The impact, however, vanished when the suspects’ demeanor was taken into consideration and concluded that while race and/or ethnicity is influential, it does not have a direct impact on police decision-making. Similarly, other research found that police use significantly more force during encounters with minorities, yet the relationship between race and the use of force dissipated after controlling for neighborhood disadvantage and crime rates (Terrill and Reisig 2003). These examples highlight the complex nature of identifying bias within police decision-making.

The use of race and/or ethnicity may also be motivated by legally accepted practices (Schafer et al. 2006). These practices include drug courier profiles and “race out of place” policing. Drug courier profiling is a set of characteristics, including the race and/or ethnicity of the citizen, thought to be typical among persons carrying illegal drugs. Although highly subjective, police may stop, question, and under some situations search citizens fitting the drug courier profile. In choosing to engage citizens, race and/or ethnicity may be one of many factors contributing to police decision-making. Alternatively, “race out of place” policing indicates that race and/or ethnicity is the sole determining factor for police engagement with citizens. “Race out of place” policing refers to the legal practice of police engaging citizens based on a perceived inconsistency between the racial and/or ethnic identity of the citizen and the racial and/or ethnic composition of the ecological or neighborhood context (Ramirez et al. 2000). Each of these instances demonstrates the importance of distinguishing legal and extralegal factors when identifying race and/or ethnicity-based policing patterns and practices. Given the contextual uniqueness of bias-based policing, the influence of race and/or ethnicity cannot be considered within a vacuum. Rather, many nuanced factors can be said to be important in police decision-making.

Measuring Bias-Based Policing Through Discretionary Decision-Making

Measuring police discretionary decision-making has been a difficult task because racial and ethnic animus is likely to be concealed within police behaviors that have low visibility. Since there is a great deal of difficulty in observing low-visibility police behaviors, the bulk of bias-based policing research has focused on systematic difference in decision-making outcomes. Furthermore, a host of discretionary decision-making outcomes with a variety of analytical approaches have been studied. The three most prominently featured discretionary decision-making points among bias-based policing focus on the use of force, the decision to arrest, and automobile stops. Each of these decision-making points provides measurable aspects to the cognitive processes of police discretionary decision-making.

The capacity to use coercive force is one of the defining features of police work. Racial and ethnic minorities consistently report the use of force against them is excessive. Among the people who contacted the police, only 1.4 % had force threatened or used against them (Eith and Durose 2011). Among threats and the use of force statistics, the most frequently cited type was being “pushed” or “grabbed” (53.5 %) (Eith and Durose 2011, p. 13). Although the threat and use of force is uncommon, African Americans and Hispanics are overrepresented among these instances. In fact, African Americans were more than twice (3.4 %) as likely to have force threatened or used against them than the national average (Eith and Durose 2011, p. 12). African Americans are also overrepresented among deadly force statistics.

Although consequences for the use of force are more immediate to citizens, the consequences of “arrests have a far more pervasive effect on peoples’ lives” (Walker 1993, p. 39). An arrest occurs when a person is taken into custody for the purpose of criminal prosecution or interrogation.

The evidentiary threshold for determining the appropriateness of an arrest is probable cause. Unfortunately for citizens, probable cause does not provide safeguards against arrest harassment or police failure to make an arrest. Further complicating the issue is the unreliability of arrest data because the point at which an individual is arrested is hard to identify and highly influenced by departmental norms. Some jurisdictions report arrests when citizens are formally restrained. Other jurisdictions, however, report arrests when citizens are formally booked. The difference between each reporting threshold represents a “dark figure” of arrests in which bias-based policing may be concealed (Erez 1984). Despite sporadic arrest reporting, official arrest statistics indicate that African Americans are overrepresented. Tillman (1987) estimated that nearly two-thirds (65.5 %) of African American males and one-third of African American females (29.6 %) will be arrested before the age of 30. This rate is nearly two times the rate of White males (33.9 %) and three times the rate of White females (10.1 %) arrested before the age of 30. While there is some indication that race and ethnicity may be an indirect cause for the decision to arrest, the equitable application of the probable cause standard appears to be a myth.

The final discretionary decision-making point measures automobile stop outcomes. Racial profiling, a phenomenon also known as “driving while Black/Brown,” has gained parlance in American vernacular to represent the bias-based treatment patterns and practices of police on minorities during automobile stops (Alpert et al. 2007). Automobile stops present three unique opportunities for measuring the discretionary decision-making of police: stop initiation, searches, and the punitiveness of automobile stop outcomes. Research on automobile stop initiation focuses on the racial and/or ethnic composition of drivers stopped by the police. The bulk of drivers are stopped by the police for traffic enforcement related issues, but more discretionary stops, such as investigatory stops, are also often captured. Among the citizens that encountered the police during automobile stops, 8.4 % were White, 8.8 % were African American, and 9.1 % were Hispanic (Eith and Durose 2011, p. 7). The relative parity of these statistics does not demonstrate the full dynamics of police-citizen automobile stops. Additionally, some researchers indicate that stop initiation poorly represents instances of bias-based policing because police officers can “only determine the race of the driver prior to the stop approximately 30 % of the time” (Alpert et al. 2007, p. 48). In response to these issues, researchers (Fallik and Novak 2012) have suggested that post-stop decision-making provides better indications of the presence of bias.

The second measured outcome from automobile stops concerns the officers’ decision to search the driver, vehicle, passenger(s), or a combination of some or all three entities. African American drivers (12.3 %) were approximately three times more likely to be searched than white drivers (3.9 %) and approximately two times more likely to be searched than Hispanic drivers (5.8 %) (Eith and Durose 2011, p. 10). Despite being searched at a greater rate than Whites, minorities are no more likely to possess illegal contraband (Engel and Calnon 2004; Lundman 2004). Predicting searches becomes even more complicated when race and ethnicity are considered among other exogenous factors. Some researchers have concluded that race and/ or ethnicity was one of numerous search predictors (Williams and Stahl 2008). Alternatively, while race remained a consequential predictor for Smith and Petrocelli (2001), Whites were nearly two and half times more likely to be the subject of consent searches. Consent searches are the most discretionary type of search legally permissible. Others found that the influence of race and/or ethnicity is neutralized once search types or typologies are specified (Fallik and Novak 2012; Schafer et al. 2006). There are eight search types permissible by Supreme Court precedent and police procedures: (1) searches incident to arrest, (2) inventory searches after a vehicle has been impounded, (3) searchers based on the presence of an existing search warrant, (4) probable cause searchers, (5) searches where contraband was discovered in plain view, (6) searches following a drug-sniffing dog alert, (7) “Terry” stop or pat-down searches, and (8) searches subsequent to the driver or passenger(s) given consent. When identifying typologies, each of the search types is typically categorized by the level of discretion required to execute the search, such as highly discretionary or non-discretionary. Finally, some researchers have discovered that race and/or ethnicity is not a significant predictor of searches (Higgins et al. 2008).

Similar nuanced inconsistencies can be said to exist for automobile stop punitiveness. Some research indicates that African Americans are more likely to be treated harshly by police sanctions (Engel and Calnon 2004). Alternatively, a more contextual awareness of less punitive outcomes among police-citizen encounters in that African Americans and Hispanics were less likely to receive punitive sanctions from the police but were more likely to be stopped for highly discretionary reasons, such as equipment violations and failure to signal (Novak 2004). This suggests that police may be using minor traffic violations as a pretextual motive for engaging minority drivers in automobile stops. An additional measure for an automobile stops’ punitiveness considers how long citizens are detained. This body of research lacks consistency in the nature, strength, and sometimes presence of bias-based policing (Withrow 2006).

Contemporary Examples Of Bias-Based Policing

Although most bias-based policing research has primarily focused on African Americans, other racial and ethnic groups have also been the targets of bias-based policing patterns and practices. Arab Americans, persons of Middle Eastern decent, and Muslims became the targets of bias-based policing. After September 11, over 12,000 Arab Americans, persons of Middle Eastern decent, and Muslims were “detained and held indefinitely” on suspicion of terrorism (Nguyen 2005, p. XVII). Furthermore, public opinions for the use of racial and ethnic profiling changed due to the fear society felt toward terrorist and terrorism. Prior to September 11, national opinion polls generally reported opposition to the use of race and/or ethnicity in policing, but after September 11, the majority of society supported the targeting of Arab Americans, persons of Middle Eastern decent, and Muslims in airports (Nguyen 2005) leading one scholar to explain, “after 9/11 the rules changed and everything we had learned about the social costs and ineffectiveness of racial profiling was largely ignored” (Withrow 2006, p. 244).

In response to terrorism threats at home, the US Justice Department began pressuring local and state authorities to enforce and enact immigration laws. Hispanics were particularly victimized by these efforts because of the loose US-Mexican border. Post September 11, political leaders “framed the border as a critical front in the war on terror” (Nguyen 2005, p. 92). For example, Arizona enacted the “Support Our Law Enforcement and Safe Neighborhoods” Act – also known as Senate Bill 1070 – which was designed to discourage illegal immigration in the United States. The bill required that police, during the course of lawful citizen contact, determine the immigration status of the people they encounter when there is reasonable suspicion to believe that the individual is an illegal alien, encouraging police to target Hispanic populations. Although the law never took effect, due to a federal injunction and a Supreme Court decision in 2012, it remains uncertain what the future will hold on this issue.

Research Limitations

Despite researchers’ best efforts to explain the etiology of bias-based policing, two methodological controversies have arisen from this body of literature that are important to consider when drawing conclusions regarding the breadth and depth of bias in policing activities. First, there is some concern for officer self-reports measures of bias-based policing. Concern stems from the fact that officers may be aware of how their accounts of situations are being used and they may fear that accurately reporting some or all of their encounters with citizens may reflect poorly on them or the department. In automobile stops, research indicated that this may result in officers “ghosting’ their data or recording race and ethnicity incorrectly to create the illusion of equitable stop and search procedures” (Williams and Stahl 2008, p. 231). This type of reactivity or Hawthorne effect greatly threatens the external validity of results. Alternatively, others found few signs of officer disengagement in his time-series analyses of encounters once it was announced that data collection would begin (Novak 2004). Given these inconsistencies, researchers should measure officer reactivity when using self-report data.

Second, measuring bias-based policing patterns and practices requires that benchmarks for performance be set. Benchmarks enable researchers to determine if police behavior matches expected decision-making outcomes. Deciding on an appropriate benchmark can be problematic with illusive and transitory populations. Related to automobile stops, “given a group of citizens stopped by the police (the numerator), what could be used as a denominator to conclusively determine whether certain drivers were stopped at a disproportionate rate?” (Schafer et al. 2006, p. 187). Over time, a variety of benchmarks have evolved, including census or modified census population estimates, information from drivers’ licenses, not-at-fault accident data, blind enforcement data, systematic social observations of violator populations (e.g., “rolling surveys”), and internal comparisons. Despite the ecological fallacies found in all of these benchmarks, coverage error – from the benchmark to the expected outcome – is more pronounced under certain research contexts. Bias-based researchers should select the benchmark that minimizes coverage error within the research context while recognizing that all benchmarks have their own limitations.

To address both of these issues, future research must tie theoretical rationales to understandings of police discretionary decision-making by using multiple data sources, ideally coming from a triangulation of sources, including “police reported, citizen-reported, and observer-reported data” (Lundman 2004, p. 343). Single source data explorations are often riddled with invalidity, inconclusiveness, and, worst of all, biases. A triangulation of data sources has the best potential to address each of these methodological issues. Efforts should be coupled with research that examines equitable and lawful policing that results in compliance by citizens (Piquero 2009). The etiology of police discretionary decision-making is best achieved from these methods.

Policy Implications

The improper use of race and/or ethnicity places the legitimacy of all law enforcement agencies in jeopardy, but efforts to curb the abuse of discretion must weigh individual rights against crime control objectives. To control the use of discretionary decision-making, several evidence-based practices have been proposed and implemented (Davis 1969; Gottfredson and Gottfredson 1988; Walker 1993). Four typologies have emerged among these strategies: structure, confinement, checking, and options.

Structural policies are rules, regulations, and guidelines that identify appropriate behaviors. An example of a structural policy geared toward bias-based policing is mandatory reporting. Mandatory reporting policies require that officers document every encounter they have with citizens. Although some mandatory reporting initiatives have been court ordered, many of these policies are agency initiated. By documenting the nature of encounters, departments have developed early intervention systems (EIS) to address issues of bias-based policing (Walker and Katz 2008). EIS is a tool used to identifying individual officers who disparately engage racial and ethnic minorities. These officers are more commonly known as “bad apples.” The use of EIS has been encouraged by the shift toward electronic record keeping.

Confinement policies are rules, regulations, and guidelines that limit police behaviors. Examples of confinement are easily found in Supreme Court decisions. For example, the Supreme Court in Whren v. United States ruled that an officers’ initial decision to engage citizens during automobile stops has to exceed the reasonable suspicion threshold. This ruling attempted to limit officer racial and ethnic pretextual motivations for stopping citizens. Although Whren may have encouraged police to hide behind minor traffic infractions when using race and/or ethnicity inappropriately during automobile stops, it confined police-initiated contacts to the reasonable suspicion standard.

Checking refers to the review of discretionary decision-making which can occur before, during, or after a decision is made. In order to be effective, the person or entity doing the checking must have a direct influence on the decision-making process. An example of a checking policy initiative used to combat bias-based policing is community review boards (CRBs). CRBs vary in the nature of the citizen input, review substance, breadth of the jurisdictional issues addressed, organizational structure, and operating policies. Functionally, CRBs provide external accountability to police community-related issues. Police departments with CRBs have improved community-police relations, and cities with CRBs have higher rates of reporting. Both of these research findings indicate that communities with CRBs have greater confidence in police and the justice process. In essence, CRBs increase the visibility of citizen-reported police misconduct by providing an external review of instances in which an officers’ discretionary decision-making may have gone awry (Walker 2001).

Perhaps the most radical policy suggestion presented in the research literature is the abolition of discretionary. While abolition has typically been focused on court discretionary decision-making, few supporters of abolition contest that police discretionary decision-making should remain unaffected. However, many researchers feel as though abolition is “unrealistic and ill-advised” (Gottfredson and Gottfredson 1988, p. 51). One of the extra option policy initiatives jurisdictions are moving toward would include issuing summons to appear in court, tickets, or fines for possession of person use marijuana. Since drug crimes disproportionately affect minorities, the extra option – other than arrest – reduces the racial and ethnic disproportionality among arrest statistics (Johnson et al. 2008). Providing extra options may not address bias-based policing directly, but it has the ability to shift the disproportionality of discretionary decision-making to less punitive outcomes, thereby reducing the prevalence of more punitive outcomes. Furthermore, it allows researchers to more easily identify instances of bias in more punitive response outcomes.

Finally, although the ability to use coercive force may be the sine qua non of policing, extralegal police aggression – also known as police brutality – is not without safeguards (Holmes and Smith 2008). Each of the aforementioned strategies for reducing discretionary decision-making (i.e., structure, confinement, checking, and options) can be found in recent use of force policy responses. First, police training began incorporating the use of force continuum into their curriculum. The use of force continuum is a structural tool that teaches officers proper responses to escalating threats of violence. Second, the Supreme Court rulings in Tennessee v. Garner (1985) confined the use of deadly force to instances where a reasonable person would have acted on the threat of death or serious physical injury posed by a suspect. The check on the use of force occurs after the fact. When an officer discharges their weapon, departments often require that the officer explain the circumstances that precipitated the discharge of their weapon in a formal report. Supervisors review these reports before determining if it was a “good” or “bad” shot. Finally, police departments nationally began issuing and training officers in the use of nonlethal weapons, such as pepper spray, Tasers, and rubber bullets. Additional options allow police to apply the appropriate amount of force to the level of escalation each situation requires. While each of these typologies uniquely addresses discretionary decision-making, when combined they have reduced the racial and ethnic disparity of persons killed by police (Sherman and Cohn 1986).

Summary

Bias-based policing conjures up raw emotions. It is a complex social question rooted deeply within the historical and structural conditions of America. Acknowledging the existence of bias-based policing potentially compromises the legitimacy of the police in a democratic society. Ignoring or minimizing bias-based policing does not provide relief to targeted populations and does not hold individuals or organizations accountable. Research on the extent and impact of bias-based policing yields inconsistent conclusions. Furthermore, the impact of policies designed to address bias-based policing is difficult to determine. Given the current state of bias-based policing, the most productive conciliatory path is to join others in calling for further examination into the extent to which race and/or ethnicity impacts discretionary decision-making.

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