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Racial Profiling In Policing
Does Racial Profiling Occur in the British Police?
A controversial issue in policing today is the alleged use of racial profiling by police to stop/search citizens. Currently only a small amount of research exists concerning this practice, none of which has been conducted in the UK. This article summarises the major cases that established the existence of racial profiling in the US, identifying with the strengths and weaknesses of the methods used while accounting for the problem that racial profiling characteristics have yet to be identified and conceptualised.
Using data collected from the stop/searches of three different actors, a White male, Asian male and a Black male in six different locations of demographic significance while controlling for suspects demeanour; each stop/search will be analysed to conclude whether racial profiling takes place by the British Police. It can be presupposed that in line with previous police research in both the UK and the US, the actors belonging to the ethnic minority groups, will suffer a higher number of stop/searches.
Does Racial Profiling occur in the British Police?
The purpose of the proposed research is to explore whether racial profiling take places by police officers when stop/searching citizens within the UK. Recent Home Office reports and studies have revealed minority ethnic groups are subjected to heightened rates of stop/search in relation to the ethnic composition of the resident nation. Figures for 2003/2004 showed that the rate of stop/search for black people was nearly six and-a-half times that for whites, while that for Asian people was nearly twice that for whites (Home Office). The proposed research will be carried out using officers on foot patrol in Manchester, a large diverse community where heightened stop/search rates amongst ethnic minorities are apparent (Greater Manchester Police Statistics 2006).
Although current literature exists concerning this problem (Harris, 1999; Weitzer & Tuch, 2002), it has only been reviewed with regards to the US police service where racial profiling was found to take place (Lamberth, 1997). No such literature or studies have been carried out within the UK.
Therefore by researching whether police officers engage in racial profiling when stop/searching citizens, individual officers and their resultant Constabulary will become accountable for the injustice practice and can be disciplined as required. Furthermore the reasoning behind such stop/searches may become apparent. This may in addition, allow for the public opinion and trust of the police to become more favourable, than recent opinion polls have suggested (FitzGerald et al. 2002) and thus allow for a more effective police service (Skogan, 2004).
Background to the Study
One of the most prominent issues facing the police today is the use of race as a criterion in police decision making during discretionary traffic and field stops, often described as racial profiling (Engel, Calnon, & Bernard, 2002). This is especially the case in minority and ethnic communities where police stops have long been viewed as controversial (Weitzer & Tuch, 2002). Although there is a significant literature on the relationship between race, police, and the administration of law (see Chambliss, 1994), recent literature shifts the attention toward the perceived racial profiling problem (see Harris, 1999; Russell, 2001; Weitzer & Tuch, 2002) and methodological discussions concerning measurement difficulties when identifying racial profiling (Ramirez, McDevitt,&Farrell, 2000; Walker, 2001).
Racial profiling is often referred to, as the alleged law enforcement practice of using skin colour as a pretext to stop, question, or search minorities, and can occur during any situation in which minorities are stopped by law enforcement officials (Harris, 1999; Russell, 1999; Smith &Petrocelli, 2001; Walker, 2001).Weitzer and Tuch (2002) recently referred to racial profiling as the “use of race as a key factor in police decisions to stop and interrogate citizens” (p. 435).
Although some form of profiling in law enforcement has long been a practice employed by police (Piliavin & Briar, 1964), it is only over the past few years that it has become a controversial topic in political, academic, and social arenas (Russell, 2001). At the core of the racial profiling issue is the supposition that police target minorities, particularly Blacks, during their normal patrol duties with the belief that minorities are more likely to be guilty of having committed a crime than have Whites (Walker, 2001).
Racial Profiling has increasingly become a topic under scrutiny throughout the democratic world, and it is difficult to overstate the importance of clear conceptualization in this research proposal. A firm understanding of the meaning and parameters of key concepts is necessary for identifying valid and reliable measures and adequately operationalising variables. In the literature to date, there appear to be at least two clearly distinguishable definitions of the term “racial profiling”, a narrow definition and a broad definition.
For the purpose of this research a broad definition of racial profiling will be used; ‘racial profiling occurs when a law enforcement officer uses race or ethnicity as one of several factors in deciding to stop, question, arrest, and/or search someone.' Under the narrow definition race must be the sole issue in deciding to stop/search someone. Stop/search is primarily an investigative power used for the purposes of crime detection or prevention in relation to a specific individual at a specific time (Lustgarten, 2002).
In the UK a stop occurs when a person is asked to account for their actions or movements for investigation purposes. Under section 1 of the Police and Criminal Evidence Act 1984, a constable does not have the right to stop and search ‘a person or vehicle or anything in or on a vehicle unless he has reasonable grounds' for suspicion that stolen property or prohibited articles are being carried. In 2002/2003, there were 869,164 stops and searches under this legislation (Home Office). Amongst them, 118,548 were Black people (14%), 58,831 were Asian people (7%) and 11,468 were of other minority ethnic origin (1%) even though Black and minority ethnic represents only around 7% of the whole population; noticeably the disproportionate use of stop searches on ethnic minorities has become apparent.
Although literature surrounding the problems of stop/searches in the UK exists (Willis, 1983; Smith, 1983; Elliott and Quinn, 2002) no research has been carried out to investigate whether the problems in the heightened number of stop/searches of ethnic minorities is in fact, due to racial profiling taking place by the police. Indeed research suggesting police racism has been carried out (Institute of Race Relations, 1987; Bowling and Phillips, 2002), the most damming of which is the Macpherson Report 1999.
This report identified “Institutional racism and a failure of leadership by senior police officers'' (Macpherson 1999, para 46.1). Macpherson highlighted a general lack of trust and confidence in the police amongst ethnic minorities and noted that the experience of black people over the last 30 years has been that ‘we have been over policed and to a large extent under protected'. It concluded that the over-representation of racial minorities in the national stop and search figures led to the ‘clear core conclusion of racist stereotyping' (Macpherson 1999, para. 6.45).
Evidence of subcultural patterns of racism and machismo began to be uncovered within the British police service during the early 1970s against a background of a racialised moral panic about ‘mugging' (Hall et al. 1978; Rowe 2004). A submission to the Royal Commission on Criminal Procedure by the Institute of Race Relations (1979, 1987) drew attention to the mass stop and search of black people.
This was further publicised due to the Brixton riots in 1981. Lord Scarman criticised the heavy-handed approach to policing in Brixton and highlighted the role of operation ‘‘Swamp 81'', which involved more than 120 officers patrolling the area with the instruction to stop and search anyone that looked ‘‘suspicious''. Over 4 days, 943 people were stopped and 118 were arrested, more than half of whom were black (Bowling and Philips 2002).
Reiner's influential analysis of the police occupational culture (Reiner, 1985) drew on earlier work by Skolnick (1975), to provide a description of what he called the ‘core characteristics of cop culture'. These included racial prejudice, some of which Reiner links to the dominant attitude of the majority towards minorities, and some to the transactional relationships between police officers and the minorities they police against.
Thus, it is apparent that racial prejudice has been identified to exist within the British Police Force, however no studies have identified whether the stop/search of these individuals was down to racial profiling by officers. One study suggested that, relative to the resident population, Asians are eighteen times and African-Caribbean' twenty-seven times more likely to be stopped by the police than whites (Bowling and Phillips 2002). Analysis of Home Office figures suggest that between 1999 and 2003, relative to the resident population, blacks are eight times and Asians two-and-a-half times more likely than whites to be stopped by the police. The same report suggests that in the two years prior to 2003, the number of stops of whites fell 19% while stops of black and Asians each increased by 28% (Institute for Race Relation 2003).
Yet the reasoning behind these disproportional figures has never been properly investigated. The Macpherson report (1999) attributed disproportionate levels of stop and search to “stereotyping”, police racism may be ‘unwitting', but nonetheless is an expression of the subjectivity of officers, albeit culturally shared. For instance, it is suggested that police are generally more suspicious of racial minorities than of white people (FitzGerald and Sibbitt 1997). However, police attention may not be as misplaced as might be supposed. It has long been observed that the ‘strike rate'- the number of arrests arising from stop/searches is approximately equal across racial categories. Stop/searches only lead to arrest, in only 13% of cases in 2003/2004 (Home Office 2005).
In the US where research is more extensive and racial profiling has been identified as police practice; Weitzer (1999, 2000) and Weitzer and Tuch (1999, 2002) investigated the public's perceptions of racial profiling. Their work has moved what we know about perceptions on profiling from anecdotal to objective. Most recently, Weitzer and Tuch (2002) reported results from a 1999 Gallup poll that indicates attitudes toward the police in general and profiling in particular.
In addition, their work suggests that individuals who believed that they had been a victim of racial profiling expressed dissatisfaction with the police in general and reported that profiling was a widespread tactic. In the UK, the “Policing for London” report found that ‘being stopped on foot' emerged as the prime factor amongst a range of ‘police contacts and experiences of crime' associated with negative views of the police (Fitzgerald et al. 2002). In general however, research has identified favourable opinions towards the police (Brandl, Frank, Worden&Bynum, 1994) most indicates difference of opinions along racial and ethical lines (Barkan&Cohn, 1998). Surveys by Flanagan and Vaughn (1995), Huang and Vaughn (1996), and Williams, Thomas, and Singh (1983) all show strong racial differentiation in opinions towards police (cited in Barkan & Cohn, 1998).
While it is important to review literature supporting my proposed research, it is also fundamental to note Jefferson (1993), who persuasively argues that race is only one, relatively minor component explaining why ‘criminalization' (stop/search, and arrest) falls more heavily upon particular sections of the population. Other components and rationale as to the high number of stop/searches of ethnic minorities will be considered as a matter of course.
To date, racial profiling is frequently described as a serious problem that occurs all too often (Cleary, 2000). A Gallup poll conducted in the US reports that 56% of Whites and 77% of Blacks believe that racial profiling is widespread (Newport, 1999 cited in Weitzer & Tuch2002). However, the true extent of racial profiling in society is unknown as little research has been done and demographic information on stops has not routinely collected by police (Cleary, 2000; Harris, 1999b; Ramirez et al. 2000; Walker, 2001). Furthermore, of the research that has been done, estimates are often difficult to interpret and comparisons must be viewed with caution because of differences in the conceptualization and operationalisation of racial profiling.
In the US, where previous studies have been conducted to assess the presence or extent of race-based policing (see Ramirez et al. 2000). The most common has been to compare the proportional representation of racial and ethnic groups in a certain population against the proportional representation of racial and ethnic groups stopped, searched, and/or arrested by police officers within the same population. Within this methodological approach there are at least two data collection strategies.
The first, relies on police officers to report the race and ethnicity of the people they stop/search in an information-gathering mechanism independent of, and in addition to, the routine information-gathering procedures (e.g., citations or activity reports) currently supported or required by their departments. This requires the officer to complete an additional form subsequent to each stop/search (Cordner et al. 2001; Norris et al., 1992; Smith & Petrocelli, 2001). They then compare the racial and ethnic proportions of the individuals stopped/searched against the proportional representation of racial and ethnic groups that existed within the population at the same time (Cox et al. 2001; Meehan&Ponder, 2002; Zingraff et al. 2000). Some of these studies have led to the identification of racial profiling in practice within US police departments.
A 1999 report by David Harris, “Driving While Black: Racial Profiling on Our Nation's Highways” cites numerous accounts of disparate treatment toward minorities by police. One anecdote used was that of Elmo Randolph, an African American dentist, who testified that over a 3-year period, he was stopped 50 times on the New Jersey Turnpike, and asked if he was carrying drugs, and released. None of the stops resulted in the issuance of a citation for any motor vehicle infraction (Kocieniewski, 1999a). This evidence certainly suggests racial profiling to have taken place on numerous occasions against a single member of the population due to his appearance.
Another finding by Harris was that police stop people of colour travelling through predominately White areas because the police believe that people of colour do not “belong” in certain neighbourhoods and may be engaged in criminal activity. This type of profiling was reported by Alvin Penn, the African-American deputy president of the Connecticut State Senate. In 1996, a Trumbull, Connecticut, police officer stopped Penn as he drove his van through this predominately White suburban town.
After reviewing Penn's license and registration, the officer asked Penn if he knew which town he was in (Bridgeport, the state's largest city, where Blacks and Latinos comprise 75 percent of the population, borders Trumbull, which is 98 percent White). Harris (1999b) as a result argued that racial profiling was institutionalized in US law enforcement in the mid-1980s through Operation Pipeline, a Drug Enforcement Agency training program on using traffic violations as pretexts for stopping persons who fit drug courier profiles, especially on roads known as drug “pipelines.”
One officer testified that he focused on “rented cars from south Florida, driven by blacks or Latinos” (Webb, 1999, p. 126) which certainly suggests a racial bias but is nevertheless true to the original Operation Pipeline drug courier profile. Although this small sample of anecdotal evidence does not prove that police officers actively engage in racial profiling, it is representative of thousands of personal stories catalogued throughout the US.
As a result of the growing body of individual accounts of racial profiling, scholars began examining the relationship between police stop/search practices and racial characteristics of individual drivers using empirical data. The majority of empirical research collected to date has been used in expert testimony accompanying lawsuits. Wilkins v. Maryland State Police(1993) was one of the first cases to introduce empirical evidence of racial profiling into the court record. Dr. John Lamberth, a professor of psychology at Temple University, conducted an analysis of police searches along I–95 in Maryland.
The research took place following a Maryland trooper stopping Robert Wilkins's rented car as the family returned from a funeral in Chicago. Over Wilkins's objections, the trooper ordered occupants out of the car, to stand on the side of the highway for an extended period of time, at night, in the rain, until the arrival of a unit with a drug-sniffing dog. No drugs or violations had taken place an as a result Wilkins sued the Maryland State Police for violation of civil rights (State of New Jersey v.Pedro Soto, et al. 1996 cited in).
Lamberth (1996) analyzed Maryland State Police stop/search data as part of the settlement agreement, comparing those findings to another rolling survey of the I-95 highway user and law-violators populations. Using data released by Maryland State Police pursuant to the settlement, Lamberth compared the population of people searched and arrested with those violating traffic laws on Maryland highways. Race could be determined for 5,555 of the 5,741 driver's observed (96.8%), and 5,354 drivers (93%) were observed violating motor vehicle laws (Lamberth, 1996).
Lamberth's definition of “violation” is controversial but has a supportable rationale. His assistants drove at the posted speed limit (55 miles per hour or 65 miles per hour, in different areas), counting the drivers who passed them as “violators”. His violator survey indicated that 74.7 percent of speeders were White, while 17.5 percent were Black. In contrast, according to State Police data, Blacks constituted 79.2 percent of the drivers searched; this proposed that Blacks were 4.85 times as likely as Whites to be pulled over by New Jersey troopers. Lamberth concluded that the data revealed “dramatic and highly statistically significant disparities between the percentage of Black I–95 motorists legitimately subject to stop by the Maryland State Police and the percentage of Black motorists detained and searched by troopers on this roadway.”
A further study by Spitzer(1999) gauged stop/frisk rates according to the racial breakdown in New York City. To accomplish this task, researchers analyzed the UF-250 forms from the NYPD. These forms are detailed reports that every officer must complete for each stop made during their shifts.
The reports include a detailed description of the stop, incorporating characteristics such as the race of the person stopped, the reason he or she was stopped, the time the stop was made, where the stop occurred, and who the officer was that made the stop. Analysis of the UF-250s between January 1, 1998 and April 1, 1999 showed that Blacks comprised 50.6% and Hispanics 33.0% of all those stopped or frisked, although they only represented 25.6% and 23.7% of the New York City population, respectively. Conversely, Whites, who comprise 43.4% of the New York City population only represented 12% of those stopped or frisked. Hence, Blacks were 6 times more likely and Hispanics 4 times more likely to be stopped or frisked in New York City than were Whites. Further research at the precinct level showed that, of the 75 precincts that form the NYPD, only 1 of the 10 precincts with the highest stop rates had a “majority” of White residents, whereas all but 2 were in the lowest 10 precincts (for stop rates) (Spitzer, 1999).
The Spitzer (1999) report also gauged whether stop/frisk differences would mediate after controlling for the crime rate according to race. The data revealed that after holding the race-specific precinct crime rates and precinct population composition by race constant, the Black stop/arrest ratio (1.54) was 23% more than the White ratio (1.24). The Hispanic stop/ arrest ratio of 1.72 was 39% more than the White stop/arrest ratio. The researchers reported that the crime rate in New York City could not substantially account for the disparities in stop rates between Blacks, Hispanics, and Whites (Spitzer, 1999). Although this study differed in method from previous research conducted it still produced the same outcome suggesting racial profiling occurred within the police departments.
However, despite empirical evidence proposing racial profiling by police officers, statewide studies in Connecticut, Texas, and Washington all failed to produce consistent findings of substantial and systematic disparity of stops with respect to the race or ethnicity of the person (Cox, Pease, Miller, & Tyson, 2001; Texas Department of Public Safety, 2000; Washington State Patrol , 2001).
In a study of the Richmond, Virginia Police Department, Smith and Petrocelli (2001) found that in a comparison of the percentages of those being stopped to that of the driving eligible population, Blacks were 46% more likely to be stopped than Whites. They reported that of the 2,673 motorists stopped, Black motorists comprised over two thirds while only making up 52% of the driving eligible population. Similar to the 1997 Lamberth study, the Richmond Police searched minorities 71.0% of the time compared to only 28.9% of Whites. Petrocelli, Piquero, and Smith (2003) also used the Richmond data to examine racial profiling at the census-tract level by studying the factors related to police stop/searches.
Their analysis indicated that the area crime rate was the only significant factor influencing police stop patterns. In other words, police stops were primarily a function of the crime rates of particular patrolling areas in Richmond (Petrocelli et al., 2003). Home Office research in the UK had similar findings. Miller (2000) found a strong positive correlation between locations where stop and search was greatest and crime was highest. Walker's (2001) study of the San Jose Police Departments' data on traffic stops yielded similar results to prior research, suggesting race was the significant factor in determining those stop/searched.
As a result of previous literature suggesting racial profiling occurs within the US police force, I advocate that the research proposed will most certainly be of importance to the UK and future policing. Within the UK literature by Norris et al. (1992) found not only that young blacks were stopped very much more frequently than other racial groups, but that these stops were made on a more speculative basis. FitzGerald and Hough found that being black was a good predictor for being stopped on foot and in a car, along with being under 30 years old and male (FitzGerald et al.2002).
In 2002 research was commissioned by the Thames Valley Police. Conducted in Reading and Slough, the survey was part of a larger study that included in-depth interviews with police officers of different ranks plus analysis of police records of stop/searches that had occurred (detailed in Qureshi 2005). The reason for commissioning the research was official anxiety at the apparent disproportionality between the racial composition of the residential population and the profile of those stop/searched in these two police divisions. Fortuitously, the racial composition of these two towns exhibited vast differences.
Reading has a mixed ethnic profile that includes a substantial proportion of black people, whereas Slough has a distinctively large Asian minority; the differences between these two towns offered the opportunity to examine any differences in patterns of ‘availability' and police stop/search practices. The research methods included direct observation of the ‘available population', analysis of the stop/search database, and interviews with officers about recent stop and searches that they had conducted. When results were compared to the resident populations of each division (2001 Census), police stop and search figures certainly suggest significant disproportionality in both locations.
However, when we consider the ‘available population', we find a rather different picture. White people are much less evident amongst those available to be stopped and searched in both towns, especially in Slough. Black and Asian people are marginally, but crucially, more abundant in Reading and far more numerous in Slough. The result's show that, in Reading, the pattern of stop/search reflects pretty closely the available population, whilst in Slough, there is significant disproportionality, with white people being over-represented amongst those stopped/searched and Asians underrepresented.
Whilst the literature analysed suggests that racial profiling may take place, it is important to consider the alternative rationale behind the higher number of stops and the methodological problems in achieving the data to analyse, chief amongst them is the reliance upon official figures of stop/searches. There is good reason to believe that these figures underestimate the actual number of stop/searches conducted by police officers (Quinton et al. 2000; Smith and Gray 1983).
Given that the issue of racial profiling at its essence involves the use of police discretion, it's important to recognize the potential role that characteristics of a particular neighbourhood or police district play in the decision to make a stop/search. In the UK the use of reasonable suspicion is often down to the discretion of the individual officer. Smith and Gray (1983) in a study proceeding PACE1984, examined the application of ‘reasonable suspicion'.
They observed that, when carrying out stop/searches, police officers rely predominantly on their own instincts, which could cause elements of race and class bias. It was Smith (1986) who positioned that in order to understand police behaviour, one must consider the environment in which police operate. The exercise of discretion occurs outside the supervisory purview of the police station (Bowling et al., 2004). This can provide the opportunity for police officers to exercise their discretionary powers based upon their own individual prejudices (Kleining, 1996).
This is apparent in research identifying police stop/search practices being driven by; age, class, gender and race (Skogan, 1990 and 1994; Clancy et al. 2001). Hence, racial profiling could be implied by officers due to their individual prejudices without being an actual ‘feature' of the police service as a whole. It may also stem from supervisor guidelines and differences in training and (Verniero & Zoubek, 1999 cited in Reitzel & Piquero2006)).
Several studies have found the ethnic composition of the available population differs remarkably to that of the residential population, and that this difference may go a long way in accounting for the apparent disproportionate use of stop/searches against people from minority communities (Miller et al. 2000; Waddington et al. 2004). One interest in all the literature concerns the baseline (Smith et al., 2000; Smith& Petrocelli, 2001; Thacher, 2001; Walker, 2001).
Currently, there is no clear agreement in regard to what a proper baseline should be in measuring racial profiling (Smith & Petrocelli, 2001; Thacher, 2001). Zingraff et al. (2000) reported that using statewide data such as census figures or number of licensed drivers in the state or a particular region is problematic because it cannot account for the distribution of people in a locale at a specific time and it does not account for differences in patrolling. Measures used in previous studies also fail to account for non-residents travelling or residing in the area under study, which itself impacts baseline measures (Cox et al 2001).
One supposition behind the higher number of stop/searches of ethnic minorities is that different racial or ethnic groups place themselves at greater or lesser risk of being stopped by the police through their differential use of public space. FitzGerald speculates that young Asian men increasingly seek to escape the confines of the family home, finding refuge amongst their companions in public places.
They disproportionately occupy public spaces as groups that sometimes engage in the kind of rowdiness that attracts police attention and are vulnerable to being stop/searched and arrested for possession of small quantities of cannabis (FitzGerald 1999). Bowling and Phillips (2001) also identify the racialised nature of ‘availability'. Racial patterning of unemployment, homelessness and school exclusion may be reflected in the composition of the ‘available population' and, even if police proportionately select from amongst this ‘available population', it remains the case that racial minorities may be more exposed to stop/searches. Hence class not race may be a cause of the higher rates of stop/search (Don et al. 2004).
The use of the residential population as the comparative basis for these statistics is problematic, not least because different sections of the population may use public space differently. It has been noted that the elderly are increasingly disinclined to venture onto the streets as pedestrians because of their fear of crime (Chivite-Matthews and Maggs 2002). Women too seem dissuaded from using the streets, especially after dark (Gilchrist et al. 1998; Mirrlees-Black et al. 1996). Hence, the overwhelming disproportionality in stop/searches experienced by young men of all racial groups and ethnic identities may simply attest to their greater availability for being stop/searched (Home Office). Rather than any particular selectivity on the part of the police. It appears necessary, therefore, to compare stop/search figures, not with the racial composition of the resident population, but with the composition of those available for being stopped because they frequent public places.
While the literature clearly presents empirical evidence of stop/searches of ethnic minorities at a higher level in both the UK and the US, it fails to properly account for the reasoning behind these high rates or use an accurate baseline of population to compare the results against. As a result, it remains a difficult task to construct reliable estimates of the unique individual and area-specific factors that contribute to explanation of police decision making and racial profiling. Engel et al. (2002) reported that non-White suspects may be more disrespectful toward police, which could be linked with higher arrest rates for minorities, especially young Black males.
On a related note no published racial profiling study has included information on citizen demeanour, yet a longstanding body of literature points to the importance of suspect demeanour on police decision making (Klinger, 1994; Lundman, 1996; Worden, Shepard, &Mastrofski, 1996). The concept of demeanour as a result will also be analysed in the proposed research. This will allow a greater understanding of whether racial profiling occurs in the British Police Force or if the high level of stop/searches is down to other rationale.
In the process of conceptualising racial profiling, it is important to consider the unit of analysis and the possibility of effects at different levels of aggregation. A better understanding of the heightened stop/search rates of minorities in the UK will be achieved through careful attention to the process of stop/search by individual police officers. Although areas with higher crime rates may experience higher rates of stop/searches, it should not effect the number of stop/searches on ethnic minorities. The Macpherson report placed an emphasis on improved monitoring and administrative controls over the use of such powers, including a specific recommendation calling for a requirement that police officers must record all ‘‘stops'' as well as ‘‘stops and searches'' made under any legislative provision (Recommendation 61). The record included the reason for the stop, the outcome, and the self-defined ethnicity of the person stopped.
As well as being given to the person who is subject to the stop. The Stephen Lawrence Inquiry recommended that stop/search records should be monitored and analysed by police services, police authorities and reviewed by Her Majesty's Inspectorate of Constabulary during inspections. In doing this the perfect template was established for recording all aspects of stop/searches, and as a result research can transpire as to whether racial profiling takes place by police officers. In the US literature reviewed, racial profiling was found to be apparent in car stops.
However, a rationale behind this process may be that profiling of the type of car driven, which Sollund (2006) describes as ‘car profiling' took place and not ‘racial profiling'. What is apparent is the racial categories used in police recording in the US, varied across agencies (Cleary, 2000; Ramirez et. al 2000.) and other important details including location and time failed to be recorded. Hence, although present research consistently suggests such practices to occur. It is necessary to research the practice in full controlling certain variables and assessing each situation individually in relation to the officer.
In order to investigate the central issues of the proposed research I intend to use a quasi-experimental approach. This test is most suited to the design as itis not logistically feasiblenor ethical toconduct a randomized, controlledtrial given the research topic. In quasi-experimentation, the researcher has to enumerate alternative explanations one by one, decide which are plausible, and then use logic, design, and measurement to assess whether each one is operating in a way that might explain any observed effect (Shadish, Cook & Campbell, 2002).
In the proposed research I will use three comparable citizens from one community that are as similar as possible except for their race; this will allow a fair comparison of the stop/searched persons' to the other's. The design of the experiment will include three levels of independent variable; race, location and demeanour. Collectively I will analyse the effects these have in the police officer's decision to stop/search. The first independent variable is a between groups factor, whereby one Black, one Asian and one White male will be used. The reason for using male's in this type of research is because they are more representative of the available population and represent a higher number of stop/searches in previous Home Office statistics.
It is fundamental to the research to match the subjects with similar characteristics (such as height, clothes, physical characteristics).This will ensure that any difference in effects which are observed will be due to race and not the controlled for characteristics. All the subjects chosen are professional actors aged 19, standing 5ft 10 tall with a medium build and dark hair. The reason for choosing subjects with these characteristics is because they fit in with what White (2003) identified as the most common youth appearance. They will all wear the same clothes and due to their profession should be able to act in an appropriate co-operative way and un-cooperative when required to. All subjects were born and reside in Manchester with no criminal record, thus no one male should be stop/searched more than the others.
The location of the research has been determined using crime and demographic statistics within the South Manchester area, provided by Greater Manchester Police (GMP). The reason for using South Manchester to carry out this research is due to its vast diverse community and differing crime rates. The areas identified will be areas where racial demographics are equal such as Northenden; where there is approximately the same number of Whites, Blacks and Asians in the community. Rusholme will be the area used for the densely populated Asian area, Hulme for the predominantly populated Black area and Chorlton for the area with a higher proportion of White citizens.
Finally Didsbury will be used as an area of low crime rate, while Wythenshawe will be utilized as the high crime rate area. Time-sampling will be employed at the chosen locations to identify when police officers are most likely to be on foot patrol and engaging in stop/searches of citizens. Relevant information will also be provided by GMP regarding shift patterns and shift locations of officers. Incidentally, previous studies reveal when lighting levels are at their worst police stop and search activity reaches its peak. It may thus be expected that minorities are more likely to be stopped during the day because clear observation of race can be more difficult at night. Walker (2001) indicated, “It is undoubtedly much more difficult to identify the race or ethnicity of people at night than during the day”. It is for this reason that the research project will begin in June 2007 where sunset is later, but allowing for the ‘available population' to become more vast.
There will be approximately 36 stop/searches as part of the research, each of which will be carried out throughout a two month period. However, it cannot be guaranteed the actor will be approached and stopped/searched within this period as police do not stop and search every individual they see. The design will require all three actors to stand at a given location at the same time on a given day. On the following day, the actors will rotate to stand at different locations. This design will continue until all three actors have been placed in all six of the locations.
Following this, actors will return to their initial location and perform the same process with a negative attitude towards the police. The time of day will be controlled for. One of the problems with this study is that it cannot be guaranteed that every individual will be stop/searched in each location, and therefore data will not be collected on this event. Should this be the case, then we will assume that there is no racial prejudice towards this individual's race. Bearing in mind each actor may be stopped/searched 12 times, GMP supervision has informed their communication that details of the individual's stops on the Police National Computer (PNC) will go unrecorded. If each stop was recorded on the PNC, it may give officers ‘reasonable suspicion' to stop/search the actor due to their increased volume of searches, appearing when officers radio through to communication.
Existing studies claiming racial profiling to be the sole cause of the higher number of stop/searches for ethnic minorities does not contain information on individual characteristics, specifically suspect-level data on demeanour (Worden & Shepard, 1996). Given the importance of suspect antagonism in determining police decision-making (Klinger, 1994; Smith, 1986), it is an essential element to incorporate into the research to gain a more reliable understanding of the topic.
Demeanour is highly subjective, and is a within subject factor because all participants will be possessing or not possessing a co-operative attitude to the police in all of the locations. The use of professional actors in changing their demeanour will be limited due to them using certain rehearsed lines to respond to officer's requests and action's. Following the research if results suggest demeanour is a factor in stop/searches it will become important to evaluate the measure used. The measure of demeanour used in this proposal has never been validated and therefore it is only the research and actor's perception of what constitutes demeanour. To advance future research an agreed measure of demeanour would be used.
The use of quality CCTV including sound, will be placed in all locations allowing for facial expressions and body language to be monitored and the nature of the exchange as well as the tone(demeanour) to be taken note of. Although it may be possible for a separate observer to record information about the nature of the interaction being monitored and scrutinized it may lead to the disengagement of interacting with the public or change the behaviour to appease the persons observing them (Ramirez et al., 2000). Officers may be tempted to engage in fewer encounters or at least fewer encounters with racial and ethnic minorities. Hence, the cameras used will clearly be on display, but carefully controlled while the stop/search or encounter is taking place to make sure all actors respond in the same way.
The use of demeanour will allow assumptions to be made regarding race and the likelihood of being stopped/searched. It would be expected if in each area when a negative attitude to the police is added, a stop/search may be more likely. However, if results suggest in the densely populated white area when all subjects have a negative attitude to the police that only the Black or just the Black and Asian male get stopped/searched then racial profiling is apparent in police practice.
GMP have been contacted and the Chief Constable has given permission for this study to go ahead, providing results are presented before being published. Although the Chief Superintendent of the South Division has been informed about the study he will not be informing officers, but ensures no disciplinary action will be taken as a direct result of the study.
The data used, will be compiled directly from the actors who will be given a copy of their stop/search forms in each location, if applicable(See Appendix A). This form is of significant relevance to the study as it contains all the relevant information needed in helping to analyse whether a stop/search was carried out on grounds of race or alternatively the reasons given for the stop, and whether these reasons are valid. It will also allow the police to identify which officers may be engaging in racial profiling and hold them to account.
This has never been achieved in past studies as they have normally analysed past data, and not developed a process to obtain the data as this research proposes to do. Of particular importance will be the officer defined ethnicity and self defined ethnicity(See Appendix B). These will be compared to see if officers perceive the subject's race differently, than the subject's actual race. This will allow different officers characteristics and possible prejudices to be identified. Only Smith and Petrocelli (2001) have examined officer characteristics as they relate to propensity to stop minorities, and they reported that female officers were significantly more likely to stop minorities than male officers. They found officer race and length of service to be unrelated to race of traffic suspects. Despite this research involving traffic stops where the underlying cause may have been “car profiling”, these apparent observed relationships will be re-examined in the analysis of results derived from the research proposed.
If police posses no prejudice, one would expect the results to demonstrate a higher number of stop/searches of each individual in the area where their race is dominant i.e.more white stop/searches in Chorlton. However it is likely that the Black and Asian actors are more likely to be stopped in a predominantly White area, than the White actor is in the predominantly ethnic areas. Different theories suggest this is due to crime rates, however this research will add to the proposition that racial profiling occurs.
One problem that may occur is through the use of different officers; however this could also have a positive effect on the study. Although officers are individuals and make decisions using discretion, it enable's ‘bias' officers to be identified and future practices to be scrutinised.
Once all stop/search forms are collated, answers will be coded and subjected to quantitative forms of data analysis. Analytical software called SPSS will be used for quantitative analysis employing measures of association and tests of significance to make comparisons between race, location, demeanour and officers reasoning for the outcomes. Quantitative analysis will also be used to make systematic comparisons between officer's perceptions of race and self-defined ethnicity.
This form of analysis will allow for an understanding of whether race effect's the likelihood of being stop/searched, or to determine whether it is due to another controlled for factor such as demeanour, which will be carefully controlled for by watching the CCTV. Previous research reveals, that despite very little difference between how racial groups encounter the police, blacks are still more hostile, reflecting their generalised hostility to the police (Tuck & Southgate 1981; Skogan 1994 cited in Brandl et al. 1994) Hence it is acclaimed that it's methodologically unsound to treat accusations of racial prejudice and discrimination as evidence of it, as some researchers are prone to do (Choongh 1997), thus signifying the importance of analysing the data without bias.
Analysis of racial profiling data has seldom produced unequivocal results. Although analysis has revealed disproportions in stop rates, data has rarely revealed whether or not an agency is engaged in systematic racial profiling. Given methodological challenges, such as benchmarking, alternative interpretations will exist even when racial disparities in stops appear pronounced. Even when disparities are not evident, some may feel that that racial profiling still exists and that the data either masks the problem or is misleading. Although this study is done on a very small scale, it can be repeated anywhere in the country to identify racial profiling within any police force. It has previously been suggested that monitoring frequent stoppers, particularly those officers who frequently stop citizens from ethnic minority groups, could be a productive means of monitoring proportionality in stops (MVA and Miller 2000)
Implementing a data collection system and analysing it more thoroughly sends a clear message to the entire police community, as well as to the larger community, that racial profiling is inconsistent with effective policing and equal protection. When implemented properly, this system can help shape and develop a training program to educate officers about the conscious and subconscious use of racial and ethnic stereotypes and promote courteous and respectful police-citizen encounters.
When implemented as part of a comprehensive early warning system, data collection processes can identify potential police misconduct and deter it. It can also improve police productivity by enabling police to assess and study the most effective stop/search practices, and provide police with information about the types of stops being made by officers. Arguably one of the most important factors regarding this study is it will enable police and the community to assess the quantity and quality of police-citizen encounters.
Racial Profiling is extremely hard to prove. This research although on a small scale, will only further the knowledge of unjust police practices and actions in the UK with regards to race. A large scale study would certainly further develop the understanding of racial profiling, however due to it's complexity it is necessary to start with a small scale study within the UK to identify if the rationale is valid.
The results of this research will be presented to GMP who may wish to investigate this matter further, as the results may well have policy implications. Once the results have been acknowledged by GMP and dealt with they will be publicised in national and international journals in the area of criminology and police research.
Barkan, S., & Cohn, S. (1998). Racial prejudice and support by Whites for police use of
Force: A research note. Justice Quarterly. Vol 4, pp743-753.
Brandl, S., Frank, J., Worden, R., & Bynum, T. (1994). Global and specific attitudes toward the police: Disentangling the relationship. Justice Quarterly, 11, pp119-134.
Bowling, B. and C. Phillips (2002) ‘Racism, Crime and Justice'. Edinburgh:
Buerger, M. & Farrel, A (2002) The evidence of Racial Profiling: Interpreting Documented and Unofficial Sources. Police Quarterly. Vol 5, No.3, pp272-305
Chambliss, W. (1994). Policing the ghetto underclass: The politics of law and law enforcement. Social Problems. Vol.41, pp177-194.
Cox, S. M., Pease, S. E., Miller, D. S., & Tyson, C. B. (2001). Interim report of traffic stops statistics for the state of Connecticut. Rocky Hill, CT: Division of Criminal Justice
Elliott, C., and Quinn, F. (2002) The English Legal System (4th Edition). Essex: Pearson Educational Limited.
Engel, R. S., Calnon, J. M., & Bernard, T. J. (2002). Theory and racial profiling: Shortcomings and future directions in research. Justice Quarterly. Vol.19, pp249-274.
Fitzgerald, M., Hough, M., Joseph, I., and Qureshi, T. (2002). Policing for London. Devon: Willan Press.
Greater Manchester Police
Retrieved April 3, 2007, from http://www.gmp.police.uk/mainsite/pages/Stats.html
Harris, D. (1999, December). The stories, the statistics, and the law: Why “driving while
Black” matters. Minnesota Law Review, Vol.84, pp265-326.
Home Office Statistics.
Retrieved May 9, 2007, from www.homeoffice.gov.uk/rds/policingdc.html
Institute of Race Relations.
Retrieved April 21, 2007, from http://www.irr.org.uk/publication/index.html
Lamberth, J. D. (1997). Report of John Lamberth, Ph.D. American Civil Liberties Union. Retrieved April 25, 2007, from www.aclu.org/court/lamberth.html
Macpherson, W. (1999). The Stephen Lawrence Inquiry: Cmd 4262-I. London: Home Office
Miller, J. (2000) Profiling Populations available for Stops and Searches. Police Research Series Paper 131. London: Home Office.
Petrocelli, M., Piquero, A. R.,& Smith, M. (2003). Conflict theory and racial profiling: An empirical analysis of police traffic stop data. Journal of Criminal Justice, Vol.31, pp1-11.
Qureshi, F. A. (2005). ‘The Impact of Extended Police Stop and Search Powers under the Criminal Justice Act 2003: An Evaluation of a Southern Town' Paper presented to the British Society of Criminology, University of Leeds, July 2005.
Ramirez, D., McDevitt, J.,&Farrell, A. (2000). A resource guide on racial profiling data collection systems: Promising practices and lessons learned. Washington,DC: U.S. Department of Justice.
Reiner, R (1985). ‘The politics of the police'. Brighton : Wheatsheaf.
Reitzel, J. & Piquero, A. (2006) Does it exist? Studying citizens' Attitudes of Racial Profiling. Police Quarterly. Vol.9, No.2, pp.161-183
Russell, K. K. (2001). Racial profiling: A status report of the legal, legislative, and empirical literature. Rutgers Race & the Law Review, Vol.3, pp.61-81.
Smith, D. J. (1983), A Survey of Police Officers. London: Policy Studies Institute
Smith, M., & Petrocelli, M. (2001). Racial profiling?: A multivariate analysis of police traffic stop data. Police Quarterly, Vol. 4(1), pp.4– 27.
Spitzer, E. (1999). The New York City Police Department's “stop and frisk” practices: A
report to the people of the state of New York from the office of the attorney general.
Albany, NY: New York Attorney General's Office.
Waddington, P.A.J., K. Stenson and D. Don. (2004) ‘In Proportion: Race, and police stop and search' British Journal of Criminology, 44, pp889-914
Walker, S. (2001). Searching for the denominator: Problems with police traffic stop data and an early warning system solution. Justice Research Policy, Vol.3, pp.63-95.
Webb, V. J., & Marshall, C. E. (1999). The relative importance of race and ethnicity on citizen attitudes toward the police. American Journal of Police, Vol.14, pp.45-166.
Weitzer, R.,&Tuch, S. (2002). Perceptions of racial profiling: Race, class, and personal experience. Criminology, 40, pp.435-456.
Zingraff, M., Mason, H. M., Smith,W., Tomaskovic-Devey, D.,Warren, P., McMurray, H., et al. (2000). Evaluating North Carolina state highway patrol data: Citations, warnings, and searches in 1998. Retrieved February 25 2007, from www.nccrimecontrol.org/shp/ncshpreport.html
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