Appendices

 

Dr. Scot Wortley

Centre for Criminology and Sociolegal Studies

University of Toronto

Submitted to the Ontario Human Rights Commission September 2021

ISBN: 978-1-4868-5400-4 (Print), 978-1-4868-5401-1 (PDF), © 2021, Government of Ontario

 

Introduction

Canada is one of the world’s most active immigrant-receiving nations, and has received international praise for its official policies of multiculturalism and racial inclusion. An argument could be made that Canada’s reputation for racial tolerance is well deserved – especially when race relations in Canada are compared to the situations in the United States and some parts of Europe. A closer examination of the historical record, however, reveals that racial bias and discrimination have been serious issues within Canadian society – particularly with respect to the operation of criminal justice system. Indeed, a number of scholars have documented that allegations of racial bias with respect to law creation, policing, the criminal courts and corrections have existed in Canada since before confederation (see for example Perry 2011; Walker 2010; Henry and Tator 2005; Chan and Mirchandi 2001; Mosher 1998). For at least the past 60 years, racial bias with respect to police stop, question and search behaviours – and the official documentation of these encounters through the practice of carding or street checks – has emerged as a particularly controversial issue. Canada’s Black, Indigenous and Muslim communities have been especially vocal in their complaints about what has come to be known as “racial profiling” or “racially biased policing.”

Historically, allegations of racial bias have been denied – often vehemently – by Canada’s major police services and police associations (see Tanovich 2006; Tator and Henry 2006; Wortley and Owusu-Bempah 2011a). Ultimately, some high-ranking police officials, including former Toronto Police Chief Bill Blair, publicly admitted that racially biased policing may be an isolated problem within some communities or among some officers. However, police leaders have rarely discussed the consequences that systemic, racially biased police practices have had on racialized communities. Furthermore, until recently, few police services committed to the long-term study of this phenomenon (see James 2005).

This may be changing. For example, in December 2018, following allegations of anti-Black racism in law enforcement, former TPS Chief Mark Saunders acknowledged that anti-Black racism is a “reality” and that public criticism has been “more than fair” (CBC News 2018). Similarly, in August 2020, TPS Interim Chief Jim Ramer recognized racial bias as an issue and stated that one of his top priorities would be to identify and eliminate systemic anti-Black racism in the Toronto Police Service (Goodfield 2020). Finally, the Toronto Police Services Board recently adopted a policy that will enable the collection of race-based data on police-civilian encounters. As stated by then-Chief Saunders, “At the end of the day, when we get this right, what we’ll be able to do is identify and monitor potential systemic racism” (Doucette 2019).

The purpose of this report is to review empirical research on anti-Black racial profiling involving the Toronto Police Service. The Toronto Police Service has been at the heart

of the Canadian racial profiling debate (Commission on Systemic Racism in the Ontario Criminal Justice System 1994). The report begins by reviewing various definitional issues related to the concept – including the concept of “carding” as described by Justice Michael Tulloch in his recent report (Tulloch 2019). The discussion of definitional issues is followed by a theoretical discussion of the possible causes of racially biased policing. This section will describe the various explanations that have been used to account for the existence of racial profiling in police stop and search practices including explicit (conscious) and implicit (unconscious) bias, racial stereotyping, actuarial/ statistical discrimination and institutional/ systemic practices. It will be argued that the research literature strongly suggests that racially biased policing can exist in the absence of individualized, overt racism or racial malice. One does not have to prove that individual police officers are explicitly or overtly racist to prove that racial profiling exists.

The following section of the report will explore research – conducted over the past 25 years – that has attempted to document the existence of racial profiling involving the Toronto Police Service and the extent that biased policing practices impact Toronto’s racialized communities. The report explores the various research methodologies that have been used to document racial profiling in Toronto, including qualitative interviews, general population surveys and official police-generated data (including data on carding or street checks). This section highlights research evidence that demonstrates that racial profiling has existed – and continues to exist – in Toronto and that TPS stop, question and search practices (SQS) have had a hugely disproportionate impact on Toronto’s Black community.[1]

The report then turns to a discussion of the possible benefits of police “street checks”

and police “stop, question and search” (SQS) practices. I first review police arguments that street checks, SQS practices and other forms of proactive street policing are valuable law enforcement tools that help reduce crime. This section will demonstrate that the empirical evidence supporting this thesis is highly contested. Overall, while there is research to suggest that police stop, question and search practices can identify offenders and reduce crime in some contexts, evidence also suggests that these crime reduction effects

are quite small, inconsistent, short-term and limited to specific neighbourhoods or communities. In general, the bulk of the research suggests that SQS practices are a highly inefficient police tactic.

This following section of the report reviews research that has documented the impact of racially disproportionate policing – including street checks – on racialized individuals and communities. These consequences include: 1) mental health problems; 2) lack of trust or faith in the police and broader criminal justice system; 3) racial disparities within the criminal justice system; and 4) blocked educational and employment opportunities. This section of the report will also discuss the issue of data retention. It will be maintained that the retention of carding or street check data may continue to have an adverse impact on the individuals included in police databases. Furthermore, since Black citizens are greatly over-represented within the street check data, the retention of data will likely have a disproportionate impact on members of the Black community. The report concludes that the documented consequences of these street check practices significantly outweigh the potential benefits.

The last section of the report provides a brief discussion of policy implications. It will be maintained that a variety of strategies – including improved screening of police recruits, the recruitment and retention of racialized officers, anti-bias training, improved regulations and guidelines for police stops and improved supervision and monitoring of front-line officers – are required to reduce racial disparities in police stop, question and search practices and reduce the negative impact that biased policing has on racialized communities. It will also be argued that the improved collection of race-based data is required to evaluate the impact of anti-bias initiatives. It will be argued that improved data collection and dissemination will also increase transparency, improve police accountability, and help improve public confidence in the police and broader justice system.

 

Definitional issues

Over the past three decades, the term racial profiling has become part of the popular lexicon. The term has appeared frequently in everything from academic manuscripts, government reports and news coverage to popular music, movies and television. The term racial profiling has also been used to describe various phenomena including the behaviour of customs and immigration officers, judges, lawyers, private security personnel, teachers, medical professionals, public servants, and members of the general public.

The Ontario Human Rights Commission (OHRC) defines racial profiling as: “Any act or omission related to actual or claimed reasons of safety, security or public protection by an organization or individual in a position of authority, that results in greater scrutiny, lesser scrutiny or other negative treatment based on race, colour, ethnic origin, ancestry, religion, place of origin or related stereotypes” (OHRC 2019: 15). The OHRC’s revised definition of racial profiling builds and expands on its earlier 2003 definition. The new definition can be broken down into the following core elements (OHRC 2019: 15-16):

• Act or omission: adds a reference to “omission” to encompass situations where authority figures fail to exercise due diligence based on racial stereotypes about certain categories of complainants or victims

• Actual or claimed reasons: adds reference to “claimed reasons” to acknowledge that authority figures may not always act based on objective concerns about safety, security, and public protection

• Safety, security and public protection: recognizes that racial profiling is uniquely focused on actions associated with safety, security and public protection, whether in law enforcement or other contexts including education, transportation, health care, employment and border security

• By an organization or individual: refers to both organizations and individuals to recognize that racial profiling may be systemic or individual

• In a position of authority: recognizes that racial profiling is particularly associated with the actions of authority figures

• Results in greater scrutiny, lesser scrutiny or other negative treatment: recognizes that racial profiling may manifest itself through greater scrutiny, lesser scrutiny (of victimization), or other negative treatment that is not exclusively related to scrutiny

• Based on race, colour, ethnic origin, ancestry, religion, place of origin or related stereotypes: captures action based on either race-related Code grounds or related stereotypes to recognize that findings of racial profiling can be made in the absence of overt stereotyping.

While acknowledging the utility of the broad OHRC definition, it is important to note that, in

the research literature, the term racial profiling is most often used in reference to police stop, question and search activities (see Rice and White 2010). Many scholars make a conceptual distinction between racial profiling and other forms of racially biased policing. Racially biased policing is a general term that refers to possible racial discrimination with respect to a wide variety of discretionary police behaviours that include stop and search practices, but also include arrest decisions, charging practices, decisions related to pre-trial detention, sentencing recommendations and use of force. Racial profiling, at least for the purposes of this report, focuses specifically on police surveillance and street interrogation practices.

Racial profiling can be said to exist when the members of a certain racial or ethnic group become subject to greater levels of law enforcement surveillance than others. Racial profiling, therefore, refers to racial disparities with respect to police stop and search activities (sometimes referred to street checks or carding), increased police patrols in racialized neighbourhoods and undercover activities or sting operations that selectively target particular racial or ethnic groups. Furthermore, racial profiling exists when racial differences or disparities in police surveillance activities cannot be explained by racial differences in criminal activity, traffic violations, citizen calls for service or other legally relevant factors (see Wortley and Tanner 2005; Wortley and Tanner 2003). This somewhat narrow definition is highly consistent with definitions provided by American scholars. For example, Ramirez and Hoopes define racial profiling as “the inappropriate use of race, ethnicity or national origin rather than behaviour or individualized suspicion to focus on an individual for additional investigation” (Ramirez and Hoopes 2003: 1196). Similarly, Warren and Tomanskovic-Devey (2009: 344) state that racial profiling “is a term used to describe the practice of targeting or stopping an individual based primarily on race or ethnicity, rather than on individualized suspicion or probable cause.”

As highlighted by Paulhamus and her colleagues (2010), the academic literature has also drawn a distinction between what has been called “hard racial profiling” (cases in which the police stop civilians solely because of their racial background) and “soft racial profiling” (the use of race or ethnicity as one of several factors in the decision to stop a civilian). Proponents of “soft profiling” definitions argue that racially biased policing exists if race contributes to police decisions to stop, question and search individuals. For example, data may reveal that the police are most likely to stop and search male civilians, late at night, within poor, high-crime communities. However, if Black males traversing these same communities, during the same time of day, are significantly more likely to be stopped than White males, this would constitute evidence of racial profiling.

Profiling could be said to exist because, in addition to gender, time of day and type of community, race still impacts police decision-making. By contrast, advocates of “hard profiling” definitions would likely argue that racial bias does not exist in this scenario because race was only one of several factors – including gender, community crime level and time of day – that influenced officer decisions to stop and detain individuals. They would likely argue that this data reflects a pattern of “criminal” rather than “racial” profiling (Satzewich and Shaffir 2009).

Some proponents of the “hard profiling” position have argued that racial bias cannot be said to exist if there is a legal or legitimate reason for stopping the civilians in question. I disagree with this argument. Consider, for example, the following hypothetical situation. Suppose that a police officer was assigned to patrol a particular stretch of highway. Also assume that this officer never stops drivers unless they are exceeding the speed limit. In other words, all of his stops are clearly “legitimate.” However, also assume that this officer stops eight out of every 10 racialized speeders he encounters while on patrol (80%), but only stops one out of every five White speeders (20%). In other words, this officer is four times more likely to stop racialized drivers than White drivers who are exceeding the speed limit. In my opinion, this police officer could still be guilty of racial bias, even though all his stops are legally justifiable.

A similar example might be applied to illegal drug use. Assume that an officer stops and searches every racialized civilian he witnesses smoking marijuana in public. Also assume that this same officer decides to ignore most of the White civilians he sees engaged in the same drug using activity. Although it could be argued that the officer has a legally legitimate reason for stopping and searching racialized drug users, the fact that he refrains from stopping and searching White drug users is evidence of racial profiling.

In sum, although the term racial profiling has been used in a wide variety of criminological and sociological contexts, this report focuses exclusively on possible racial biases with respect to police street checks or stop, question and search (SQS) activities. To determine whether systemic racial profiling exists or not, researchers much first establish that some racial or ethnic groups are more likely to be stopped, questioned and/or searched by the police than others. If large racial disparities do not exist, it is highly unlikely that racial profiling is a problem. The next task is to explore the possible reasons behind any observed racial differences in exposure to involuntary police contact. In other words, can racial differences in the exposure to police stop and search activities be explained by other legally relevant factors? The report returns to this question – with a focus on the Toronto Police Service – after discussing the potential causes or reasons behind racial profiling.

A note on Justice Tulloch’s definition of “carding”

Public discussions concerning racial profiling in Ontario have been complicated by a variety of competing definitions. For example, in his 2018 report, the Honourable Michael Tulloch draws a strong distinction between “street checks” and what he refers to as “carding.” Justice Tulloch defines police carding as: “Situations in which a police officer randomly asks an individual to provide identifying information when there is no objectively suspicious activity, the individual is not suspected of any offence and there is no reason to believe that the individual has any information on any offence. That information is then recorded and stored in a police intelligence database” (Tulloch 2018: xi). In a later section of the report, Justice Tulloch makes a distinction between “legitimate” street checks and carding:

Many of the issues surrounding carding and street checks stem from a misunderstanding of the terms themselves. A street check is where information is obtained by a police officer concerning an individual, outside of a police station, that is not part of an investigation. This is a very broad category of police information gathering, and much of it is legitimate intelligence gathering of potentially useful information. Carding, as referred to in this report, is a small subset of street checks in which a police officer randomly asks an individual to provide identifying information when the individual is not suspected of any crime, nor is there any reason to believe that the individual has information about any crime. This information is then entered into

a police data-base (Tulloch 2018: 4).

Justice Tulloch argues that street checks often reflect legitimate police intelligence gathering activity. By contrast, due to their randomness, carding practices are an illegitimate practice that should be eliminated.[2]

In my opinion, the definitions of both “street checks” and “carding” provided by Justice Tulloch are incomplete when it comes to studying the phenomena of racial profiling. First of all, by its very definition, racial profiling is not random or arbitrary. Racial profiling is caused by racial bias (see discussion below) and thus is strongly associated with the race of civilians – or the racial composition of neighbourhoods – subject to police activity. Furthermore, long before Ontario’s new street check regulation and Justice Tulloch’s report, the Charter of Rights and Freedoms prohibits arbitrary police detentions. Thus, Justice Tulloch’s call to eliminate “carding” is nothing new.

Another weakness with Justice Tulloch’s definition of “carding” is that it does not acknowledge the concept of the pre-text stop – an important concept within the racial profiling literature.  Pre-text stops involve officers using minor offences (i.e., traffic violations, jaywalking, by-law violations, etc.) as a justification, excuse, or pretext to investigate more serious criminal activity (e.g., illegal drugs, illegal firearms, etc.). American research suggests that Black civilians are much more likely to be subject to pretext stops than people from other racial backgrounds (see Rushin and Edwards 2021; Gizzi 2011; Harris 2002; Harris 1997). Similar research and monitoring is required in Toronto and other Canadian jurisdictions (see discussion below).

A problem that could arise with the use of Justice Tulloch’s definition of “carding”

 is that it seems to appear to imply that racial profiling cannot exist if officers have a “legitimate” or “legally justifiable” reason for stopping or detaining an individual.

I disagree. As discussed above, racial profiling still exists if officers pay more attention to law violations committed by Black and other racialized civilians than law violations committed by White civilians. As a result, the focus of the analysis provided in this report is on racial disparities with respect to police stop, question and search (SQS) activities. It is not limited to police activities that Justice Tulloch would explicitly identify as “carding” or “street checks.”[3]

Furthermore, a focus on police SQS activities better captures the concerns of Black and other racialized communities. For example, previous research indicates that when it comes to addressing issues related to racial profiling, the police and the community have very different conceptions of street checks. While the police view street checks as a specific intelligence tool, racialized communities view street checks more literally – as being stopped, questioned or “checked” by the police on the street (see Wortley 219).

 

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The causes of racial profiling

What might be the possible cause or source of racial profiling or racially biased policing? Although researchers have spent a great deal of time and effort trying to both define and measure this phenomena, less attention has been given to developing an integrated theory that would help explain the existence of racial profiling by the police. Consistent with the work of Tomaskovic-Devey, Mason and Zinraff (2004), I propose five different theoretical models that might help explain racial profiling: 1) the racial animus model; 2) the statistical discrimination/criminal stereotype model; 3) the implicit bias model; 4) the institutional model; and 5) the police deployment model. It should be stressed that the first three models focus

on the intent and activities of individual police officers, while the final two models focus on organizational mechanisms. It is important to note that the two organizational models do not require any racial bias in officer or organizational intent, although they will produce racially biased police practices and disproportionately impact the members of racialized communities (see Tomaskovic-Devey et al. 2004: 3).

 

The racial animus model

The racial animus model holds that, within any given society, some people have a conscious dislike or prejudice against the members of other racial groups. To the extent that police services reflect the population that they serve, it is likely that some police officers will also have overtly racist beliefs that may promote or condone the poor treatment of racialized groups. Fortunately, North American research suggests that openly racist beliefs or prejudice have declined significantly over the past 50 years (see Schuman et al 1997; Henry and Tator 2005).^[4] Thus, it is likely that overt or explicit racial animus will be limited to a relatively small number

of police officers. Nonetheless, these few racist officers could significantly increase the rate of stop and search for targeted racialized groups and subsequently damage police-community relationships (Tomoskovic-Devey et al. 2004: 9).

According to the racial animus model, if police services can only identify and terminate these few “bad apples,” the problem of racial profiling will be eliminated. However, since most modern police services formally proscribe against racist attitudes and behaviour, the identification of overt racism among police officers is not a simple task. Indeed, the actual expression of racist beliefs by police officers, especially as they pertain to the treatment of racialized civilians, is likely to be rarer than the incidence of racial prejudice among police officers (see Tomoskovic-Devey et al. 2009: 9).

It is possible for some police services to have more “bad apples” than others. This might occur if police recruitment procedures do not effectively screen for racial animus or if informal field training processes encourage the expression of racist beliefs. Racial animus is also more likely to flourish within police organizations in which prohibitions against racist behaviour are not properly enforced (see Tomoskovic-Devey et al. 2009).

It should be stressed that the racial animus or “bad apples” explanation for racial profiling is somewhat popular among certain police administrators because it holds that racial profiling is an isolated problem, rather than a systemic issue, involving only a few corrupt police officers (see Tator and Henry 2006). On the other hand, many police officers and police union leaders have come to equate the term “racial profiling” with accusations of overt racism. As a result, when their police service is faced with allegations of racial profiling, many officers believe that they as individuals are being accused of holding overtly racist beliefs and are deliberately trying to harm racialized communities. Not surprisingly, many police officers find such accusations offensive (see Paulhamus et al. 2010; Satzewich and Shaffir 2009; Ioimo et al. 2007).^[5]

In sum, although it cannot be totally dismissed, the racial animus model only provides a theoretically limited explanation for racial profiling. Other explanations hold that racial profiling is not rooted in the overt racism of individual police officers. Rather, profiling practices stem from the broader police culture and specific organizational practices.

 

The statistical discrimination/criminal stereotype model

Racial profiling may also be caused by racial stereotyping with respect to criminal behaviour. In other words, individual police officers may develop beliefs, stereotypes

or profiles about the types of people who are more or less involved in criminal activity. These stereotypes might emerge as a result of socialization into the police subculture, personal job experiences, access to crime statistics or exposure to media depictions and mainstream stereotypes concerning crime and violence. For example, police supervisors and front-line officers may be exposed to crime statistics that show that

a large proportion of gun-related murders and gun possession charges involve Black male offenders. This pattern may be reinforced by racialized media coverage of crime and their own experiences on patrol. Exposure to this information may cause them to believe that it is more rational for police officers to pay special attention – or otherwise suspect – Black males than other civilians. Such conscious stereotyping could directly contribute to racial profiling. Far from an “individual problem,” racial stereotyping can become an informal, institutional phenomenon.

The mental construction of the “typical offender” has sometimes been referred to as “criminal profiling” and often involves race or ethnicity as well as other personal characteristics including age, gender, social class and personal appearance (see Satzewich and Shaffir 2009). Stereotyping may play an important role with respect to proactive policing.^[6] Police supervisors, as well as the general public, put pressure on police officers to identify criminal offenders

and subsequently ensure public safety. Demonstrating a proficiency at identifying and apprehending criminals may also be directly related to future promotion and career opportunities. Thus, many officers may feel a need or pressure to categorize people they encounter on the street by their likelihood of being involved in criminal activity. As a result, officers may feel that it would be more efficient or rational, from a crime-fighting perspective, to focus their surveillance activities on young, racialized males than, for example, older White females.

In a classic observational analysis of police patrol practices, Skolnick (1966) observed that the police in the United States tend to perceive young Black males as "symbolic assailants" and thus stop and question them on the street as a means of effective or efficient “crime prevention.” Anderson (1990) further articulates this tendency in his ethnographic study of a multi-racial community located in a large American city. In documenting the general police tendency to stop, search and harass young Black citizens as part of their routine patrolling activity, Anderson notes that:

On the streets, colour-coding works to confuse race, age, class, gender, incivility, and criminality, and it expresses itself most concretely in the person of the anonymous Black male. In doing their job, the police often become willing parties to this colour-coding of the public environment... a young Black male is a suspect until he proves he is not (Anderson 1990, pp. 190-191).

While patrolling the streets, the police may engage in the same type of actuarial risk assessment – and subsequent statistical discrimination – used by insurance companies (see Feeley and Simon 1992). For example, it is well known that insurance companies charge much higher premiums for young male drivers than drivers with other demographic characteristics. The justification for these higher rates is that, from a statistical standpoint, younger males are more likely to engage in risky driving behaviours (speeding, driving under the influence, etc.) and are more likely to become involved in serious traffic accidents. The same logic of statistical probability may be employed by the police on the street. According to individual and collective police experiences, young racialized males may be identified as the most likely to be involved in serious crime and violence. Thus, just as all young males must suffer from higher insurance premiums, all young racialized males, regardless of their individual behaviour, pay a higher cost when it comes to police attention.

Even though the majority of young males may have a clean driving record, they must pay higher insurance premiums because of the actions of a relatively few members of their demographic group. Similarly, even though the majority of young racialized males are law-abiding, they must pay a higher criminal justice premium: a criminal justice premium that manifests itself with respect to much greater exposure to police stop, question and search activities. Frank Zimring, an American academic who has championed the use of stop and search  tactics, admits that, due to statistical discrimination, Black and other racialized males are going to be disproportionately subjected to police stops. He further concedes that this amounts to “a special tax on minority males” (Bergner 2014). This theme is further elaborated by Tomaskovic-Devey and his colleagues (2004: 12) when they state that:

The use of profiles in law enforcement is thought to increase the efficiency of officers, and, consequently, the police organization as a whole. Unfortunately, criminal profiles are often based on stereotypes of characteristics related to different groups. In turn, group membership becomes a proxy for suspected criminality. An obvious result of such group generalizations in policing is that a widely cast net subjects many noncriminal minorities to police scrutiny while White people – both criminal and noncriminal – escape such surveillance. Criminal status no longer represents an individual characteristic but is shaped by group racial status.

It is important to note that this process of racial stereotyping does not necessarily involve racial animus or malice. Instead, police officer stereotypes about the “probable criminal” may be rooted in a professional desire to be efficient or effective when using limited law enforcement resources. Nonetheless, such racial stereotyping, even when grounded in statistics and conducted in the name of public safety, can have a profoundly negative impact on racialized communities (see discussion below).

 

The implicit bias model

The discussion, immediately above, referred to processes of explicit criminal profiling or criminal stereotyping that may consciously impact the actions of individual police officers. However, others have argued that implicit cognitive biases can also exist at the subconscious level (see Fridell 2017, White and Fradella 2016; Tomaskovic-Devey et al. 2004 for detailed discussions about the psychology behind the development of implicit cognitive biases). The basic argument is that people, in order to deal with an excess of information, learn to categorize. Categorization provides cognitive efficiency because it enables people to organize information and make decisions more quickly.

Research suggests that people tend to categorize themselves and others into groups automatically and unconsciously. Lacking detailed information about specific individuals, people categorize others on the basis of highly visible and easily attributable characteristics such as race, gender and age. In turn, this process of categorization has an almost automatic impact on how we perceive strangers and often directly impacts how be behave towards them. There is also a general tendency to make in-group and out-group distinctions and for people to display in-group favouritism. Out group biases, including negative attributions, may have a subconscious impact on police decision-making. As Tomaskovic-Devey and his colleagues (2004: 15-17) state:

This general tendency to make in-group and out-group distinctions has implications for racial bias in police stops. Because there is a tendency toward automatic display of in-group favouritism on making in-group and out group distinctions, officers may process information about driver threat in the context of both the driver’s and officer’s racial background. When engaging in proactive policing such as patrolling

a neighbourhood or interstate, officers are attempting to process large amounts of information in short time periods, with little individual information. They observe many people doing many things in dynamic settings. Acting as “cognitive misers,” they attempt to process the information in a way that allows them to be efficient in evaluating all that is observed. Placing information in categories is a primary way that this is accomplished. These categories trigger stereotypes that help determine what seems suspicious or out of place. The types of information police routinely focus on are those that tend to be associated with criminality and public safety. Police can be expected to focus in particular on behaviour, language, vehicle qualities, and appearances (i.e., clothing, jewelry) and settings that invoke images of criminality or threats to public safety. When the officer is making discretionary choices about who to pull over and who to cite, this type of cognitive bias may make cars driven by minority drivers seem slightly more dangerous.

The idea that unconscious or implicit racial bias can impact police decision-making has seemingly been embraced by a number of Canadian law enforcement agencies – including the Durham Regional Police Service, the Peel Regional Police Service, the Ottawa Police Service and the Toronto Police Service. These services have all commissioned the delivery of a training program known as “Fair and Impartial Policing” (fipolicing.com). This program, developed by criminologist Lorie Fridell, is designed to increase police officer awareness of their own implicit or unconscious biases and how these biases may impact how they treat or

respond to people from diverse backgrounds. Unfortunately, at the time of writing this report, the research team could not identify a single published article that evaluated implicit bias training in the Canadian context. Thus, it is impossible to determine whether implicit bias training has actually reduced racially biased policing practices among Canadian police services.

Overall, the research literature suggests that both conscious and unconscious stereotyping, at the level of the individual police officer, might contribute to racial differences in police stop and search activities. However, to truly comprehend the phenomenon of racial profiling, organizational as well as individual factors must be considered.

 

The institutional model

In the sections above, the report discussed how racial profiling may be the result of conscious racial stereotyping – often justified as criminal profiling – or implicit biases that are outside the consciousness of individual police officers. While conscious stereotypes or criminal “profiles” may be widely held within the police subculture and could be transmitted through informal socialization processes within police organizations, implicit biases, on the other hand, result from normal cognitive functioning and are thus common among people from all occupations and social backgrounds. However, we also cannot dismiss the possibility that certain police services actually develop profiling practices that are formally sanctioned by the organization’s leadership. In the United States, the use of formal racial profiles dates back to the late 1970s, when the federal government created drug courier profiles for the purpose of apprehending drug traffickers at American airports. The practice was later extended to highways and became a widespread policy in the early 1990s after the U.S. Drug Enforcement Agency (DEA) offered drug interdiction training to local and state patrol officers.

During this time, race was introduced as both a legitimate and normal characteristic of drug courier profiles, and police departments used these profiles to make stop and search decisions. A highway drug interdiction program, known as Operation Pipeline, trained more than 27,000 officers from 48 states how to use these profiles (Harris 2002; Warren and Tomaskovic-Devey 2009). There is also evidence to suggest that some Canadian police services may have received training from the DEA that is consistent with the principles of Operation Pipeline (see discussion in Tanovich 2006). There is also emerging evidence to suggest that formal, race-based criminal profiles have been extended to assist police in the identification of street gang members as well as drug traffickers (see Zatz and Krecker 2003; Barrows and Huff 2009).

In sum, it is important to note that the source of racial profiling behaviours cannot always be traced to the racialized beliefs, stereotypes or unconscious biases of individual police officers. Nor can it always be linked to racial stereotypes that are promoted within the informal police subculture. Sometimes the source of racially biased stop and search activities lies in the formal policies and training procedures of police organizations themselves. In other words, even officers who do not hold racist beliefs may engage

in racial profiling when they follow the formally sanctioned orders or instructions provided

by their supervisors and trainers. Once again, although the establishment of formal, race-based criminal profiles are often justified on the basis of effective policing and public safety, they also serve to stigmatize entire racialized communities and subject all members of identified groups to differential police treatment.

 

The police deployment model

Research suggests that police officers are not often deployed evenly across all areas of a community or urban area. For example, neighbourhoods with high rates of violent crime (homicides, shootings, assaults, robberies, gang activity, etc.) will typically receive more police patrols than neighbourhoods with low levels of violent offending. Indeed, modern, data-driven police management practices entail that crime “hot spots,” areas with higher than average rates of violent crime, should receive a disproportionate share of police attention. In addition to the uneven deployment of police patrols across neighbourhoods, research also suggests that the style of policing may vary across communities. Several studies have documented, for example, that policing is often more proactive or aggressive in areas with high crime rates. By contrast,policing tends to be more reactive and less aggressive in areas with low crime rates (Tomankovic-Devey et al. 2004; Nobles 2010; Parker et al. 2010).

Research also demonstrates that recent immigrants and certain racialized groups are over-represented in economically disadvantaged, high-crime communities, while White people are over-represented in wealthy, low-crime communities. Thus, by default, racial minorities are more likely to be subjected to more policing – including aggressive stop and search activities – as a function of the where they reside.^[7] Critics have argued that the greater police presence in racialized communities, combined with a more aggressive or proactive policing style, represents a form of systemic bias that will ultimately expose racialized civilians to negative police encounters. In other words, according to the police

deployment model, racial profiling is not necessarily the product of racial stereotyping or racial animus. It might, in fact, be partially explained by where the police are deployed and how the police exercise their authority across different communities.^[8]

One further note of caution when discussing the alleged “objectivity” of police deployment practices that are based on the statistical analysis of neighbourhood crime data. As discussed later in this report, biased police practices can produce biased police data. For example, biased policing may be at least partially responsible for the high rates of crime associated with curtained neighbourhoods or communities. Biased data, in turn, can be used to justify the biased police practices. The relationship between crime rates and aggressive, proactive police practices may be a form of self-fulfilling prophecy.

 

Summary

The purpose of this section has been to review possible explanations for racial profiling. Future research is needed to determine which of the above explanations are the most valid, or whether all five theoretical frameworks occur simultaneously and thus account for some proportion of the racial profiling phenomena. Some scholars believe that, since racial animus has declined significantly within society, overt racism will only explain a small amount of racial profiling behaviour. Similarly, due to political pressures, it is likely that organizational guidelines that directly target certain racial groups are becoming increasingly rare. However, racial stereotyping, cognitive biases and systemically biased police deployment practices likely remain prevalent and thus are still highly relevant to both researchers and policy-makers. It

is also important to note that some of the theoretical models discussed above are more amenable to policy than others. Formal race-based criminal profiles can be eliminated. Police services can screen for racial animus in new recruits, and discipline or terminate sworn officers who display overtly racist attitudes or behaviours. Policing in high-crime neighbourhoods can also be restricted to rapid response to calls for service, rather than proactive policing practices that often subject law-abiding residents to aggressive street interrogations. However, as noted by Tomaskovic-Devey, Mason and Zingraff (2004: 25), implicit biases and individual-level stereotyping may be more difficult to identify and control.

 

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Evidence of racial profiling by the Toronto Police Service

A review of the international literature reveals that five different methodological strategies have been employed by researchers to explore racial disparities in police stop, question and search activities. These five research methodologies include: 1) qualitative methods; 2) survey methods; 3) observational methods; 4) official statistics on police stops; and 5) official data on street checks or carding. In this section of the report, we examine previous research that has attempted to explore the issue of racial profiling in Toronto. A review of the literature reveals that, with respect to the Toronto Police Service, racial profiling has been examined using only three of the five research methodologies described above: qualitative methods, survey research and official statistics on street checks (also referred to as contact cards, field information reports and regulated interactions). We could not identify an observational study of racial profiling conducted in the Toronto region. Furthermore, despite public demand and report recommendations, the TPS has never conducted a study to examine racial disparities with respect to traffic and/or pedestrian stops.[9] 

The review of research evidence begins with an examination of qualitative studies before turning to a discussion of survey research conducted prior to the 2017 implementation of Ontario’s new street check regulation. After examining official TPS street check data and describing the dramatic decline in documented street checks post-regulation, the report reviews new survey research conducted since 2017. Results from these recent surveys challenge the argument that Ontario’s Street Check Regulation has reduced racial profiling and underscore the great need for race-based data collection on TPS stop, question and search activities.

 

Qualitative research

Much of the early work on racial profiling in the United States and Great Britain consisted of one-on-one interviews or focus groups with racialized youth (Jones-Brown 2000; Brunson 2007). In the Canadian context, James (1998) conducted intensive interviews with over 50 Black youth from six different cities in Ontario – including Toronto. Many of these youths reported that being stopped by the police was a common occurrence for them. There was also an almost universal belief that skin colour, not style of dress, was the primary determinant of attracting police attention. As one of Black male respondent noted: "They drive by. They don't glimpse your clothes, they glimpse your colour. That's the first thing they look at. If they judge the clothes so much why don't they go and stop those White boys that are wearing the same things like us. I think that if you are Black and wearing a suit, they would think that you did something illegal to get the suit" (James 1998: 166).

James concludes that the adversarial nature of these police stops contributes strongly to Black youths’ hostility and negative attitudes towards the police (James 1998: 173). Neugebauer's (2000) informal interviews with 63 Black and White Toronto youth produced very similar results. Although the author found that teenagers from all racial backgrounds often complain about being hassled by the police, both White and Black youth agree that Black males are much more likely to be stopped, questioned and searched by the police in Toronto than teens from other racial backgrounds.

During a series of public consultations in Toronto, conducted by the Ontario Government’s Review of the Roots of Youth Violence, strikingly similar stories were communicated to the lead investigators. Black and Indigenous youth from Toronto repeatedly told the inquiry that they felt targeted by the police – often through aggressive police stop and search activities – and that this targeting had eroded their trust in the police and the broader criminal justice system (McMurtry and Curling 2008a; McMurtry and Curling 2008b).

In another qualitative study, the Ontario Human Rights Commission (OHRC) gathered detailed testimonials from a non-random sample of over 800 people in Ontario – most of them Black residents of Toronto – who felt that they had been the victim of racial profiling (Ontario Human Rights Commission 2003). The OHRC project was not only successful in providing vivid descriptions of specific racial profiling incidents, but also provided detailed information concerning how these incidents negatively impact both racialized individuals and communities (Williams 2006). The OHRC conducted a second major investigation into racial profiling in 2015. This investigation involved consultations with a non-random sample of over 1,600 individuals and organizations. Once again, the Commission heard that racial profiling is a major problem in Toronto (Ontario Human Rights Commission 2017).

Importantly, after the release of the first two OHRC investigations, the existence of systemic racism within policing has been acknowledged by representatives from both the TPS and TPSB (see Ontario Human Rights Commission 2017; Aguilar 2020; Fox 2020; Goodfield 2020; Toronto Police Services Board 2020; CBC News 2018; Doolittle 2009).

Finally, since 2018, as part of its current inquiry into racially biased policing, the OHRC has conducted a series of interviews and focus groups with members of Toronto’s Black communities and members of the TPS. As with its earlier investigations, the OHRC continued to hear complaints about racial profiling and unfair TPS stop and search

practices. Civilian allegations have also been supported by the testimonials of police officers. In sum, the overall narrative that emerges from two decades of qualitative OHRC research is that racial profiling – within the TPS – is still a problem.

The argument that little has changed with respect to racial profiling in Toronto is reinforced by a number of recent, smaller-scale qualitative studies. These studies, all conducted since 2017 and the imposition of Ontario’s Street Check Regulation, focus on Black youth from disadvantaged Toronto communities. All of these studies document negative encounters between Black youth and the TPS, including allegations of racially biased stop and search practices. All document how TPS stop and search activities contribute to community distrust of the police, reduce the likelihood that youth will report crime, and increase reliance on self-help strategies designed to ensure personal safety (see Haag 2021; Samuels-Wortley 2021; Samuels-Wortley 2020; Nichols 2018).

Findings from the above government inquiries and academic studies were reinforced

by the Community Assessment of Police Practices (CAPP) research project. During the summer of 2014, the research team, funded by the Toronto Police Services Board, conducted an ambitious community survey that involved interviews with a non-random sample of 404 residents of 31 Division – an area encompassing one of the most racially diverse and socio-economically disadvantaged regions of Toronto. Approximately half the sample self-identified as Black, 12.1% as White and 30.4% as members of another racialized group. The results of the study indicate that respondents had little trust or confidence in the police. Furthermore, regardless of their own racial background, the majority of respondents felt that the Toronto police engaged in racial profiling. Consistent with this belief, Black respondents were much more likely to report that they had been recently stopped, searched and “carded” by the police than youth from other racial backgrounds. Compared to their White counterparts, Black youth were also more likely to report that, during police encounters, they had been intimidated and treated with hostility and disrespect (see Price 2014).

As discussed briefly above, qualitative methodologies have also been used to study police officer perceptions of the racial profiling issue. For example, following a series of newspaper stories on racially biased policing, former Toronto Police Chief Julian Fantino asked several senior Black officers, including Superintendent Keith Forde, to investigate how allegations

of racial profiling were being perceived by Black members of the force. In response to this request, 36 Black officers from the TPS met to discuss the issue of racial profiling in October 2003. A focus group format was utilized. All of the participating TPS officers agreed that racial profiling was a problem and that the criminal stereotyping of Black citizens was widespread within the Toronto Police Service. The majority of respondents also reported that they themselves had been the victim of racial profiling. Three officers, in fact, reported that they had been stopped and questioned by the police on more than one occasion in the same week, and six officers reported that they had been stopped on more than 12 occasions in the same year. In a subsequent presentation of these findings to their fellow officers, the senior Black officers tasked with the investigation began with the statement: “We know that racial profiling exists” (see Tanovich 2006: 35-36).

Similar research on the perceptions and experiences of Black police officers has recently been conducted by Dr. Akwasi Owusu-Bempah (Department of Sociology, University of Toronto). Owusu-Bempah (2015) conducted in-depth interviews with a non-random sample of 50 Black male police officers – many employed by the TPS. He argues that this police sample can provide unique insights into the reality of racism within law enforcement because of the respondents’ dual identities and experiences as both Black males within Canadian society and their experiences as police officers.

Almost all the Black male police officers involved in this study reported that they had observed racial profiling and other forms of racially biased policing on the job. Most admitted that they had worked with fellow officers who openly engaged in racial profiling and condoned the practice. Indeed, the majority indicated that they themselves had been subjected to racial profiling on multiple occasions – even after becoming a police officer.

All agreed that such racial bias has had a negative impact on Toronto’s Black community, and has produced distrust between the police and Toronto’s Black residents. Many of the officers argued that racially biased policing is caused by racial stereotypes that associate the Black population with both criminality and dangerousness (Owusu-Bempah 2015).

 

Summary

In conclusion, qualitative research, involving both Toronto residents and Toronto police officers, has produced findings that are highly consistent with the argument that the Toronto police engage in racial profiling. The nature of these qualitative results has not changed over the past three decades. Proponents argue that qualitative research methods can help researchers make sense of police stop and search statistics and further understand how police surveillance activities impact the lives of racialized people. As Brunson (2010: 221) notes, although statistics may help us identify racial differences in overall exposure to police surveillance activities, “they have not elicited the kind of information that would allow researchers to acquire deeper understandings of meanings for study participants.

On the other hand, qualitative research methods provide a unique opportunity to examine

and better understand the range of experiences that may influence individuals’ attitudes towards the police.” Stewart (2007: 124) adds: “A qualitative research approach allows researchers to measure the various sources of negative direct and vicarious police experiences and understand the meaning one attaches to these experiences.”

Although qualitative studies tend to provide great detail about police encounters and the "lived experience" of racial minorities, they have often been criticized for being based on small, non-random samples – usually from economically disadvantaged communities. In other words, it is often difficult to generalize the results of qualitative research to the wider population. Furthermore, most qualitative studies focus on the experiences of racialized people in isolation. In other words, they do not directly compare the experiences of racial minorities with the experiences of White people. These facts alone have led to charges that the qualitative research evidence documenting racial profiling is "selective" or "anecdotal" and thus not truly representative of police behaviour (see Wilbanks 1987; Melchers 2006). It should be stressed, however, that police denials of racial profiling are equally “anecdotal” and have thus been largely dismissed by racial minority organizations and anti-racism scholars (see Tator and Henry 2006). In sum, although qualitative research methods have considerable value when it comes to documenting and understanding police-race relations, there is a general consensus among researchers that, when possible, they should be supplemented with more quantitative approaches.

 

Survey research

Unlike qualitative research strategies, survey methods often explore the opinions and experiences of citizens using large, random samples. Thus, unlike qualitative results, survey findings can be more easily generalized to the entire population in question. With respect to racially biased policing, survey methods have been used to document that racial profiling is viewed as a serious problem by a large proportion of the Canadian population. In a 2007 survey of Toronto residents, for example, respondents were asked the following question: Racial profiling is said to exist when people are stopped, questioned or searched by the police because of their racial characteristics, not because of their individual behaviour or their actions. In your opinion, is racial profiling a problem in Canada or not? The results suggest that Black Canadians are much more likely to perceive racial profiling as a major social problem than their Chinese and White counterparts. Indeed, six out of 10 Black respondents (57%) view racial profiling in Canada as a “big problem,” compared to only 21% of White and 14% of Chinese respondents.^[10]

Respondents were then asked: Suppose that, in a particular neighbourhood, most of the people arrested for drug trafficking, gun violence and gang activity belong to a particular racial group. In order to fight crime in this area, do you think it would be okay or legitimate for the police to randomly stop and search people who belong to this racial group more than they stop and search people from other racial groups? According to the responses to this question, four out of 10 White respondents (39%) and a third of Chinese respondents (34%) feel that racial profiling is a legitimate crime-fighting strategy, compared to only 23% of their Black counterparts. These racial differences in opinion are statistically significant (see Wortley and Owusu-Bempah 2011b; Wortley and Owusu-Bempah 2009).

It is important to note that, in addition to measuring public opinion about racial profiling, survey methods can also be used to measure actual experiences with police stop and search activities in Toronto. The ability for surveys to measure race – as well as other variables that may theoretically predict contact with the police – is an important methodological advance that partially addresses the crucial issue of “benchmarking”

(see detailed discussion in Wortley 2019a; Wortley 2019b). In other words, survey methods enable us to estimate whether race has an impact on police stops and searches after statistically controlling for other relevant factors.

To date, there have been six large Canadian surveys that have addressed the racial profiling issue. Five of these studies were conducted in the Toronto region and the sixth involved a national sample that included a large number of Black Toronto residents. All six studies attempted to document whether racial minorities are more likely to be stopped and questioned by the police than White people – after statistically controlling for other factors that might increase or decrease the likelihood of drawing police attention (see reviews in Wortley 2016; Owusu-Bempah and Wortley 2014).

To begin with, a 1994 survey of over 1,200 Black, Chinese and White Toronto residents (at least 400 respondents from each racial group), conducted by York University’s Institute for Social Research, found that Black people, particularly Black males, are much more likely to report involuntary police contact than either White or Asian people. For example, almost half (44%) of the Black males in the sample reported that they had been stopped and questioned by the police at least once in the past two years. In fact, one-third (30%) of Black males reported that they had been stopped on two or more occasions. By contrast, only 12% of White males and 7% of Asian males reported multiple police stops.

Multivariate analyses of these data reveal that racial differences in police contact cannot

be explained by racial differences in social class, education or other demographic variables. In fact, two factors that seem to protect White males from police contact – age and social class – do not protect Black males. White people with high incomes and education, for example, are much less likely to be stopped by the police than White people who score low on social class measures. By contrast, Black people with high incomes and education are actually more likely to be stopped than Black people with a lower-class background. Black professionals, in fact, often attributed the attention they receive from the police to their relative affluence. As one Black respondent stated: “If you are Black and you drive something good, the police will pull you over and ask about drugs” (see Wortley and Tanner 2003; Wortley and Kellough 2004).

A second study, conducted in 2000, surveyed approximately 3,400 Toronto high

school students about their recent experiences with the police (Wortley and Tanner 2005; Hayle, Wortley and Tanner 2016). The results of this study further suggest that Black youth are much more likely than people from other racial backgrounds to be subjected to street interrogations. For example, over 50% of the Black students report that they have been stopped and questioned by the police on two or more occasions in the past two years, compared to only 23% of White students, 11% of Asians and 8% of South Asians. Similarly, over 40% of Black students claim that they have been physically searched by the police in the past two years, compared to only 17% of their White and 11% of their Asian counterparts.

However, the data also reveals that students who engage in various forms of crime and deviance are much more likely to receive police attention than students who do not break the law. For example, 81% of the drug dealers in this sample (defined as people who sold drugs on 10 or more occasions in the past year) report that they have been searched by the police, compared to only 16% of students who did not sell drugs. This finding is consistent with the argument that the police focus more on civilians who engage in illegal activity than civilians who do not engage in crime.

The data further reveal that students who spend most of their leisure time in public spaces (e.g., malls, public parks, nightclubs, etc.) are much more likely to be stopped by the police than students who spend their time in private spaces or in the company of their parents. This leads to the million-dollar question: Do Black students in this study receive more police attention because they are more involved in crime and more likely to be involved in leisure activities which take place in public spaces?

While the survey data reveal that White students report much higher rates of both alcohol consumption and illicit drug use, Black students report higher rates of minor property crime, violence and gang membership. Furthermore, both Black and White students report higher rates of participation in public leisure activities than students from all other racial backgrounds. These racial differences, however, do not come close to explaining why Black youth are much more vulnerable to police contact.

Multivariate analysis reveals that after statistically controlling for criminal activity, drug use, gang membership and leisure activities, the relationship between race and TPS stop and search activity becomes even stronger. Why? Further analysis reveals that racial differences in TPS stop and search practices are, in fact, greatest among students with low levels of criminal behaviour. For example, 34% of the Black students who have not engaged in any type of criminal activity still report that they have been stopped by the police on two or more occasions in the past two years, compared to only 4% of White students in the same behavioural category. Similarly, 23% of Black students with no deviant behaviour report that they have been searched by the police, compared to only 5% of White students who report no deviance (Wortley and Tanner 2005). Thus, while the first survey, discussed above, reveals that age and social class do not protect Black people from police stops and searches, this study suggests that good behaviour also does not shelter Black civilians from unwanted police attention.

This high school survey was also able to demonstrate that, because they are subject to higher levels of police surveillance, Black youth in Toronto are also more likely to be caught when they break the law than White youth who engage in exactly the same forms of criminal activity. Consider the example of student drug dealers. As discussed earlier, we defined a drug dealer as any respondent who had sold illegal drugs on at least 10 occasions in the past year. Our findings further reveal that 65% of Black drug dealers have been arrested at some time in their life, compared to only 35% of the White drug dealers – a finding that likely reflects the fact that Black students are much more likely to be stopped and searched by the police (Wortley and Tanner 2005; Hayle, Wortley and Tanner 2016).^[11]

These findings have also been replicated using a national sample of Canadian youth (12–17 years old). Fitzgerald and Carrington used data from the 2000–2001 National Longitudinal Survey of Children and Youth (sample size=4,164 respondents) to explore whether “high-risk” visible minority youth (Black, Indigenous and Arab respondents) were more likely than White youth or “low-risk” minority youth (South Asians and Asians) to be stopped and questioned by the police. It is important to note that a high proportion of the Black respondents to this national survey were from Toronto.

Consistent with the Toronto high school survey discussed above, Fitzgerald and Carrington (2011) found that Black, Indigenous and Arab youth from Toronto and other regions of Canada were significantly more likely to be stopped and questioned by the police over the past year than White, Asian or South Asian youth. Furthermore, multivariate analyses reveal that the impact of race on police stops remains statistically significant after controlling for other theoretically relevant variables including socio-economic status, family background, parental supervision, leisure activities, neighbourhood safety and individual involvement in both violent and nonviolent crime. In other words, although high-risk racialized youth reported higher levels of criminal involvement than White youth, this did not explain why racialized youth were more likely to be stopped and questioned by the police.

Indeed, consistent with Wortley and Tanner’s (2005) findings, the results of Fitzgerald’s and Carrington’s (2011) work suggests that racial differences in police contact are greatest among youth with low levels of criminal involvement. Once again, Canadian findings suggest that “good behaviour” does not protect Black people and other minorities from unwanted police contact to the same extent that it protects White people. The authors conclude that their findings are consistent with allegations of racial profiling.

A fourth Canadian survey, conducted in 2007, involves interviews with a random sample of 1,500 White, Black and Chinese Torontonians, 18 years of age or older. Over 500 respondents were selected from each of the targeted racial groups (Wortley and Owusu-Bempah 2011b). Respondents were asked how many times they had been stopped and questioned by the police – while driving in a car or walking or standing in a public space – in the past two years. The results suggest that a third of the Black respondents (34%) have been stopped by the police in the past two years, compared to 28% of White respondents and 22% of Chinese respondents.

Racial differences exist for both traffic and pedestrian stops. Black people are especially likely to experience multiple police stops. Indeed, 14% of Black respondents indicate that they have been stopped by the police on three or more occasions in the past two years, compared to only 5% of White and 3% of Chinese respondents. On average, Black respondents experienced 1.6 stops in the past two years, compared to 0.5 stops for White people and 0.3 stops for Chinese respondents.

Multivariate analysis of the 2007 survey data reveals that Black males from Toronto are particularly vulnerable to police stops. One in four Black male respondents (23%) indicate that they were stopped by the police on three or more occasions in the past two years, compared to only 8% of White males and 6% of Chinese males. On average, Black males experienced 3.4 police stops in the past two years, compared to 0.7 stops for White males and 0.5 stops for Chinese males. Although Black females are less likely to be stopped and questioned by the police than Black males, they are significantly more likely to report police stops than White or Chinese females. In fact, Black females (9%) are more likely to report three or more police stops than White (8%) or Chinese males (6%). On average, Black females report 0.7 police stops in the past two years, compared to 0.4 stops for White females and 0.2 stops for Chinese females (Wortley and Owusu-Bempah 2011).

Survey respondents were also asked if they had been physically searched by the police in the past two years. Once again, the data reveal that Black people – particularly Black males – are more vulnerable to police searches than respondents from other racial backgrounds. Overall, 12% of Black male respondents report being searched by the police in the past two years, compared to only 3% of White and Chinese males. Black females are also more likely to report being searched by the police (3%) than White or Chinese females (1%).

The data from this survey of Toronto residents clearly indicate that Black respondents are more likely to be stopped and searched by the police than White or Chinese respondents. However, as discussed above, there are factors, besides race, that may explain Black over-representation in police encounters. For example, Black Torontonians tend to be younger and less affluent than their White and Chinese counterparts. Thus, it may be youthfulness or poverty – not racial bias – that explains why Black people are more likely to be stopped and searched. Similarly, Black people may be more likely to be stopped because they are more likely to reside in high-crime neighbourhoods, often marked by aggressive police patrol strategies. Furthermore, racial differences in behaviour, not race itself, might explain why Black people receive greater police attention. For example, compared to people from other racial backgrounds, Black people may be more vulnerable to police stops because they spend more time driving or hanging out in public spaces. Finally, Black people may be more likely to draw the legitimate attention of the police because they are more likely to be involved in traffic violations or various forms of criminal activity.

In order to address these competing hypotheses, the authors produced a series of logistic regressions predicting police stop and search experiences. In addition to race, these regressions statistically control for a variety of demographic variables including age, gender, education, household income and place of birth. Our analysis also controlled for level of crime within the respondents’ neighbourhood, frequency of driving, level of involvement in public leisure activities, alcohol use, marijuana use and criminal history.

The results of the multivariate analyses indicate that, among Toronto residents, Black racial background remains a strong predictor of police stop and search activities after statistically controlling for other theoretically relevant variables. Chinese racial background, on the other hand, is unrelated to the probability of being stopped and searched by the police. The results further suggest that the more stringent the measure of police stops, the stronger the relationship with Black racial background. For example, an examination of the odds ratios indicates that Black people are 1.9 times more likely than White people to experience one or more stops in the past two years, 2.3 times more likely to experience two or more stops and 3.4 times more likely to experience three or more stops. Furthermore, the results suggest that Black people are also 3.3 times more likely than White people to have been searched by the TPS in the past two years (Wortley and Owusu-Bempah 2011b).

All respondents who reported that they had been stopped and questioned by the TPS in the past two years (N=423) were subsequently asked a series of questions about their

most recent police encounter. The results clearly indicate that Black Toronto residents tend to interpret police stops more negatively than their Chinese and White counterparts. To begin with, respondents were asked if they thought their latest police stop was fair or unfair. Almost half of the Black respondents (47%) felt that their last police stop was unfair, compared to only 17% percent of Chinese and 12% of White respondents. Compared to White and Chinese respondents, Black respondents were also less likely to report that the police adequately explained the reason for the stop and were more likely to report that the police treated them in a disrespectful manner.

 Respondents to this survey were also asked the following open-ended question: The last time you were stopped by the police, why do you think they stopped you? One out of every four Black respondents (25%) specifically claimed that they were stopped because of their race. By contrast, only two Chinese respondents and two White respondents cited race as the reason that they were stopped. Interestingly, both of these White respondents claimed that they were stopped by the police because they were riding in a car with Black people. With these results in mind, it is not surprising to note that Black respondents were much more likely than Chinese or White respondents to report that they were “very upset” by their last police encounter (Wortley 2011b). These results are remarkably consistent with American research that also suggests that Black people are more likely to feel that they have been treated unfairly or with disrespect during police stops (see Warren 2011).^[12]

The issue of involuntary police contact was also explored by a survey conducted as part of the Black Experience Project (Environics Institute 2017). This survey, conducted in 2015, explored the opinions and experiences of 1,504 Black residents, 16 years of age or older, from the Greater Toronto Area. My reanalysis of this data, obtained by the OHRC, confirms that negative encounters with the police are very common among the Black residents of the GTA – particularly Black men. For example, 71% of Black male respondents reported that they had been stopped and questioned by the police in a public place, 53% reported that they had been harassed or treated rudely by the police, 23% had been arrested by the police at some time in their life, and 17.5% reported that they had been subject to police use of force (see Figure 1).^[13]

The data further reveal that negative police experiences are slightly more common among Black residents of the City of Toronto than respondents who live in other areas of the GTA (see Figure 2). For example, Black Toronto residents are more likely to report police

use of force, being arrested by the police and being harassed or treated rudely by the police. However, other GTA residents are slightly more likely to report that they have been stopped and questioned by the police in public. Unfortunately, the data do not allow for an examination of where police stops took place. It is quite possible, therefore, that some respondents who live outside of Toronto were actually stopped by the Toronto Police when travelling through the city for work or leisure. All regional differences are statistically significant at the p >.05 level.

In the past, critics have argued that it is poverty or lower-class position, not racism, that exposes Black people to negative police encounters. However, consistent with previous studies, the results of the Black Experience Project reveal that higher social-class position does not protect Black people from involuntary police contact (see Figures 3 and 4) For example, Black people with an undergraduate university degree are more likely to report being stopped and questioned by the police (56.4%) than people with a high school degree or less (45.2%). Similarly, respondents who earn $100,000 or more per year are more likely to report being stopped and questioned by the police (60.3%) than respondents who earn less than $20,000 per year (46.7%). These differences are statistically significant. These findings further strengthen the argument that race alone draws police attention, not social class or residence in a poor neighbourhood.^[14]

 

Summary

With respect to investigating racial profiling, survey research has three distinct advantages over qualitative data. First of all, since surveys are based on large, random samples, research results can be more easily generalized to the total population. Secondly, surveys permit direct comparisons between people who report that they have been stopped and searched by the police and people who have not been stopped. Thus, we are able to determine if people who are frequently stopped and searched by the police are different – with respect to race or other theoretically relevant factors – than people with little or no contact. Finally, in addition to documenting specific experiences with the police, surveys can also be used to investigate the psychological impact that perceived racial profiling incidents have on targeted populations.

Survey research, however, is not without its limitations. Potential weaknesses with survey methods include problems with sampling error, questionnaire construction, respondent recall, respondent honesty and sample exclusion (see Lichenberg 2007; Lundman 2003). However, comparing the results of surveys with the results of other qualitative and quantitative research methods can serve as a validity check and ultimately increase confidence in the findings. It is thus important to note that the results of the above Toronto-area surveys are remarkably similar to the results produced by qualitative studies (see discussion above) and studies that examine official statistics from the Toronto Police Service. We turn to an analysis of official TPS “street check” data in the next section.

 

Official police statistics: street checks

A fourth strategy for measuring police stop and search activities involves the use of formal police records to document discretionary police-civilian interactions. In the United States and Great Britain, official police-reported data is arguably the most common source of information on police stop and search practices (Miller 2010; Paulhamus et al. 2010; Tillyer et al 2010; Batton and Kadleck 2004). This is not surprising given that police statistics are rather quick and inexpensive compared to large-scale surveys, systematic social observation, interviews, ethnography, and other qualitative methods. Often, data is already available, and new data collection strategies require minimal changes to current stop and search recording practices. Large police datasets can also be generated in a relatively short period of time at minimal cost to the organization. Official data collection also has the advantage of maintaining high levels of police discretion in policing practice, but at the same time goes towards addressing and allaying community concerns about racial profiling (Data Collection Resource Centre 2011). Finally, one advantage of police-recorded stop data includes legal and contextual variables that may be missing from citizen reports of police stops, such as reason for the stop, official disposition of the stop, the police perception of citizen race, as well as the exact date, time and location of the stop.

Unfortunately, unlike England and many regions of the United States, police services in Canada are not required to record the race or ethnicity of the civilians they stop and/or search. Furthermore, with the exception of special studies conducted in both Kingston (Marshall 2017; Wortley and Owusu-Bempah 2016) and Ottawa (Foster, Jacobs and Siu 2016), no Canadian police service voluntarily collects and disseminates data on traffic or pedestrian stops. Thus, in this country, official police statistics typically cannot be used to investigate racial differences in police stop and search activities.

Importantly, another source of official Canadian data can be used to assess racial differences in levels of police contact. This data involves a range of police activities including street checks, contact cards, community engagement incidents, field information reports and regulated interactions. Although the exact terminology used to identify such police-civilian engagements varies from police service to police service, they tend to refer

to the same phenomenon. For the purposes of this report, the term “street checks” will be used to refer to practices that include contact cards (carding), field information reports, community engagement incidents and regulated interactions. It should be stressed that street checks are not completed after every police stop. Before the 2017 implementation of Ontario Regulation 58/16 (see discussion below), street checks were only filled out when individual police officers want to record the details of an encounter they have had with a particular civilian. It should be noted that, in the vast majority of cases, street checks are not filled out during police encounters that end in arrest or criminal charges. In such cases, a record of arrest and/or criminal incident report is used to capture relevant information. Street checks, on the other hand, are typically filled out in cases where criminal charges are not laid, but the police officer still wants to record – for police intelligence purposes – personal information about the civilian stopped and details about the encounter. Over the past decade, numerous police services have released street check data to the public. This data has consistently demonstrated that, across time and police jurisdictions, Black people are highly over-represented in police street check statistics. However, a great deal of the public attention and debate has focused on street checks conducted by the Toronto Police Service (TSP).

The Toronto case study

Although street checks have been collected, in one form or another, by police in Ontario since at least 1970, information about what they contained was never released to the public. However, following a hotly contested freedom of information request that ultimately took them to the Ontario Court of Appeal, the Toronto Star newspaper eventually obtained information on over 1.7 million civilian street checks that had been filled out by the Toronto police officers between 2003 and 2008. Subsequent data requests from the Star captured information from more than two million additional street checks completed between 2008 and November 2013. Overall, the data indicate that the Toronto Police Service completed close to three million street checks over the decade spanning 2003 to 2013 – approximately 300,000 per year (see Rankin 2010a; Rankin 2010b; Rankin and Winsa 2012; Rankin and Winsa 2014).

The contact cards or street checks obtained by the Star contain various pieces of information including the civilian’s name and home address, the reason for the stop and the location and time of the encounter. These cards also include basic demographic information including age, gender and skin colour. The cards often include information on the civilian’s associates (i.e., who they were with at the time of the stop) and specific observations or comments about the encounter deemed relevant by the officer(s) involved. Police argue that this information helps them keep track of who is present on the streets at certain times and locations and that this information may help them identify potential crime suspects, victims and potential witnesses.

Critics argue that these contact cards provide insight into police surveillance practices and largely reflect the types of neighbourhoods and civilians that come under enhanced police scrutiny. A possible methodological benefit of the contact card data received by the Star is that at the time of the first data request, the police did not know that contact card information was going to be available for public scrutiny. In other words, the actions of the police documented by the Toronto contact card data were not impacted by their knowledge of an ongoing research project (see Barnes 2010 for the potential impact of what has become known as the Hawthorne Effect).

The following results stem from a re-analysis of TPS street check data, compiled from 2008 to 2013, conducted for the purposes of this report. The results are highly consistent with findings previously published in the Toronto Star – with several refinements. To begin with, only those cases in which the race of the carded civilian was recorded by the officer are included in the current analysis (sample size=1,846,930).^[15]

The data indicate that 25% of all street checks completed by the TPS between 2008 and November 2013 involved individuals described as “Black.” Census projections, however, suggest that only 8.08% of Toronto’s population at the time self-identified as Black.^[16] In other words, Black people are 3.09 times more likely to appear in street check statistics than their representation in the Toronto population would predict (see Table 1).

Further analysis reveals that during this period, the street check rate for Black people was 2,123.0 per 1,000. In other words, the TPS conducted 2,123.0 street checks for every 1,000 Black people in the Toronto population – or approximately 2.1 stops for every Black person in the city. By contrast, the street check rate for White people was only 653.7 per 1,000 – significantly less than one stop for each White person in the general population. Overall, the Black street check rate is 3.25 times greater than the White rate. This indicates that, between 2008 and 2013, Black people in Toronto were 3.25 times more likely to experience a TPS street check than White people (see Table 1).[17]

 

Table 1: Toronto Police Service street check data, by race, 2008 to 2013

Racial groups	Population size	% of population	Total number of street checks	% of street checks	Odds ratio	Street check rate (per 1,000)
White	1,454,030	54.09	950,457	51.46	0.95	653.7
Black	217,360	8.08	461,468	25.00	3.09	2,123.0
Brown	337,512	12.55	308,809	16.72	1.33	914.9
Other racialized	679,840	25.28	126,196	6.83	0.27	185.6
Total	2,668,742	100.00	1,846,930	100.00	1.00	692.1

A number of critics, however, have argued that many street checks completed by the Toronto Police likely involve civilians who do not actually live in the city. If this is true, it would make the street check rates and racial disparities, presented in Table 1, unstable. Fortunately, the 2008–2013 street check dataset indicates whether individuals reside in the City of Toronto or some other jurisdiction. Further analysis reveals that during this time period, 708,706 carding incidents – or approximately 38% of all carding cases – involved individuals who were not residents of Toronto. Table 2, therefore, recalculates street check statistics using only those cases that involve Toronto residents and include the race of the civilian carded (sample size=1,138,224). The results suggest that although the removal of non-residents reduces the overall carding or street check rate, the magnitude of the racial disparities is not diminished. In fact, racial disparities actually become more pronounced. Limiting the analysis to Toronto residents, the street check rate drops from 2,123.0 to 1,362.0 for Black people and from 653.7 to 392.6 for White people. However, the data also indicate that between 2008 and 2013, Black residents of Toronto were 3.22 times more likely to be carded than their representation in the general population would predict. Furthermore, the data indicate that Black Toronto residents are 3.47 times more likely to be subjected to a TPS street check than their White counterparts.

 

Table 2: Toronto Police Service street check data, by race, Toronto residents only, 2008 to 2013

Racial groups	Population size	% of Population	Total number of street checks	% of street checks	Odds ratio	Street check rate (per 1,000)
White	1,454,030	54.09	570,897	50.16	0.93	392.6
Black	217,360	8.08	296,051	26.01	3.22	1,362.0
Brown	337,512	12.55	195,787	17.20	1.37	580.1
Other racialized	679,840	25.28	75,489	6.63	0.26	111.0
Total	2,668,742	100.00	1,138,224	100.00	1.00	426.5

Another potential weakness with typical Census benchmarking is that it does not account for civilians who have been subject to multiple street checks. Indeed, individuals who are street checked on multiple occasions can drive up the street check rates for an entire racial group. Table 3, therefore, recalculates odds ratios and street check rates by controlling for individuals who have been stopped on multiple occasions. The data provided in Table 3 counts every civilian once and thus eliminates the influence of outliers.

The data indicate that between 2008 and 2013, 629,556 unique Toronto residents were responsible for 1,138,224 distinct street checks (about 1.8 street checks per individual in the dataset). On average, Black individuals in the street check dataset were involved in 2.23 street checks during this time frame, compared to 1.89 for Brown individuals, 1.70 for White individuals and 1.29 for individuals from other racialized groups.

When individuals are counted only once, racial disparities noticeably decrease. For example, the percentage of Black people in the street check data drops from 26.01% to 21.06% and the odds ratio drops from 3.22 to 2.61. However, even when counting unique individuals once, Black people are still 2.6 times more likely to appear in the TPS street check dataset than their presence in the general population would predict. Similarly, even when counting individuals once, the Black street check rate (610.1 per 1,000) remains 2.65 times higher than the White rate (230.3 per 1,000). In other words, the data suggest that between 2008 and 2013, the TPS conducted street checks on approximately 61.0% of Toronto’s Black resident population, compared to only 23.0% percent of Toronto’s White resident population.

 

Table 3: Toronto Police Service street check data, 2008 to 2013, by race Toronto residents only – unique individuals counted once

Racial group	Population count	% of population	Number of street checks	% of street checks	Odds ratio	Street check rate (per 1,000)
White	1,454,030	54.09	334,811	53.18	0.98	230.3
Black	217,360	8.08	132,621	21.06	2.61	610.1
Brown	337,512	12.55	103,365	16.42	1.31	306.3
Other racialized	679,840	25.28	58,759	9.33	0.37	86.4
Total	2,668,742	100.0	629,556	100.0	1.00	235.9

Community residents have long argued that young Black males are particularly vulnerable to street checks and other police surveillance activities. This claim is also supported by previous survey research (see discussion above). Table 4 provides an additional examination of this hypothesis by examining racial differences in Toronto police carding practices, between 2008 and 2013, for young male residents of Toronto. It should be stressed that all street checks captured in this table involve confirmed Toronto residents – not individuals who reside outside the city limits.

The first thing to highlight is that young males, regardless of their racial background, tend to be significantly over-represented in carding incidents. For example, although 15–24-year-old males represent only 6.3% of Toronto’s population, they account for 30.0% of all carding incidents involving Toronto residents. Overall, young males in this age group were 4.8 times more likely to be carded than their proportion in the general population. However, the data also reveal that young Black males were particularly vulnerable to street checks during this period. Although census estimates indicate that Black males, 15–24 years of age, represent only 0.5% of Toronto’s population, they accounted for 10.3% all street checks conducted by the Toronto Police Service between 2008 and 2013. In other words, young Black males in this age category were 20.6 times more likely to be carded than their representation in the general population would predict. By contrast, young White males,

in the same age category, are only 3.3 times more likely to be carded than their representation in Toronto’s population.

The data further indicate that the carding or street check rate for young Black males (8,709.7 per 1,000) is 4.3 times higher than the city average for males in this age group (2,044.8 per 1,000) and 6.2 times greater than the carding rate for young White males (1,415.6 per 1,000). To put these findings into further context, the data suggest that,

between 2008 and 2013, the TPS conducted approximately 8.7 stops for every young Black male resident of the city, compared to only 1.4 stops for every White male resident in the same age category. These racial differences cannot be easily dismissed.

 

Table 4: Toronto Police Service carding data, 2008 to 2013, carding incidents involving young male residents of Toronto (15–24 years of age)

Racial groups	# of male Toronto residents (15–24 years of age)	% of Toronto population that is male (15–24 years of age)	# of street checks involving male Toronto residents (15–24 years of age)	% of all street checks involving male Toronto residents (15–24 years of age)	Odds ratio	Street check rate (per 1,000)
White	90,333	3.4	127,877	11.2	3.3	1,415.6
Black	13,503	0.5	117,607	10.3	20.6	8,709.7
Brown	20,968	0.8	77,188	6.8	8.5	3,681.2
Other racialized	42,234	1.6	18,884	1.7	1.1	447.1
Total	167,035	6.3	341,556	30.0	4.8	2,044.8

Further analysis of the TPS carding data indicate that Black people were issued a disproportionate number of contact cards in all Toronto neighbourhoods – regardless of the local crime rate or racial composition. Indeed, the findings indicate that although Black people were over-represented in contact cards collected in high-crime neighbourhoods, they were even more highly over-represented in contact cards collected in low-crime, predominantly White neighbourhoods (Meng 2017; Rankin 2010a; Rankin 2010b; Rankin and Winsa 2012). This finding seemingly contradicts the argument that Black people are only stopped more than White people because they are more likely to live in or spend time in high crime communities. In fact, the data reveal that Black residents of Toronto are more likely than people from other racial groups to be carded both within the patrol zones that they live in and when they travel outside of their immediate neighbourhood.

Additional analysis of the TPS contact card dataset indicates that many police street checks were conducted for reasons of “general investigation.” In other words, these contacts were not the result of a specific traffic violation, criminal investigation or suspect description. For example, in 2008, the TPS filled out 289,413 contact cards: 158,685 of these contacts (55%) were conducted for reasons of “general investigation.”^[18] Consistent with the overall findings, 24% of these “general investigation” stops involved Black people (a rate that is three times higher than the representation of Black people in the general Toronto population). By contrast, less than 1% of all recorded stops were conducted for reasons of suspected bail non-compliance, suspected street gang activity, suspected gun-related activity, a suspected robbery or a suspected break-and-enter incident (Rankin 2010b). An argument could be made, therefore, that these findings are highly consistent with racial profiling allegations – that skin colour makes Black people more vulnerable to general police investigations that do not involve an articulable cause or individualized suspicion. At the very least, they serve to highlight the great need for further research and monitoring.^[19]

 

2014 Toronto Street check data

According to new TPS street check data obtained by the OHRC, the number of street checks conducted by the Toronto Police Service declined dramatically from 403,462 in 2012 to only 24,364 in 2014. This dramatic decline likely resulted from increased public concern about racially biased policing and community allegations of racial profiling. This decline also corresponds with the release of the TPS’s PACER report (PACER 2014). This report recommended that the performance of front-line officers should no longer be evaluated with respect to the number of street checks completed during each shift. Finally, in 2012, the Toronto Police Services Board created a Street Check Sub-Committee (SCSC). The SCSC eventually directed the TPS to introduce an interim street check receipt process, effective July 1t, 2013. The implementation of this receipt process, which required TPS officers to provide a receipt to all civilians involved in street check incidents, likely contributed further to the dramatic decline in street checks between 2012 and 2014. . However, despite the dramatic decline in overall street check numbers, the following analysis reveals that racial disparities persisted into the 2014 period.

Table 5 presents data on street checks, conducted and documented by the Toronto Police Service, in 2014. Population estimates are based on the 2016 Canadian Census. It should be noted that in 2014, the TPS added two racial categories to their street check classification strategy: Indigenous and Asian. However, they continued to use a category denoting “Brown” skin colour. For purposes of this analysis, we have collapsed the following racial categories from the Census into the “Brown” category: South Asian, West Asian/Arab and Latin American.

The data, once again, suggest that Black civilians are grossly over-represented in street checks documented by the Toronto Police Service in 2014. For example, although Black people represent only 8.9% of Toronto’s population (as measured by the 2016 Census), they represent 26.5% of all street checks conducted by the TPS in 2014. In other words, Black people are 3.0 times more likely to appear in Toronto police street check data than their presence in the general population would predict. The data also indicate

that Indigenous people are over-represented in Toronto street checks. They are 2.9 times more likely to appear in TPS street check statistics than their presence in the population would predict. All other racial groups are under-represented in 2014 TPS street check data. White people, on the other hand, appear in the street check data at a level consistent with their representation in the general population.

According to the data presented in Table 5, Indigenous and Black people have, by far, the highest street check rates. Indigenous people have the highest rate (27.4 per 1,000), followed closely by Black people (26.9 per 1,000). The street check rates for all other racial groups fall below 10 per 1,000. Thus, in Toronto, the 2014 Indigenous (27.4) and Black (26.9) street check rates are over three times greater than the rate for White civilians (8.6 per 1,000).

According to the 2014 data provided by the TPS, civilian race was not recorded for 1,204 street checks (or 4.9% of the entire sample). This missing data could contribute to the under-estimation of racial disparities. Thus, in Table 6, we eliminate missing cases from the data and recalculate the odds ratios. After excluding the missing cases, the percentage of street checks involving Black civilians jumps from 26.5% to 27.9% and the odds ratio increases from 3.0 to 3.1. In other words, after eliminating missing cases, Black people are 3.1 times more likely to appear in 2014 TPS street check data than their presence in the general population would predict.

Similarly, after excluding missing cases, the percentage of street checks involving Indigenous civilians jumps from 2.6% to 2.7% and the Indigenous odds ratio increases from 2.9 to 3.0. In other words, after eliminating missing cases, Indigenous people are 3.0 times more likely to appear in 2014 Toronto police street check data than their presence in the general population would predict.

A potential weakness of census benchmarking techniques is that they do not account for street checks involving non-residents of the jurisdiction under study. The argument is that visitors to the city may drive up the street check numbers for certain racial groups. Fortunately, the 2014 Toronto street check data can distinguish between residents and non-residents. Table 7 recalculates odds ratios and street check rates after non-residents have been eliminated from the Toronto street check data. Overall, racial disparities increase after removing non-residents from the calculations. For example, the odds ratio for Black civilians rises from 3.1 to 3.2 after non-residents have been eliminated from the sample. In other words,

Black residents of Toronto are 3.2 times more likely to appear in street check data than their presence in the general population would predict. Furthermore, the street check rate for Black Toronto residents (18.6 per 1,000) is 3.3 times higher than the rate for White residents (5.7 per 1,000).

Another potential weakness with census benchmarking is that it does not account for civilians who have been subject to multiple street checks. Indeed, individuals who are street checked on multiple occasions could drive up the street check rates for an entire racial group. Table 8 therefore recalculates odds ratios and street check rates by controlling for individuals who have been stopped on multiple occasions. The data provided in Table 8 counts every civilian once and thus eliminates the influence of outliers.

The data indicate that 12,882 unique Toronto residents produced 15,697 distinct street checks (about 1.20 street checks per individual Toronto resident in the dataset). Almost nine out of 10 individuals (88.2%) appear only once in the 2014 TPS street check data. Only 11.8% were subject to two or more street checks. Within the dataset, Indigenous people averaged 1.39 street checks, followed by Black people (mean=1.26), Asian people (mean=1.24), White people (mean=1.17) and “Brown” people (mean=1.13).

In the 2014 Toronto data, when individual residents are counted only once, racial

disparities remain unchanged. For example, when counting individuals once, Black people

are still 3.1 times more likely to appear in the Toronto street check dataset than their presence in the general population would predict. Similarly, the Black street check rate (14.8 per 1,000) remains 3.1 times higher than the White rate (4.8 per 1,000).

The Toronto 2014 data also describe the reason or justification for the street check

(see Table 9). It should also be noted that the street check reason categories changed dramatically between 2013 and 2014. The data suggest that in 2014, over half of Toronto

police street checks (58.2%) were classified as “investigation.” No other details are provided. An additional 11.9% were related to “suspicious activity” and 10.9% were “vehicle-related.” Once again, very few street checks explicitly deal with specific criminal investigations. For example, only 1.9% of all 2014 street checks dealt with suspected street gang activity (see Table 10).

Table 10 reveals that racial disparities exist with respect to most types of street checks. Indeed – with the exception of street checks related to biker gangs – Black civilians are significantly over-represented in all street check categories. By contrast, Indigenous people are primarily over-represented in vulnerable persons checks. By contrast, other racial groups are under-represented in each street check category. Interestingly, White civilians are over-represented with respect to street checks related to both biker gangs and vulnerable persons. Although Black civilians represent only 8.9% of the population, they represent 63.1% of street gang-related street checks, 27.2% of street checks related to drugs and 25.86% of “general investigations” (see Table 10).

 

Table 5: Total street checks, Toronto Police Service, 2014, by racial group, population estimates from 2016 census

Racial group	Population estimate (2016 census)	% of population (2016 census)	# of street checks	% of street checks	Odds ratio	Street check rate (per 1,000)
White	1,282,750	47.7	11,084	45.5	1.0	8.6
Indigenous	23,065	0.9	631	2.6	2.9	27.4
Asian	548,870	20.4	1,519	6.2	0.3	2.8
Black	239,850	8.9	6,455	26.5	3.0	26.9
Brown	597,130	22.2	3,471	14.2	0.6	5.8
Missing	----	----	1,204	4.9	----	----
Total	2,691,665	100	24,364	100.0	1.0	9.1

“Brown” includes “South Asian,” “Latin American,” “Arab” and “Other”

 

Table 6: Total street checks, Toronto Police Service, 2014, by racial group (excludes cases in which race is missing),population estimates from 2016 census

Racial group	Population estimate (2016 census)	% of population (2016 census)	# of street checks	% of street checks	Odds ratio	Street check rate (per 1,000)
White	1,282,750	47.7	11,084	47.9	1.0	8.6
Indigenous	23,065	0.9	631	2.7	3.0	27.4
Asian	548,870	20.4	1,519	6.6	0.3	2.8
Black	239,850	8.9	6,455	27.9	3.1	26.9
Brown	597,130	22.2	3,471	15.0	0.7	5.8
Total	2,691,665	100	23,160	100.0	1.0	8.6

“Brown” includes “South Asian,” “Latin American,” “Arab” and “Other”

 

Table 7: Total street checks, Toronto Police Service, 2014, by racial group, City of Toronto residents only, census population estimates based on 2016 Canadian census

Racial group	Population estimate (2016 census)	% of population (2016 census)	# of street checks	% of street checks	Odds ratio	Street check rate (per 1,000)
White	1,282,750	47.7	7,373	47.0	1.0	5.7
Indigenous	23,065	0.9	363	2.3	2.6	15.7
Asian	548,870	20.4	1,078	6.9	0.3	2.0
Black	239,850	8.9	4,463	28.4	3.2	18.6
Brown	597,130	22.2	2,420	15.4	0.7	4.1
Total	2,691,665	100	15,697	100.0	1.0	5.8

“Brown” includes “South Asian,” “Latin American,” “Arab” and “Other”

 

Table 8: Total street checks, Toronto Police Service, 2014, by racial group (City of Toronto residents only – unique individuals counted once), census population estimates based on 2016 Canadian census

Racial group	Population estimate (2016 census)	% of population (2016 census)	# of street checks	% of street checks	Odds ratio	Street check rate (per 1,000)
White	1,282,750	47.7	6,123	47.5	1.0	4.8
Indigenous	23,065	0.9	303	2.4	2.7	13.1
Asian	548,870	20.4	886	6.9	0.3	1.6
Black	239,850	8.9	3,552	27.6	3.1	14.8
Brown	597,130	22.2	2,018	15.7	0.7	3.4
Total	2,691,665	100	12,882	100.0	1.0	4.8

“Brown” includes “South Asian,” “Latin American,” “Arab” and “Other”

 

Table 9: Reasons or justifications for street checks conducted by the Toronto Police Service, 2014

Reason for street check	#	%
Drug-related	2,319	9.5
Biker gang/organized crime	204	0.8
Street gangs/guns	464	1.9
Investigation	14,179	58.2
Suspicious activity	2,893	11.9
Vehicle related	2,620	10.8
Vulnerable persons check	1,685	6.9
Total	24,364	100.0

 

Table 10: Percentage of civilians street checked by the Toronto Police Service for specific reasons, by racial background, 2014

Reason for street check	White	Indigenous	Asian	Black	Brown	Missing	Sample size
Drug-related	48.4	1.6	4.3	27.2	13.1	5.5	2,319
Biker Gang/organized crime	66.2	1.5	2.5	5.4	3.9	20.6	204
Street gangs/guns	16.4	0.9	6.5	63.1	6.0	7.1	464
Investigation	45.9	3.1	6.6	25.8	14.3	4.3	14,179
Suspicious activity	45.3	2.3	5.6	25.9	16.6	4.3	2,893
Vehicle related	35.7	0.9	5.6	32.7	17.6	7.5	2,620
Vulnerable persons check	58.9	3.5	8.3	15.4	9.8	4.0	1,685
% of population	47.7	0.9	20.4	8.9	22.2		-----

“Brown” includes “South Asian,” “Latin American,” “Arab” and “Other”

 

Toronto Street checks in the Canadian context

Toronto is certainly not the only Canadian city to observe gross racial disparities in police street check statistics. For example, Charest (2009) examined 163,630 identity or street checks carried out by Montreal police (SPVM) from 2001 to 2007. The data show a marked increase in the number of ID checks of Black Montreal residents over the study period. By 2006–2007, Black residents were four times more likely to be stopped and interrogated by the police than their representation in the population. In fact, 30% of all ID checks conducted by the Montreal police involved Black citizens, even though Black citizens comprised only 7% of Montreal’s population [Charest, 2009: 3 (original in French)]. As summarized by Eid et al. 2011: 26:

The Charest report highlighted “certain of the harmful consequences of the fight against street gangs and the repercussions of special squads like Avance and Éclipse on the volume and quality of ID checks of members of ethnic groups.” It notes that, between 2001 and 2007, the frequency of ID checks increased significantly in the city of Montréal (60% in Montréal, 125% in Montréal-Nord and 91% in Saint-Michel). In addition, it turns out that these observed increases are mainly attributable to stopping persons of “Black descent.”

Similarly, a recent inquiry conducted by the Nova Scotia Human Rights Commission found that within the Halifax region, Black people are grossly over-represented in police street check statistics. Although they represent only 3.7% of the population, Black people were involved in 18.4% of the street checks conducted by the local police between 2006 and 2017. In other words, Black people are five times more likely to appear in police street checks than their representation in the general Halifax population would predict. Other findings from the Nova Scotia inquiry reveal that:

• Between 2006 and 2017, the average annual street check rate for Black Halifax residents (156 per 1000) was more than six times higher than the street check rate for White residents (25 per 1000)
• While the number of completed street checks varied from year to year, the level of Black over-representation remained constant throughout the study period
• The over-representation in street check statistics is particularly high for Black males. The average annual street check rate for Black males (276 per 1000) was 6.9 times greater than the rate for White males (40 per 1000) and 22 times greater than the rate for White females (23 per 1000)
• Although the Black population of Halifax is younger than the White population, racial disparities cannot be explained by group-related age differences. In fact, Black people are grossly overrepresented in street checks across all age categories
• Racial differences in street checks cannot be explained away by criminal history or unique individuals (outliers) who are subject to multiple street checks
• Residential location does not reduce racial disparities in police street check statistics. Racial disparities exist in all Halifax census tracts. In fact, the street check rate for Black people was higher in low-crime, predominantly White communities than in high-crime communities with a large Black population
• Street checks appear unrelated to crime. Increases and decreases in street check activity are unrelated to changes in community-level crime rates over time (for more details see Wortley 2019).

Importantly, these findings are consistent with the argument that higher rates of police surveillance contribute to the criminalization of Nova Scotia’s Black community. Indeed, according to police records, approximately one-third of the Black male residents of Halifax (30.9%) were charged with at least one criminal offence between 2006 and 2017, compared to only 6.8% of White males (Wortley 2019).

Over the past few years, street check data has also been released to the public by a growing number of other Canadian police services. When racial data is included, the results (see OHRC 2016; Legal Aid Ontario 2016; Hoffman et al. 2015) consistently reveal that regardless of municipality, Black and other racialized civilians are much more likely to be subject to a street checks than members of the White majority:

• Between 2011 and 2014, the Ottawa police recorded 23,403 street checks. Results indicate that Black civilians were more than three times more likely

to be subject to a street check than their representation in the general population would predict. Middle Eastern civilians were two times more likely to be subjected to a street checks, while White people were under-represented (Yogaretham 2015)

• Between 2010 and 2015, the Hamilton police conducted over 18,500 street checks. Black people were four times more likely to be subject to a street check than their representation in the general population would predict (CBC 2015)

• In 2014, the London Police conducted 8,400 street checks. Black and Indigenous people were over three times more likely to be entered into the street check dataset than their representation in the London population (O’Brien 2016)

• The Peel Regional Police conducted 159,303 street checks between 2009 and 2014. Analysis of the street check data reveals that Black residents are three times more likely to be entered into the street check dataset than White residents (Grewel 2015).

The Toronto Police Service is clearly not the only urban Canadian police agency that engages in street checks or carding. Furthermore, as in Toronto, data from other Canadian cities suggest that Black residents are particularly vulnerable to this form of proactive police surveillance activity. However, what makes Toronto stand out from other police services is the high rate with which they used this tactic – especially between 2008 and 2013. Table 11 compiles data from various street check data releases, with 2016 Census population projections, to produce street check rates per 1,000 for various Canadian cities.

Due to population growth, the use of 2016 projections produces more conservative street check estimates than using projections for the exact years the street check data were collected. Nonetheless, the data reveal that the average street check rate for Toronto, between 2008 and 2013, was 125.6 per 1,000. This street check rate is far higher than the street check rates recorded by any other Canadian police service. During this period, Toronto’s street check rate (125.6 per 1,000) is 4.3 times higher than the rate for Halifax (29.4 per 1,000) – the Canadian jurisdiction with the next highest street check rate. Toronto’s rate is also 5.7 times greater than the rate for Calgary (21.9 per 1,000), six times greater than the rates produced by Edmonton and Peel Regional Police services, 20 times higher than the rate for the Ottawa Police Service, and 30 times greater than the rate for the Hamilton Police Service. This data clearly indicates that Toronto residents in general, and Black Toronto residents in particular, have historically been more likely to be exposed to police carding or street check practices than the residents of any other Canadian urban centres.

 

Table 11: Police street check rates, per 1,000, across various Canadian municipalities

City	Population size	Street check data collection period	# of street checks completed	Average # of street checks completed each year	Average annual street check rate per 1,000
Toronto	2,688,742	2008-2013	2,026,258	337,710	125.6
Calgary	1,230,915	2015	27,000	27,000	21.9
Edmonton	899,447	2009-2014	105,306	17,551	19.5
Peel Region	1,381,739	2009-2014	159,303	26,550	19.2
London	494,069	2014	8,400	8,400	17.0
Halifax	403,390	2006-2017	142,456	11,871	29.4
Montreal	1,753,034	2001-2007	163,630	23,376	13.3
Ottawa	934,243	2011-2014	23,403	5,850	6.3
Hamilton	747,545	2010-2015	18,500	3,083	4.1
Vancouver	603,502	2008-2017	97,281	9,728	16.1

Table 12 provides race-specific odds ratios for selected Ontario police services. As discussed earlier in this report, an odds ratio of greater than 1.00 indicates that the members of a specific racial group are over-represented in a jurisdiction’s street check data. An odds ratio of less than 1.00 indicates that a group is under-represented. For the purposes of this report, we consider an odds ratio of 1.50 or higher an indication that a group is significantly over-represented in police street checks. An odds ratio of 1.50 indicates that a group is 50% more likely to appear in the street check data than their presence in the general population would predict. The data reveal that Black people are significantly over-represented in the street check data for eight of the nine police jurisdictions for which data could be obtained. The only exception is the Ontario Provincial Police (OPP). Indeed, for Toronto, Peel, Ottawa, London, Kingston and Hamilton, Black people are three times more likely to appear in the street check data than their presence in the general population would predict. In both York Region and Waterloo Region, Black people are approximately 4.5 times more likely to appear in the street check data than the general population.

Indigenous people are over-represented in the street check data for London, Toronto (2014), Hamilton and the OPP. In other jurisdictions, Indigenous representation in the street check data is equal to their proportion of the general population. The findings indicate that people of Middle-Eastern descent are significantly over-represented in the street check data for the Ottawa, York Region and Peel Region. They are under-represented in all other police jurisdictions. The data further indicate that people of “Latin American” descent are significantly over-represented in the street check data from the Peel Regional Police Service. Interestingly, the data indicate that people of both Asian and South Asian descent are significantly under-represented in the street check data for all police services included in the current study (i.e., odds ratios of 0.5 or less). Finally, in most cases, the representation of White people in police street check data approximates their representation in the general population (see Table 12).

Table 13 presents the average annual street check rates, by race, for each police jurisdiction. The data indicate that for all police jurisdictions, the annual Black street check rate is between 3.0 and 4.6 times greater than the White street check rate. The only exception is the OPP. Importantly, the data also point to Toronto exceptionalism – particularly between 2008 and 2013. During this period, the annual Black street check rate for Toronto (352.6 per 1,000) was approximately five times greater than the Black street check rate for any other Ontario jurisdiction. In other words, although Black people were subject to higher street check rates in all Ontario jurisdictions, they were especially vulnerable to street checks in Toronto (especially between 2008 and 2013). It should also be noted that for each racial group, street check rates were much higher in Toronto between 2008 and 2013 than any other jurisdiction. In fact, the annual street check rate for White Torontonians during this period (122.6 per 1,000) is significantly higher than the annual Black street check rates for all other Ontario police services (see Table 13).

 

Table 12: Street check data from selected Ontario police services, odds ratios by race (odds ratios greater than 1.5 indicate significant over-representation in street check data)

Police service	Date range	Total # of street checks	White	Black	Indigenous	Middle-Eastern	South Asian	Asian	Latin American	“Brown”	Other racialized groups
Ottawa	2006–2016	140,750	0.8	3.2	1.1	2.8	0.2	0.3	1.3	---	---
London	2013–2016	36,775	1.0	3.0	2.3	0.7	0.2	0.2	0.3	---	---
York	2013–2016	19,945	1.1	4.6	1.2	2.0	0.8	0.4	1.2	---	---
Waterloo	2006–2016	43,716	1.0	4.7	1.1	0.7	0.3	0.3	1.1	---	---
Kingston	2006–2016	31,668	1.0	3.1	0.9	0.3	0.4	0.2	1.0	---	---
Peel	2006–2007	29,770	0.9	3.3	0.8	2.0	0.6	0.4	1.8	---	---
Peel	2008–2016	173,725	1.0	3.0	1.0	1.3	0.6	0.4	2.0	---	---
Toronto	2008–2013	1,846,930	1.0	2.9	---	---	---	---	---	0.9	0.3
Toronto	2014	23,160	1.0	3.1	3.0	---	---	0.3	---	0.7	---
Hamilton	2006–2016	12,565	0.9	3.2	2.2	0.7	0.3	0.4	1.0	---	---

 

Table 13: Average annual street check rates (per 1,000) from selected Ontario police services, by race

Police service	Date range	Total # of street checks	White rate	Black rate	Indigenous rate	Middle-Eastern rate	South Asian rate	Asian rate	Latin American rate	“Brown” rate	Other Racialized rate
Ottawa	2006–2016	140,750	12.3	48.4	16.6	41.4	3.6	4.5	18.1	---	---
London	2013–2016	36,775	24.9	72.3	57.6	16.9	4.0	4.9	6.5	---	---
York	2013–2016	19,945	5.1	20.7	5.5	9.3	3.6	1.9	5.3	---	---
Waterloo	2006–2016	43,716	7.9	36.2	9.3	5.7	2.5	2.2	8.3	---	---
Kingston	2006–2016	31,668	25.2	75.1	22.5	8.0	10.6	4.0	25.7	---	---
Peel	2006–2007	29,770	11.8	42.8	10.6	26.8	7.8	4.7	23.7	---	---
Peel	2008–2016	173,725	12.9	48.2	18.6	24.9	11.1	5.4	33.3	---	---
Toronto	2008–2013	1,846,930	122.6	352.6	---	---	---	---	---	105.7	36.33
Toronto	2014	23,160	8.6	26.9	27.4	---	---	2.8	---	5.8	---
Hamilton	2006–2016	12,565	2.1	7.1	4.8	1.6	0.6	0.8	2.1	---	---

Summary

The above analysis of officially recorded TPS street check data is completely consistent with results derived from both qualitative interviews and general population surveys. All three methodologies consistently reveal that Black people are grossly over-represented with respect to police stop, question and search activities. Furthermore, between 2008 and 2013, Toronto’s street check rate was much higher than the recorded street check rates for all other Canadian jurisdictions. This finding indicates that Black Toronto residents, compared to Black people who reside in other Canadian jurisdictions, have been particularly vulnerable to police racial profiling.

 

The impact of Ontario’s Street Check Regulation

On January 1, 2017, the Government of Ontario implemented new regulations designed to govern how the police conduct street checks (Ontario Regulation 58/16). It appears that this regulation has virtually eliminated traditional police street check practices across the province – including street checks conducted by the Toronto Police Service (Tulloch 2019). Figure 5 documents the number of street checks formally documented by the TPS between 2008 and 2019. The annual number of street checks conducted by the TPS rose gradually from 323,041 in 2008 to a high of 403,662 in 2012.

By 2012, street checks had become a public issue and the TPS was facing allegations of racial profiling. After an internal review of street check practices, and the adoption of a new street check policy, the number of street checks documented by the TSP plummeted to 189,536 in 2013 and to 24,364 in 2014 (PACER 2014). Apparently, a moratorium was put on street checks in 2015 and 2016, and no street checks were formally recorded by the TPS during this two-year period. Ontario’s street check regulation came into play in 2017. Since that time, the TPS has, according to official statistics, conducted only 28 street checks: 25 in 2017, two in 2018, and only one street check in 2019. Thus, according to official police statistics, street checks are a thing of the past.

The disappearance of street checks from official police statistics leads to a new research question: Has the elimination of street checks solved the problem of police racial profiling? Previous research strongly suggests that community members and police officials often have very different definitions of what constitutes a street check. While community members tend to define street checks as being stopped, questioned and searched by the police, the police traditionally focus on a much narrower range of technical activities associated with the collection of information for intelligence purposes (see Wortley 2019a). It is also clear that formal street checks are far less prevalent than investigative stops conducted by the police. For example, between 2013 and 2014, the Ottawa Police Service conducted over 81,000 traffic stops, compared to only 20,000 street checks (Foster et al. 2016). Thus, although street checks appear to no longer exist, we must further explore whether racial disparities in police stop, question and search activities (SQS) persist. Emerging evidence from three recent studies suggests that despite street check regulations, alarming racial differences still exist with respect to police SQS practices.

The Toronto Guns and Youth Violence Project involves in-depth interviews with 492 young people, 16–24 years of age, residing in economically disadvantaged, high-crime communities within the City of Toronto. All interviews were conducted in 2018 or 2019, a full year after Ontario’s street check regulations had come into effect. Almost three-quarters of the sample (74.2%) self-identified as Black. A third (32.1%) indicated that they had been arrested at least once in their life. All respondents were asked whether they had been stopped and questioned by the police in the past year. A total of 197 respondents (40.0% of the sample) reported that they had been stopped by the police at least once in the past year, and 19% stated that they had been searched. It should be noted that the 197 individuals, from this small sample, who indicated that they had been stopped by the police in the past year, is 64 times greater than the total number of official street checks (three) recorded by the Toronto Police Service during this same period.

The data from this project also indicated that Black respondents (44.6%) were much more likely to report being stopped by the police in the past year than respondents from other racial backgrounds (28%). Indeed, almost a third of Black respondents (31.9%) indicated that they had been stopped by the police on multiple occasions in the past year, compared to only 16.8% of respondents from other racial backgrounds. Furthermore, 27.9% of Black respondents indicated that they had been physically searched by the police in the past year, compared to only 14.6% of non-Black respondents. These racial differences are statistically significant (see Wortley et al. 2019).

Similar results were produced by a study entitled Perceptions of the Toronto Police and the Impact of Rule Changes Under Regulation 58/16: A Community Survey (Fearon and Farrell 2019). This study was conducted by Professor Gervan Fearon (Brock University) and Professor Carlyle Farrell (Ryerson University) on behalf of the Toronto Police Service’s PACER Committee and the Toronto Police Services Board (TPSB). Between November and December 2017, a structured questionnaire was administered to a random sample of 1,517 Toronto residents. One out of four respondents (24.4%) self-identified as Black, 23.3% self-identified as White, 11.7% self-identified as South Asian, 8.3% self-identified as East Asian, and 32.3% self-identified as the member of another racial group (Fearon and Farrell 2019: 9). The survey had three major areas of interest: 1) perceptions of the Toronto Police Service; 2) opinions towards and experiences with street checks; and 3) community members’ knowledge of Ontario’s new street check regulations that came into effect on January 1, 2017.

All respondents were asked the following question about street checks:

Carding or street checks refers to a police officer stopping and asking you a series of questions (e.g. your name, age, height, weight, names of your friends etc.) and recording this information on a contact card. The information is subsequently entered into a database for possible use in future criminal investigations. Have

you ever been carded by Toronto police officers?

The data indicate that 170 respondents – 11.3% of the sample – report being carded, or street checked, by the Toronto Police. However, my reanalysis of the data indicates that street check experiences are not evenly distributed across racial groups. Indeed, 19.1% of Black respondents report that they have been street checked by the TPS, followed by 10.3% of South Asian respondents, 5.5% of White respondents and 4.1% of East Asian respondents. In other words, Black respondents were 3.5 times more likely to report a police street check than their White counterparts. At the bivariate level, this racial difference is statistically significant. Furthermore, a multivariate, logistic regression analysis conducted by the authors reveals that Black racial background remains a strong, statistically significant predictor of police street checks even after taking other theoretically relevant factors into account. Indeed, after controlling for gender, age, education, income and neighbourhood crime rate, Black respondents were still 2.2 times more likely to be subject to a street check than White people (Fearon and Farrell 2019: 66–67).

All respondents who reported being street checked were asked when they had last been carded. Interestingly, 21% indicated that they had been street checked in 2017 – the year that the new street regulations came into play. It is also interesting to note that while this small survey of 1,500 respondents documented 34 street checks in 2017, the Toronto Police Service officially recorded only 25 street checks that year for the entire Toronto population of 2.7 million. This finding strengthens the argument that while official street checks have been effectively eliminated, the police may still be stopping and questioning people in a manner that is consistent with racial profiling. As Fearon and Farrell note:

Also interesting is the result that 21% of respondents reported being carded in calendar year 2017 (the year the new rules took effect) which compares to the 19% of respondents who reported being carded the previous year when the new rules were not yet in force (Table 48). One may, therefore, conclude that the imposition

of these new rules has not diminished the rate at which individuals are being carded in the City of Toronto (Fearon and Farrell 2019: 56).

The final survey to consider is a partial replication of a survey that was originally conducted in 1994 on behalf of the Commission on Systemic Racism in the Ontario Criminal Justice System. The original survey (discussed above), conducted by York University’s Institute for Social Research, involved a random sample of over 1,200 Toronto residents who self-identified as either White, Black or Chinese (over 400 respondents from each racial group). This survey, the first of its kind in Canada, asked respondents detailed questions about their experiences with and perceptions of the Canadian criminal justice system. Importantly, the 1994 survey was replicated in 2007, by the Hitachi Survey Research Centre at the University

of Toronto. Both the 1994 and 2007 surveys have resulted in several reports and publications in academic journals (see Commission on Systemic Racism 1995; Wortley 1996; Wortley et al. 1997; Wortley and Tanner 2003; Wortley and Tanner 2005; Wortley and Owusu-Bempah 2009; Wortley and Owusu- Bempah 2011; Owusu-Bempah and Wortley 2013; Wortley and Owusu-Bempah 2016).

The most recent survey was conducted by Environics Research, on behalf of the Canadian Association of Black Lawyers and Legal Aid Ontario, using an online methodology (see https://cabl.ca/race-and-criminal-injustice-new-report-from-cabl-ryerso…-

and-the-university-of-toronto-confirms-significant-racial-differences-in-perceptions-and-experiences-with-the-ontari/). Environics surveyed 1,450 residents from the Greater Toronto Area (GTA) who were 18 years of age or over. Quotas were set to ensure that the final sample consisted of at least 450 respondents from each of three racial groups: 450 of the respondents identified as Black, 450 as Asian (including people of Chinese, Korean, Japanese backgrounds) and 550 as White/Caucasian. The survey was conducted between May 16 and July 29, 2019 – more than two years after the implementation for the Ontario street check regulations.

Many of the survey questions asked in 2019 were identical to the questions asked in both 1994 and 2007. This allows for a trend analysis, or a comparison of how Black, White and Asian people responded to questions about the police and the criminal courts over the past 25 years (Wortley and Owusu-Bempah 2020).^[20]

As with the earlier versions of the survey, all respondents to the 2019 study were asked if they had been stopped and questioned by the police – as a pedestrian or while driving in a vehicle – over the past two years. The results reinforce that Black people are much more vulnerable to police surveillance than people from other racial groups. Once again, these findings are highly consistent with allegations of racial profiling. Overall, 40.4% of Black respondents report being stopped by the police at least once in the past two years, compared to only 24.7% of White and 24.9% of Asian respondents. However, the results further reveal that Black respondents are particularly vulnerable to multiple police stops. One-quarter of Black respondents (26.2%) report that they have been stopped two or more times in the past two years, compared to only 11.8% of Asian and 9.8% of White respondents. These racial differences are highly statistically significant (see Table 14).

Additional analysis reveals that Black males are particularly vulnerable to police stops. Overall, half of all Black males (49.2%) report being stopped by the police at least once in the past two years, compared to only 25.9% of White males and 29.8% of Asian males. Black males are also much more likely to report multiple police stops. A third of Black male respondents (34.2%) report two or more police stops in the past two years, compared to only 15.6% of Asian and 9.1% of White males. As a further illustration, 21 respondents in the sample indicated that they had experienced 10 or more police stops in the past two years. Fifteen of these 21 respondents (71.4%) were Black males, even though Black males represent only 13.3% of the total sample. These racial differences are highly statistically significant (see Table 15).

Although men are much more likely to be stopped by the police than women, racial differences in exposure to police stops also exist among women (see Table 16). In general, Black women experience more police stops than either White or Asian women. For example, 33.8% of Black female respondents report at least one police stop in the past two years, compared to only 23.4% of White and 20.6% of Asian females. These racial differences are statistically significant. It is also important to note that Black females (20.2%) are more likely to report multiple police stops than either White (9.1%) or Asian (15.6%) males.

Importantly, multivariate statistical analysis reveals that Black racial background remains a strong predictor of police stops after controlling for other theoretically relevant variables including respondent age, education, income, immigration status, driving frequency, late-night leisure activities, community crime and disorder, violent victimization, illegal drug use and criminal history. After controlling for other variables, the data indicate that Black people are

1.9 times more likely to report one or more police stops, 2.8 times more likely to report two

or more stops, 7.3 times more likely to report three or more stops, and 9.0 times more likely

to report four or more police stops. Additional analysis reveals that – after other variables have been taken into statistical account – Black people are 6.1 times more likely to be searched by the police during a stop incident (Wortley and Owusu-Bempah 2020).

 

Table 14: Percentage of respondents who report being stopped and questioned by the police during the past two years (combined traffic and pedestrian stops), by respondent race (2019 CABL Survey)

Number of stops	Black	White	Asian
Not stopped	59.6	75.3	75.1
Stopped once	14.2	14.9	13.1
Stopped two or more times	26.2	9.8	11.8
Sample size	450	550	450

x²=60.168; df=4; p >.001

 

Table 15: Percentage of male respondents who report being stopped and questioned by the police in the past two years (combined traffic and pedestrian stops), by respondent race (2019 CABL Survey)

Number of stops	Black	White	Asian
Not stopped	50.8	74.0	70.3
Stopped once	15.0	16.8	14.2
Stopped two or more times	34.2	9.1	15.6
Sample size	193	285	212

x²=51.723; df=4; p >.001

 

Table 16: Percentage of female respondents who report being stopped and questioned by the police during the past two years (combined traffic and pedestrian stops), by respondent race (2019 CABL Survey)

Number of stops	Black	White	Asian
Not stopped	66.1	76.6	79.4
Stopped once	13.6	12.8	12.2
Stopped two or more times	20.2	10.6	8.4
Sample size	257	265	238

x²=18.747; df=4; p >.001

Tables 17 and 18 compare police stops across jurisdictions. The results suggest that racial differences in reported police stops are statistically significant across the GTA. However, racial differences are much more pronounced among City of Toronto respondents than respondents who live elsewhere in the GTA (i.e., Peel, Durham, York and Halton regions). Black Toronto residents appear to be particularly vulnerable to multiple police stops. For example, 32.8% of Black Toronto residents report that they have been stopped by the police on multiple occasions in the past two years, compared to only 18.7% of Black respondents who reside in other areas of the GTA. This finding is completely consistent with official data, discussed above, which demonstrates that the TPS’s historical street check rate is much higher than other Canadian police services.

 

Table 17: Percentage of respondents who report being stopped and questioned by the police during the past two years, by respondent race (Peel, Durham, York and Halton residents) (2019 CABL Survey)

Number of stops	Black	White	Asian
Not stopped	64.6	72.8	69.9
Stopped once	16.7	17.9	16.9
Stopped two or more times	18.7	9.3	13.2
Sample size	209	302	219

x²=9.610; df=4; p >.048

 

Table 18: Percentage of respondents who report being stopped and questioned by the police during the past two years, by respondent race (City of Toronto residents only) (2019 CABL Survey)

Number of stops	Black	White	Asian
Not stopped	55.2	78.2	80.1
Stopped once	12.0	11.3	9.5
Stopped two or more times	32.8	10.5	10.4
Sample size	241	248	231

x²=58.357; df=4; p >.001

As discussed above, the 2019 survey is a replication of similar studies conducted in both 1994 and 2007. Table 19 and Figure 6 reveal the percentage of respondents who report being stopped by the police, during the past two years, for each year the survey has been conducted. Two important findings emerge. First of all, across all surveys, Black respondents report a much higher frequency of involuntary police contact than respondents from other racial groups. Secondly, the frequency of police stop activity increased significantly between 1994 and 2019. For example, in 1994, only 16.8% of Black respondents indicated that they had been stopped by the police on two or more occasions in the past two years. This figure rises to 21.0% in 2007 and 26.2% in 2019. Similarly, in 1994, only 4.7% of Asian respondents indicated that they had been stopped by the police on two or more occasions, compared to 12.5% in 2007 and 11.8% in 2020. By contrast, the stop rate for White people has remained relatively constant. In other words, according to these survey results, racial disparities in police stop activities have become even more pronounced over this 25-year period.

Summary

These findings are particularly important in light of Ontario’s new Street Check Regulation (O.Reg. 58/16). Although official statistics suggest that street checks were eliminated after the implementation of these regulations, the results of this 2019 survey, conducted more than two years after the street check regulation was imposed, suggest that Toronto-area police continue to stop and question civilians at a high rate. Furthermore, Black people continue to be stopped and questioned by the police at a rate far higher than people from other racial groups. Thus, although the Ontario Street Check Regulation may have eliminated the formal documentation of street checks, it has not decreased racial disparities in police stop and question activities. Eliminating the street check paper trail has not eliminated all evidence of racial profiling. This finding also supports the argument that the police should be mandated to collect information on all police stops – not just those that result in a formal street check. We will return to this argument in the final section of this report.

 

Table 19: Percentage of respondents who report being stopped by the police in the past two years, by respondent race and year of survey (2019 CABL Survey)

Number of stops	Black			White			Asian
	1994	2007	2019	1994	2007	2019	1994	2007	2019
None	71.9	66.1	59.6	81.8	78.8	75.3	85.4	71.9	75.1
One	11.3	12.9	14.2	10.2	13.9	14.9	9.9	15.6	13.1
Two or more	16.8	21.0	26.2	8.0	7.3	9.8	4.7	12.5	11.8

Summary of the research evidence

As documented above, findings from qualitative studies, survey research and an analysis of official TPS street check data all lead to one conclusion: the Black residents of Toronto are subjected to much higher rates of police surveillance than members of the White majority or members of other racial minority groups. In my opinion, this constitutes strong evidence that the Toronto Police Service has engaged in racial profiling. Furthermore, research conducted over the past two years strongly suggests that the TPS still engages in racially biased stop, question and search tactics, despite the Ontario government’s efforts to regulate street checks. In the next section of the report, we review the argument that street checks and investigative police stops are an effective crime prevention strategy. The subsequent sections explore the various consequences associated with racial profiling. Analysis reveals that the consequences of racially biased police practices far outweigh any potential public safety benefits.[21]

 

The perceived benefits of police stops

In recent years, North American police officials have come to increasingly defend “stop and frisk” tactics and “street checks” as effective crime prevention strategies (Zimring 2012). They have argued that these tactics are particularly effective with respect to combating street gangs and reducing gun violence. Arguments in favour of stops/carding have included the following points:

• Police stop, question and search (SQS) activities can result in the identification and confiscation of both illegal hand guns and illegal drugs. Removing drugs, guns and offenders from the street will ultimately reduce violent crime and save lives.

• Even when unproductive, police stops are a deterrent. Stopping and searching civilians, especially the residents of high-crime communities, will send the message that the police are taking violence and drug crime seriously. Offenders will come to know that the certainty of police detection and punishment is high, and this will eventually deter them from carrying drugs or guns in public. This deterrent effect will reduce the likelihood of violent, gun-related crime and make communities safer.

• Stop, question and search tactics hold offenders accountable. Stopping civilians and demanding identification will help police officers identify offenders who have warrants out for their arrest. It will also help the police identify offenders who are in violation of parole, probation and other court-imposed conditions (including pre-trial release conditions). By uncovering breach-of-condition violations, stop and search tactics can increase control over offenders who do not respect community sanctions. This increased control will prevent more serious forms of offending.

• Gang members and drug traffickers often do not reside in the communities that they “terrorize.” Stop and frisk practices can help identify trespassers and keep them out of public housing developments. Such practices will reduce both crime and fear of crime in affected communities.

• Stopping and documenting civilians (carding) can improve police intelligence. It can, for example, provide information on who resides in particular neighbourhoods or who frequents particular crime “hotspots.” Carding can also help identify criminal “associates” and link offenders to potential witnesses, victims and accomplices. Such intelligence can help the police solve crimes or decide what individuals or groups should be targeted for further investigation.

Unfortunately, such police arguments rarely consider the legality of these stop, question and search tactics. Even if effective – many have argued that these tactics cannot be condoned because they clearly violate basic civil rights (Tanovich 2006). It was this very logic that Judge Shira Scheindlin of the U.S. District Court for the Southern District of New York applied when she ruled that the NYPD’s Stop, Question and Frisk (SQF) policy was unconstitutional (Bergner 2014). After all, one could argue that if we eliminated all civil rights, and all rules of procedural justice, we would be in a better position to fight crime. Police would be better able to identify illegal activity and arrest offenders if they could only stop, detain, question and search any person at any time for any reason. They could also fight crime more effectively if they had the power to immediately conduct warrantless searches of homes and vehicles without having to explain or justify their actions. Such tactics, even if highly effective at detecting crime, apprehending criminals and deterring future offending, would violate the general principles of democracy and the rule of law.

Philosophical arguments aside, research evidence on the actual effectiveness of police stop, question and frisk tactics is quite limited. Canadian data is virtually nonexistent. Some American studies, however, do suggest that targeted, broken-windows policing strategies – including hot-spots policing and stop and frisk tactics – are responsible for significant crime declines in cities like New York, New Orleans and Los Angeles (see Land 2015; Braga 2015; Braga 2012; Durlauf and Nagin 2011). Skeptics, however, argue that most studies are inconclusive and have not taken into account other factors that may explain recent crime reductions – including community crime prevention initiatives and anti-violence movements that have emerged within poor, racialized communities. Skeptics also maintain that over the past two decades, violent crime has also declined in many urban centres that do not employ aggressive stop, question and frisk tactics (see Doob and Gartner 2017; White and Fradella 2016; Apel 2015; Meares 2014; Tonry 2011).

Recent analysis of crime data in the United States also reveals that the crime prevention qualities of police stop, question and frisk (SQF) practices are rather limited. For example, Rosenfeld and Fornago (2012) examined the impact of SQF on robbery and burglary rates in New York City between 2003 and 2010. Their multivariate analysis controlled for a number of other factors including, neighbourhood disadvantage and stability, percentage of Black people in the community and overall crime trends. Results suggest that SQF did not impact burglary rates and had only a small and inconsistent impact on robbery rates. The authors conclude that based on the study results, one can’t conclude that stop, question and frisk (SQF) has no impact. However:

…if there is an impact it is so localized and dissipates so rapidly that it fails to register in annual precinct crime rates, much less the decade-long city-wide crime reductions that public officials have attributed to the policy. If SQF is effective, but its effects are highly focused and fleeting, policy makers must decide whether expansions in a policy that already produces 700,000 police stops a year are warranted, especially given the ongoing controversy regarding the disproportionate impact of SQF on racial and ethnic minorities and the possibility that it reduces police legitimacy, which may erode its crime-reduction effects over the long term (Rosenfeld and Fornago 2012: 117-118).

In another recent study based in New York City, Weisburd et al. (2015) found that controlling for a variety of other community-level factors, the approximately 700,000 stop, question and search encounters conducted by the NYPD each year contribute to only a small, two per cent reduction in crime. The authors note that attributing even this small crime reduction to SQF is problematic because it is impossible to distinguish the impact of police stops from their mere presence in the community. In other words, the impact of SQF tactics on actual crime rates is likely much smaller than advocates claim. The authors conclude that despite the fact that police stop and frisk tactics may have a small crime reduction effect:

The aggressive use of SQFs could erode citizens’ willingness to report crime to, or to cooperate in investigation and intelligence gathering with, the police…The question is whether this approach (SQFs) is the best one for crime prevention at hot spots and whether its benefits are greater than the potential negative impacts on citizen evaluations of police legitimacy (Weisburd et al. 2015: 50).

Interestingly, despite dire warnings, new regulations and the dramatic decline of stop and frisk activities in New City have not resulted in significant increases in violent or property offending. In fact, crime rates have continued to decline to historic lows (see Chaun et al 2015; Wegman 2015; Bostock and Fessenden 2014). For example, in 2003, the NYPD conducted approximately 160,000 stop, question and frisk investigations. There were 597 homicides that year. In 2011, the NYPD conducted 685,000 SQFs and the number of homicides dropped to 515. After being ruled unconstitutional, the number of SQFs dropped to only 47,000 in 2013. However, the number of homicides continued to decline – only 333 murders were recorded that year (Weisburd et al. 2015).

A similar situation seems to be emerging in Toronto. As the result of public pressure and the implementation of a new policy, the number of contact cards completed by the Toronto Police Service dropped by over 75% between 2012 and 2014 (see Rankin and Winsa 2014). However, Toronto’s rate of violent crime continued to decline over this two-year period. In 2015, violent crime had dropped to its lowest level since the mid-1960s (see Boyce 2015).

While Canadian data is not available, we also know from American and British research that that police stop, question and search activities rarely uncover direct evidence of criminal activity. Some have likened it to looking for a needle in a haystack. For example, between

2004 and 2012, the NYPD conducted approximately 4,135,000 stop, question and frisk investigations.^[22] Only 46,000 of these stops – a mere 1.1% – resulted in the seizure of illegal contraband and only one out of every 1,000 stops (0.01%) resulted in the seizure of an illegal firearm (see Torres 2015). A similar picture emerges in England. As documented

by Bowling and Phillips (2007), the per capita police stop rate in England and Wales is approximately 6.5 times greater for Black people than for White people. However, the hit rate for both Black and White people is almost identical – about one per cent of stops for both groups result in the discovery of illegal activity. The fact that these hit rates do not vary by race might be interpreted as an absence of racial bias. However, the hit rate figures, combined with the per capita stop and search rate, sheds light on another reality: every year, innocent Black people in England and Wales are 6.5 times more likely than innocent White people to endure an unnecessary stop and search encounter with the police. This fact could undermine public confidence in the police – a topic addressed further in the next section.

In Toronto, it has been recently argued that the elimination of street checks has contributed significantly to a rise in violent crime – including shootings and homicides. For example, in 2012, the TPS conducted 403,662 street checks. By contrast, in 2018, the TPS conducted only two street checks (a decline of 403,660 street checks over a six-year period). However, over this same period, the number of homicides committed in Toronto rose from 57 in 2012 to 96 in 2018 – a difference of 39 homicides (a 68% increase). However, even if we accept

the argument that all 39 additional homicides would have been prevented if street checks numbers had remained high, street checks would still emerge as a highly inefficient crime prevention method. Indeed, according to these numbers, it would take 10,350 street checks to prevent one Toronto homicide.

Similarly, according to TPS statistics, the number of shootings in Toronto rose from 213 in 2012 to 424 in 2018 – a difference of 211 shootings (a 99% increase). Even if we buy that all of this increase in shootings would have been prevented by street checks, the data suggest that it would take 1,913 street checks to prevent just one shooting. Thus, when we consider the negative impact that street checks have had on the Black community, the value of street checks as a crime prevention strategy must be questioned.^[23]

At the same time, we must not completely handcuff the police. We must remember that racialized communities are sometimes negatively impacted by high levels of violence and, like all people, desire police protection when it is needed. Nonetheless, even advocates of stop, question and search tactics are now arguing that aggressive, arbitrary police stops of all “available” civilians must be dramatically reduced (Zimring 2012). Furthermore, the use of documented police stops to evaluate officer performance is a failed practice. In cities like New York and Toronto, such policies dramatically increased the number of stops being conducted, diminished the usefulness of these encounters, and greatly damaged police-community relations (White and Fradella 2015). A more targeted, community-driven approach is required.

The implementation of focused deterrence strategies is one possible solution. Proponents argue that these strategies can reduce serious violence while simultaneously improving the often strained relationship between the community and the police. To begin with, focused deterrence directly involves community leaders, social service providers and regular citizens in the planning and implementation of violence-prevention initiatives. Partnerships between the police and community improve the transparency of law enforcement activity, and provide local residents with both a voice and a role in crime prevention work. By using various analytical tools – including community stakeholders – to identify individuals, groups and gangs central to local crime problems, these initiatives are highly focused on very high-risk people. In other words, they do not subject law abiding citizens to indiscriminate police surveillance and investigation.

Police also make concerted efforts to communicate with targeted individuals and warn them of the consequences of continued criminal behaviour. They are also made aware of community-based programs and services that will help them exit the criminal lifestyle. Community members tend to appreciate the fairness of offering youthful offenders the opportunity to change their behaviour rather than simply relying on arrest and prosecution.

Finally, focused deterrence focuses on issues of procedural justice and legitimacy. Targeted offenders are treated with dignity and respect. Preliminary evaluation findings suggest that the focused deterrence approach has been successful at lowering crime rates and improving community confidence in police operations (Goff et al. 2015; Corsaro and Engel 2015; Brunson 2015; Land 2015). Such programs could represent the balance between public safety concerns and civil rights that Canada deserves.

 

The consequences of racial profiling

The social and psychological consequences of racial profiling and police stop, question and search activities have been extensively documented (see reviews in White and Fradella 2016; Doob and Gartner 2017; Glaser 2015; Harris 2002; Hart et al. 2008; Tanovich 2006; Ontario Human Rights Commission 2003; Tator and Henry 2006; Bowling 2011). In sum, people who perceive that they have been the victim of racial profiling often feel humiliated, frightened, angry, depressed, frustrated and helpless.

Previous research further suggests that racial profiling – as with other types of racism – is a quality-of-life issue and that frequent exposure to police stop and search activities can have a negative impact on both physical and mental health (see White and Fradella 2016; Glaser 2015; Paradies et al. 2015; Watts 2014; Freeman 2012; Pieterse et al. 2012). The focus of this section of the report, however, is to clearly document the consequences of racial profiling with respect to the criminal justice system.

First of all, logic dictates that there is a direct relationship between how closely people are monitored by the police and how likely they are to get caught for breaking the law. In other words, if racial minorities are systematically stopped and searched more frequently by the police than White people, they are also more likely to be detected and arrested for illegal activity than White people who engage in exactly the same criminal behaviour. Thus, racial

differences in police stop and search activities directly and significantly contribute to the over-representation of certain racial groups – Black and Indigenous Canadians in particular – within the Canadian criminal justice system (Wortley and Owusu-Bempah 2016; Owus-Bempah and Wortley 2014; Wortley and Owusu-Bempah 2011a).

In the United States, numerous academics have demonstrated that racially biased police stop and search practices, implemented as part of the War on Drugs, directly contributed to the dramatic increase in the over-representation of Black and Hispanic people within the American correctional system (Gabbidon and Greene 2005; Walker et al. 2004; Mauer 1999; Cole 1999; Tonry 1995; Mann 1993). Critics further argue that differential law enforcement practices help explain why the majority of people convicted

of drug crimes in the United States are Black and Hispanic, even though the vast majority

of drug users and traffickers are White (Harris 2002; Tonry 1995).

The hypothetical data provided in Table 20 provides a simple illustration of how racial profiling can impact the over-representation of racial minorities in the justice system. Let us assume that a particular community has 2,000 residents aged 18 to 24 years. Let us also assume that 1,000 of these neighbourhood youth are Black and the other 1,000 are White. The rate of carrying illegal drugs for personal use is exactly the same for each racial group (20%). In other words, the community has 200 Black drug users and 200 White drug users. However, due

to informal racial profiling practices by the local police, 50% of the Black youth in the neighbourhood will be stopped and searched by the police during the course of the year, compared to only 10% of the White youth. As a result, 100 of the 200 Black drug users will be detected and charged with drug possession by the police, compared to only 20 of the 200 White drug users. Thus, the profiling of the Black population will ensure that Black youth are more likely to be caught for breaking the law than their White counterparts. This process will ultimately lead to the over-representation of Black youth in the criminal justice system. Furthermore, at the end of the year, the police may review their drug arrest statistics and note that 100 of the 120 drug arrests (83%) that they made in this neighbourhood over the past year involved Black youth, a statistic that will serve to further reinforce racial profiling practices. In other words, racial profiling can become a self-fulfilling prophesy.

 

Table 20: Hypothetical distribution of youth in a fictional community

Characteristics and outcomes	Black youth	White youth
Number in community	1,000	1,000
Number using illegal drugs	200	200
Percentage who use drugs	20%	20%
Number searched by the police in the past year	500	100
Number detected with drugs and charged	100	20
Percentage of all drug users detected by the police	50%t	10%

This, of course, may be an overly simplistic example, but it does demonstrate how racial profiling can potentially contribute to the over-representation of racial minorities in the criminal justice system. Indeed, a recent investigation conducted by the OHRC indicates that Black Toronto residents are grossly over-represented in a wide range of discretionary offenses – including drug possession. The authors argue that this over-representation is directly related to racial profiling and TPS over-surveillance of Black communities (Wortley and Jung 2020). It is also likely that racial profiling and biased police surveillance practices directly contribute to the gross over-representation of Black people in TPS use of force incidents. The greater the overall exposure to police contact, the greater the likelihood that some police encounters will deteriorate into use of force. Furthermore, the results of the OHRC’s investigation reveals that, compared to incidents involving White people, use of force incidents involving Black people are more likely to result from proactive policing (i.e., police stops) than calls for service (see Wortley and Laniyonu 2020).

While racial profiling may contribute to the over-representation of racialized people within the justice system, over-representation in turn causes immense social and economic harm to racialized communities and families. Scholars often refer to such harm as collateral damage. The collateral damage associated with disproportionate racial minority incarceration, for example, can include economic hardship, social stigmatization, childhood trauma and underdevelopment, family dissolution, and poor physical and mental health (see Pinard 2010; Western and Wildeman 2009; Foster and Hagan 2009; Pager 2009).

A second major consequence of racial profiling is that negative police stop and search experiences can undermine the legitimacy of the police and the broader criminal justice system. Indeed, a growing volume of American (White and Fradella 2016; Glaser 2015; Zhao et al. 2015; Coraso et al. 2015; Gau 2012; Unnever et al. 2011; Gabbidon et al. 2011; Mbuba 2010; Higgins et al. 2010; Gibson et al. 2010; Slocum et al. 2010; Gabbidon and Higgins 2009; Lurigio et al. 2009; Higgins et al. 2008; MacDonald et al. 2007; Weitzer and Tuch 2006; Reitzel and Piquero 2006; Skogan 2006; Skogan 2005; Engel 2005; Hagan et al. 2005; Weitzer and Tuch 2005; Tyler 2005; Rosenbaum et al. 2005; Brown and Benedict 2002; Weitzer and Tuch 2002), British (Bradford 2011; Bradford et al. 2009; Bowling and Phillips 2002) and Canadian studies (Sprott and Doob 2014; Cao 2011; Wortley and Owusu-Bempah 2011a; Wortley and Owusu-Bempah 2011b; Wortley and Owusu-Bempah 2009; O’Connor 2008; Wortley et al. 1997; Wortley 1996) have firmly established that certain racial minority groups, including Black, Hispanic and Indigenous people, have much more negative views about the police and the wider justice system than White people.

Furthermore, additional research suggests that much of the racial disparity in perceptions of the criminal justice system can be explained by disproportionate exposure to police stop and search activities. Indeed, a number of studies have now established that people who are frequently stopped and searched by the police have less trust in the justice system and are more likely to view criminal justice institutions as biased. Research also suggests that indirect or vicarious exposure to racial profiling (through the experiences of family members and friends) can also have a negative impact on perceptions of the police, criminal courts and corrections (Zhao et al. 2015; Bradford 2011; Gabbidon et al. 2011; Wortley and Owusu-Bempah 2011b; Gibson et al. 2010; Rosenbaum et al. 2005; Bradford et al. 2009; Wortley and Owusu-Bempah 2009; Weitzer et al. 2008; Skogan 2006; Weitzer and Tuch 2005; Tyler and Wakslak 2004; Fagan and Davies 2000; Wortley et al. 1997; Wortley 1996).

Importantly, these same studies suggest that racial groups who have the highest level of involuntary contact with the police tend to have the most negative views of the police and the least trust in the justice system (see Wortley and Owusu-Bempah 2009). For example, Fearon and Farrell’s 2019 survey of Toronto residents found that, consistent with official police statistics, Black people were more likely to be subject to police street checks than people from other racial backgrounds. They also found that people who had been subjected to street checks were less trustful of the police than those who had not been subjected to such police practices. It is thus not surprising that in this survey, Black people expressed far less trust and confidence in the police than respondents from other racial backgrounds (Fearon and Farrell 2019).

The 2019 CABL survey of Toronto residents, discussed above, produced similar results. In general, the survey found that, compared to their White and Asian counterparts, Black people have far less trust and confidence in the police and are much more likely to perceive the police as racially biased. A multivariate analysis reveals that Black distrust in law enforcement can be partially explained by higher rates of both direct and vicarious experiences with police stop and search practices (Wortley and Owusu-Bempah 2020).

The overall evidence suggests that police racial profiling helps explain why Black Canadians view the police as more racially biased than any other sector of Canadian society. For example, the 2015 Black Experience Project survey asked respondents the following question:

To what extent do you think that Black people in the GTA experience unfair treatment in the following situations because they are Black. Would you say this happens frequently, occasionally, rarely, or never?

The results reveal that 86.3% of respondents feel that Black people are frequently subject to unfair police treatment. By contrast, only 66.9% of respondents feel that Black people are subject to frequent unfair treatment within the employment sector, and only 40.8% believe they are frequently subjected to unfair treatment within the educational system (see Figure 7).

Negative perceptions of the justice system and/or a lack of trust in the police have profound consequences for the functioning of the justice system. For example, a number of researchers have found that people with poor perceptions of the justice system are less likely to cooperate with police investigations and provide testimony in court (Gibson et al. 2010; Slocum et al. 2010; Tyler and Fagan 2008; Hart et al. 2008; Brunson 2007; Stewart 2007; Tyler 2006; Brown and Benedict 2002). Furthermore, a number of theoretical perspectives, including Tyler’s theory of Legitimacy and Compliance (Tyler 2006) and Sherman’s Defiance Theory (Sherman 1993) maintain that people with poor perceptions

of the police and broader justice system are less likely to obey the law than those who perceive the system as legitimate. Indeed, an increasing number of empirical studies are providing strong empirical evidence in support of this hypothesis: people who perceive a high level of racial bias or discrimination within society are more likely to engage in criminal behaviour than others (see Burt 2015; Coroso et al. 2015; James and Warner 2015; Augustyn and Ward 2015; Penner et al. 2014; Intravia et al. 2014; Martin et al. 2010; Bouffard and Piquera 2010; Wortley and Tanner 2008; Stewart 2007; Kane 2005; Caldwell et al 2004; Tyler and Wakslak 2004).

In other words, individuals are better able to justify their criminal actions and neutralize their guilt when they feel that the justice system – and society itself – is fundamentally unfair or biased. Furthermore, because of their poor relationship and perception of the police, some racialized individuals feel that they must take personal responsibility for their own safety and resort to street justice, further increasing the level of violence in disadvantaged racial minority communities (see Coroso et al. 2015; Intravia et al. 2014; Stewart 2007). In sum, racial differences in stop and search activities contribute to negative perceptions of the police and justice system among racialized civilians. These negative perceptions, in turn, result in a lack of cooperation with the police and courts and ultimately contribute to racial minority involvement in crime and violence.

In sum, the research literature clearly illustrates that street checks – otherwise known

as police stop, question and search tactics – are not harmless and should thus not be condoned in the name of public safety or crime prevention. The empirical evidence strongly suggests that the costs are greater than the benefits. Indeed, racial biases with respect to police surveillance activities can have a hugely detrimental impact on individuals, communities, and the operation of the criminal justice system. Eminent Canadian criminologists Tony Doob and Rosemary Gartner, after reviewing the extensive academic literature on police stops, also came to this conclusion:

The police have a number of important roles to play in public safety and in the operation of the criminal justice system. The findings that we cite here which suggest that certain approaches to crime and public protection either do not work or have overall negative impacts should be placed in this larger context. Perhaps the conclusion that one could come to that might be the least controversial would be the need to monitor and evaluate police policies related

to street stops to ensure that the benefits outweigh the possible harm that could come from such interventions. This is the same conclusion that one could apply just as easily to medical or educational interventions as police interventions.

An important point to remember is that one cannot conclude something is effective, just because assertions are made that it is. Data are important. And sometimes, the findings are complex. Certain kinds of activities of the police can have quite positive effects if the community is engaged in an appropriate fashion. But looking at the issue that we started with – street stops by the police of people who have not apparently committed an offence – it is quite clear that to us that it is easy to exaggerate the usefulness of these stops, and hard to find data that supports the usefulness of continuing to carry them out. This is not to say that the police should not be encouraged to continue to talk to people on the street. But evidence that it is useful to stop, question, and/or search people and to record and store this information simply because the police and citizens “are there” appears to us to be substantially outweighed by convincing evidence of the harm of such practices both to the person subject to them and to the long term and overall relationship of the police to the community (Gartner and Doob 2017: A22).

 

A note on the retention of carding or street check data

One issue associated with the practice of carding or street checks is the retention of the personal information collected from these types of police-civilian interactions. As noted above, the police argue that this information is of high value with respect to future criminal investigations. It may, they argue, help identify crime victims, suspects and witnesses. Recently, it has also been argued that the retention of this type of intelligence-related data may help the police investigate and ultimately solve “cold cases.” Critics, however, have argued that the retention of personal information in “known to police” datasets can cause serious damage to individuals. Furthermore, since Black people and other racial minorities are, in most cases, grossly over-represented in contact card or street check datasets, they are also much more likely to suffer from any negative consequences associated with the retention of this information.

Unfortunately, there has been no published research on exactly how – and how frequently – street check data has historically been used by police services or the extent that the use of street check data has impacted racialized individuals or communities. In order to systemically assess the impact of street check data, the police would have to dramatically increase transparency and release information to researchers. Important questions that can only be answered with improved data access include:

1. Historically, who has access to street check data and how often is this information used? For example, to what extent are street check data accessed by front-line patrol officers and criminal investigators? For what purposes? Do officers, for example, routinely access such data when they conduct traffic stops or respond to calls for service? To what extent do investigators use street check data to identify suspects or witnesses?

2. To what extent are street check data shared with outside police and public security agencies (e.g., CSIS, the Canadian Border Security Agency, American security agencies, etc.)?

3. To what extent are street check data shared with members of the public as part of employment, education or volunteer-related security checks? To what extent does the release of this information limit employment, educational and volunteer opportunities?

4. What type of information is provided within street check records? Of importance may be the notes, comments or observations police officers make during street checks about the civilians they interact with. For example, do officers make comments about the demeanour of civilians, their level of cooperation with the police, the people they are associating with, etc.?

5. To what extent does the information contained within street checks impact subsequent police decision-making? Does the information contained within street checks have an impact on how harshly or leniently civilians are treated during future encounters with the police?

Although relevant large-scale data about the uses – and possible misuses – of street check information have not been made available to the public or researchers, concerns have been raised. The following examples serve to illustrate how the retention of street check data may have a negative impact on civilians:

• In April 2012, Andrew Tysowski, a Carleton University student, was stopped by an Ottawa police officer for running a red light. When asked, Tysowski told the officer he had never been in trouble with the police before. However, after conducting a computer check in his patrol car, the officer allegedly returned to Tysowski and issued him a traffic ticket. According to Tysowski, the officer called him a liar and told him: “Don’t be an asshole the next time. Anyone else it would be a warning, but because of your record from 2006, I am giving you a ticket.”
  
  
  
  Concerned by the interaction and the idea that he might have a police record, Tysowski eventually filed a complaint with the Ontario Independent Police Review Directorate (OIPRD). When the OIPRD released their report into the complaint, Mr. Tysowski learned that his “record” stemmed from an incident, in 2006, when he had been taken off a bus by officers and questioned about a robbery. Although cleared of all suspicion, the officers involved produced a street check about the incident where they stated that they were making a note of Tysowski’s negative attitude towards the police in the event he should ever apply to join the Ottawa Police Service.
  
  
  
  Tysowski stated that he wanted his street check record expunged because it could “show up anywhere” and could negatively impact his future opportunities and interactions with the police. This case provides an example of where negative subjective information from an earlier street check was seemingly used to justify harsher police treatment during a traffic stop. It is also clear that the information on the street check could have hindered Tysowski’s subsequent employment opportunities (Adam 2012; Davies 2015).

• In February 2012, an officer from the Kitchener-Waterloo Police Service stopped a vehicle owned and driven by Andre McGann (Her Majesty the Queen v McGann). The officer detained McGann for questioning, ran a computer check on his driving and criminal record, requested information on known criminals associated with the address McGann indicated as his destination, called for police backup, asked McGann to exit his vehicle and subjected McGann to search. When asked to explain the stop, detention and search of McGann, the officer reported that one of factors that raised his suspicion was that McGann had been stopped and carded by the Toronto Police Service on three occasions in the past year. This case indicates that street check information is sometimes shared between different police services. This case also serves to illustrate how information from previous street check incidents may impact subsequent police suspicions and behaviour.

• As part of his Osgoode Hall criminal law program at York University’s Osgoode Hall, George “Knia” Singh applied to take part in a ride-along with the Toronto Police Service. His application was denied and he could not participate in the ride-alongs with his fellow classmates. Although he does not have a criminal record, Mr. Singh claims that he was informed by police that his ride-along application was denied because his “community engagement” or “street check” record indicated prior association with serious criminals. Singh had long volunteered his time to work with at-risk youth in high-crime, socially disadvantaged areas of the city and believes that this is how his association with “criminals” was established. A police spokesman later confirms that street check records are often reviewed before approving police ride-alongs and that prior association with criminals might have a negative impact on the approval process. This case provides evidence with respect to how street checks – conducted in the name of police intelligence – could be used for security check purposes and ultimately damage civilian opportunities (Rankin 2016).

• Available information also suggests that carding or street check records have, in the past, been routinely released by the police as part of employment and/or vulnerable sector security checks. Information from street checks has also been used internally to assess police recruits (see Crib 2014; Price 2014; PACER 2012). There has thus been great concern about the accuracy of such reports and fears that the release of such information can cause damage to the employment prospects and volunteer opportunities of persons who have never been convicted of a crime. Such information could also damage the reputations of law-abiding civilians. For example, how would an employer or local school respond to street check information suggesting that a job applicant has criminal associates, been observed in a “high-crime” neighbourhood or been disrespectful towards police?

The above examples, although limited, exemplify valid concerns surrounding the retention, use and dissemination of personalized street check data. They demonstrate that the use of street check information often extends beyond the investigation of specific criminal incidents. In fact, street check information can potentially enhance police suspicion towards previously carded individuals and could be used to justify harsher treatment. Street check data might also be used as an alternative, non-conviction criminal record that could negatively impact employment, volunteer and educational prospects.

As Black communities are greatly over-represented in street check datasets, the negative impact of data retention will likely be greater on Black people than people from other racial groups. Fortunately, in 2017, the Ontario government introduced new regulations that have significantly reduced both the number of police street checks and police access to personal street check data. Furthermore, to their credit, over the past five years, both the Toronto Police Service and the Toronto Police Services Board have introduced policies that have further restricted access to historical street check data and information on regulated interactions (see Toronto Police Service 2016; Toronto Police Services Board 2016). These policies, in my opinion, will likely limit future harms caused by the retention

of this type of information. However, these policies do not address the damage to Black communities already caused by previous uses of street check data. Nor do these policies allay community fears that historical street check data – as well as historical information on other TPS non-conviction incidents – could still have negative consequences for members of Black communities.

 

Conclusion

What is perhaps most remarkable about racial profiling research is that, regardless of the research strategy used, the same constellation of results emerges. In general, research from Toronto and other jurisdictions suggests that:

• Racially biased policing is caused by a variety of factors including explicit (conscious) bias, implicit (unconscious) bias, statistical discrimination and systemic or institutional factors
• Regardless of the research methodology used, studies conducted in Toronto consistently find that Black civilians are more likely to stopped, questioned and searched (street checked) by the TPS than White people. The evidence reveals that the TPS engages in racial profiling or biased policing practices
• Racial differences are greater for TPS police searches than for police stops
• Racial differences in TPS stop, question and search activities remain after other legally relevant factors have been taken into statistical account
• Many TPS stops are conducted for purposes of “general investigation” rather than “individualized suspicion.” The fact that Black people are more vulnerable to such “general investigation” stops is consistent with allegations of racial profiling by the TPS
• The “hit rate” or “success rate” for random police stops or checks is uniformly low. The police rarely identify criminal activity during such encounters. The hit rate for Black people is usually the same – or lower – than the hit rate for White people. These findings suggest that race-based criminal profiling is no more successful than randomized police checks
• The fact that Black people are much more likely to be stopped and searched by the police – but Black stops are no more successful than White stops – indicates that innocent Black civilians are much more likely to be subjected to arbitrary police investigations than innocent White people
• Research indicates that racially disproportionate police stop, question and search activities have major social consequences for Black and other racial minority communities. These consequences include: 1) damage to physical and mental health; 2) the gross over-representation of racial minorities in the criminal justice system; 3) a decline in the perceived legitimacy of the police and overall negative attitudes towards the police and broader criminal justice system; 4) reluctance to report criminal activity and a lack of cooperation in police investigations; 5) perceptions of injustice and a lack of faith in social institutions; and 6) higher rates of racial minority offending
• The crime prevention benefits of police stop, question, search and document practices are contested. Best estimates suggest that overall effects on crime reduction are small – much smaller than proponents claim. There is a growing

consensus among academics that the costs associated with the widespread, arbitrary use of aggressive police stop, question and search tactics far outweigh the potential benefits.

A large number of policy initiatives have been identified that might reduce racially biased policing and the negative impact of racially disproportionate stop, question and search practices. Recommended policy options have included: 1) improved screening of police recruits for racial bias and cultural competence (Nicholson-Crotty et al. 2019; Miles-Johnson 2019; Conti and Doreian 2014; Zimny 2015); 2) improved recruitment of racialized officers so that the police reflect the diversity of the communities they serve (Benton 2020; Donahue 2019); 3) improved training in race relations, implicit bias and cultural competency (Miller et al 2020; Davis 2015; Moon et al. 2018); 4) training in less aggressive and more respectful methods for dealing with civilians during police stops (Rosenbaum and Lawrence 2017); 5) improved community policing and focused deterrence strategies (Braga et al. 2020; Thomas and Burns 2019); 6) Regulation and policy that guides officer discretion with respect to stops and searches (Tulloch 2019); and 7) increased civilian oversight and police accountability mechanisms (Kwon and Wortley 2020; Nolan 2019; Walsh and Conway 2011). Many community members and researchers have also called

for more police transparency with respect to the collection and dissemination of data – including race-based data – that will enable better quality research into police activities, improved evaluation of anti-racism efforts and greater police accountability.

 

The arguments for and against police data collection

Over the past two decades, a fierce debate has taken place in Canada over the collection and release of official data on police stop and search activities. On the one hand, many community organizations and civil rights groups have called for the systemic collection

of stop and search data. They have also maintained that this data should be released to

the public on an annual basis. On the other hand, many police organizations and police associations have, in general, fiercely resisted calls for mandatory data collection on police stop, question and search activities. This section of the report briefly reviews the major arguments for and against data collection. It is important to review these historical arguments in order to highlight recent progress with respect to TPS race-based data collection policies.

The argument for data collection

1. Data collection may directly reduce racially profiling and other forms of racially biased policing. Data collection is not only a research exercise. It is a form of police monitoring and accountability. Officers who engage in racial profiling – out of racial animus, racial stereotyping or some other reason – will be less likely to engage in biased stop and search activities if they know that their actions will be directly reviewed by their supervisors. Data collection makes what has been called the “invisible” side of policing more “visible.” Internal benchmarking will also help police managers identify potentially biased officers and target them for re-training or disciplinary action.
   
   
   
   The question is: Without monitoring, how do police supervisors know what their officers are doing when they hit the street? This argument is also consistent with the results of other police monitoring practices. For example, in the United States, it is well known that racial disparities in police use of force declined significantly after officers were mandated to fill out “use-of-force” forms every time they drew their gun or used force against a civilian (see review in Wortley 2006). Although limited, research in both England (Miller 2010) and the United States (Warren et al. 2009) also suggests that data collection may have contributed to a decline in racially biased policing within many jurisdictions. In sum, without proper monitoring, individual police officers will be better able to hide or conceal racial profiling practices.

2. Data collection may improve police relationships with racialized communities. As discussed at length above, Black Canadians and other racial minority groups have significantly less trust and confidence in the police than White people. Data monitoring of police stop and search activities might improve these perceptions in several ways. First of all, monitoring could actually reduce racially biased policing. Secondly, data monitoring provides transparency. It demonstrates that the police have nothing to hide and are willing to share their actions with the public. By contrast, the refusal to collect and release data could be perceived as evidence that the police are “circling the wagons” and trying to prevent the release of information that may not portray them in a positive light. Finally, the willingness to collect and release data on stop and search activities may convince the public that the police are taking the issue of racially biased policing seriously and are trying to reduce the impact of profiling on racialized communities.
   
   
   
   To date, very little research has explored the impact of police data collection on public attitudes. However, British researchers have demonstrated that, since stop and search data collection was mandated in England and Wales, racial minority group confidence in the police has improved significantly (see Bradford 2011; Myhill and Beak 2008).

3. Data collection will assist in the evaluation of anti-racism and anti-racial profiling programs. Over the past two decades, Canadian police services have introduced a wide variety of anti-racism initiatives designed to reduce racially biased policing and improve police relationships with racialized communities. These initiatives include anti-racism/cultural sensitivity training; programs to increase the recruitment of racialized officers and the establishment of police-community consultative committees. Recently, a number of police services, including the Ottawa Police Service, have established explicit anti-racial profiling policies. Unfortunately, as Stenning (2003) notes, none of these anti-racism initiatives have been subject to a high-quality evaluation.^[24] The question is, therefore: without the collection of data on police stop and search activities, how can we tell if anti-profiling policies are effective or not? You simply can’t. Furthermore, without data collection it would also be difficult, if not impossible, to properly evaluate the effectiveness of other anti-racial profiling strategies including anti-profiling training, cameras in police cruisers, etc.

4. The monitoring of police stop and search activities is an important management tool. One of the greatest challenges facing the establishment of data collection or monitoring programs is the perception that the utility of such programs is limited to the investigation of racial bias. Nothing could be further from the truth. Besides race, data collection forms should be designed to collect information on the age, gender and home address of
   
   the civilian, whether the stop was a pedestrian or vehicle stop, the time
   
   and location of the stop, the reason for the stop, whether the civilian was searched or not, and the outcome of the stop (no action, warning, ticket, summons, arrest, etc.).
   
   
   
   Thus, besides racial differences in exposure to the police, these data can be used for a variety of other purposes including: 1) measuring gender and age differences in exposure to the police; 2) police stop and search behaviours within specific neighbourhoods; 3) the reasons officers decide to stop drivers and pedestrians; and 4) the effectiveness of police stops. In other words, an effective data collection system can assist police supervisors with respect to monitoring the activities of their officers in the field and establishing measures of effectiveness and productivity.
   
   
   
   As Tillyer and his colleagues (2010: 87) note, once a data collection system has been established: “Law enforcement agencies can now assess and begin to understand the decision-making process of their officers with the assistance of these data. The trend toward vehicle stop data collection across the nation offers several advantages to police agencies.

In particular, these efforts can assist in informing agencies about patterns and trends in disparities in the stop and search outcomes

for specific racial/ethnic groups. In undertaking this self-evaluation, agencies demonstrate a commitment to unbiased policing, particularly in situations where an agency voluntarily initiates data collection or goes beyond what is legislatively or judicially required of them. Moreover, understanding the patterns of vehicle stops and their outcomes can assist agencies in the effective and efficient allocation of resources which are often prime considerations in the present budget conscious environment.

Cleary the advantages of such a data collection system would extend to pedestrian as well as vehicle stops.

The final argument in favour of data collection is more philosophical than practical. It concerns the ownership of information about the police and police actions. It must be remembered that, since their creation, police services tend to be developed as para-military organizations. As such, they often view information as “intelligence” and try to use this intelligence to their advantage. Indeed, besides data on stop and search activities, it is very difficult to access many types of information on coercive police operations – including information on police use of force, local arrest data, data on police remand decisions, police complaints, etc. Often such information is only made available through freedom of information requests.

It is also important to note that modern police organizations often have public relations departments or public relations personnel. As with other corporations, one might argue that it is the job of police public relations personnel to selectively release information that will establish a positive image of the police service, while preventing the release of information that could “harm” the reputation of the service. Police advocates have argued that such image management is important with respect to maintaining public confidence in the police and ensuring proper police functioning. Others, however, have maintained that, at least in theory, the police work for the public. As such, the police must be transparent and both collect and release all information that the general public – or particular groups within the public sector – demand. As Kane (2007: 778), argues, police departments sometime unwisely operate as if police-generated records are propriety data.

The public funds police departments and all dimensions of their coercive activities. The public owns all information related to police operations and processes. Thus, police departments should be required not only to collect data on coercive outcomes and processes but also to make them generally available to the public (original emphasis).

As we shall see, such views are not often shared by police officers or their supervisors.

The argument against data collection

It is also important to note that the advantages of police data collection need to be weighed against the potential challenges or consequences of such endeavours. Below we outline a few of the major arguments against data collection that have been provided by police organizations and their advocates.

1. Data collection will damage police officer morale. A number of critics have argued that police officers are not supportive of efforts to monitor their activities, and that forcing police services to collect data on police stop and search activities will damage police morale. Damage to police morale, in turn, could lead to a drop in job satisfaction and productivity.
   
   
   
   Unfortunately, we could not locate any research that addresses this claim. For example, we could not locate information to suggest that the police services in Britain or the United States – where data collection is mandated – have lower morale than the police services where data collection has not yet been instituted. However, there is evidence to suggest that the “poor morale” argument has been repeatedly used by police organizations and police unions to resist other public accountability measures, including police use-of-force regulations, public complaints commissions, civilian oversight agencies, officer name tags and the establishment of Ontario’s Special Investigations Unit (see Sewell 2010; Morin 2008; Wortley 2006).
   
   
   
   In sum, the potential impact of data collection on officer morale and job satisfaction is an important research question that deserves to be investigated. However, we must also consider the possibility that, despite initial resistance, police officers will eventually accept data collection responsibilities as part of their job description and conduct themselves in a professional manner. Finally, it is possible that the impact of data collection on officer morale could be minimalized if data collection can be sold as part of a wider intelligence gathering/performance monitoring system rather than a tool for identifying racial profiling.
   
    
2. Data collection will compromise public safety. It has also been argued that forcing the police to collect data on the people they stop and search will lead to “de-policing.” In other words, police officers will deliberately reduce the stops and searches they conduct on racial minority civilians in order to avoid allegations of racial bias. Such de-policing behaviours, it is argued, will have
   
   a detrimental impact on the crime rate. This argument was made by Craig Bromell, then-President of the Toronto Police Association, in the aftermath
   
   of the 2003 Toronto Star series on racial profiling. Brommel maintained that
   
   if data collection was imposed on the Toronto Police Service, police officers would simply stop engaging in proactive policing within racial minority communities and that this would give racial minority criminals a free reign.
   
   
   
   Others have argued that data collection will take valuable time and resources away from police crime-fighting and prevention activities, and that this will,
   
   in turn, lead to more crime. However, we could find no empirical evidence to support this claim. Indeed, since data collection was mandated, crime rates – including violent crime rates – have declined significantly in both Great Britain and the United States (Siegel et al. 2010). Interestingly, crime rates have also declined in regions without data collection – perhaps indicating that data collection procedures have little to do with the causes of crime. Finally, there is little evidence to suggest that data collection has actually reduced police stop and search activities. Indeed, the number of stops and searches recorded by the police in both England and New York City has increased significantly since data collection began (see Jones-Brown et al. 2010; Miller 2010).

3. Data collection is too expensive. A number of critics have argued that police data collection is too expensive and would take valuable resources away from other important policing functions. By contrast, others have argued that, after initial start-up costs, police data collection is relatively efficient and inexpensive. Indeed, many police services already have data collection processes in place that document police-civilian encounters (i.e., contact cards or electronic reports) and only minor adjustments are required to move to the full collection of stops data.^[25]
   
   It is true, however, that some of the more advanced benchmarking techniques, discussed above, can be quite expensive. Nonetheless, the costs of using these approaches can be offset when the police enter into partnerships with university researchers. Such partnerships are often successful at securing external funding and can thus minimize the impact on police budgets. Furthermore, there are many university researchers who would be willing to provide their methodological expertise and analytical skills for free – as long as they and their graduate students can have access to police data for publication or dissertation purposes. In other words, working with university researchers is much cheaper than dealing with private consultants. Finally, police services in both England and the United States have been able to deal with the financial burden of data collection without sacrificing service. There is no reason to believe that Canadian police services can’t do the same.^[26]

4. Data collection will compromise officer safety: Some have argued that data collection will put police officers at higher risk of serious injury or death. This is a somewhat difficult argument to understand – especially since the same critics often argue that data collection will also reduce the overall number of police-civilian encounters (a fact that would reduce the overall risk of a violent confrontation). Perhaps they are arguing that data collection will change the nature of how the police deal with civilians once a stop is initiated. For example, because they fear allegations of racism, police may be more reluctant to search or use force against racial minority suspects who may be carrying weapons. Nonetheless, we could find absolutely no evidence to suggest the number of police officers injured or killed on the job has increased within jurisdictions that have mandated data collection.
   
   
   
   It is also important to note that similar concerns about officer safety were voiced when new use-of-force regulations mandated the completion of use-of-force forms every time the police pulled their guns or used physical force against a civilian. The argument then was that officers may hesitate to use force in dangerous situations because they do not want to perform extra paperwork. Now, decades later, we know that such concerns were unfounded. Indeed, American research suggests that since the implementation of use-of-force regulations, the number of officers seriously injured in the line of duty has significantly declined – as have the number of civilians killed or injured by the police (see Wortley 2006).

5. The data could be used in court. Some critics fear that, if available, aggregate statistics on police stop and search activities will be increasingly used by lawyers in both the criminal and civil courts. Such data, they worry, could clog the criminal courts with cases that allege “racial profiling” and thus slow down the court process and ultimately damage conviction rates. Others worry that police data could increase civil claims alleging police racism, and that such allegations will increase legal costs and claims payments. We cannot discount this possibility. However, it is important to note that such cases have existed before data collection and will likely exist after data collection has begun. Furthermore, all cases must be judged on their own merit, and it is unlikely that data alone will prove racial bias in any particular case. Furthermore, if data collection helps to reduce racial profiling, as suggested above, fewer racial profiling cases could emerge. Finally, it is possible that high-quality research on police stop and search may help the courts perform their function and make wise decisions that are consistent with the principles of justice. Fear of data – and its possible use in court – is not a valid reason to ban data collection.

6. The data could damage racial minorities: In an interesting twist, some have argued that data on police stop and search activities could actually damage racial minority communities. They maintain that, while some may interpret the over-representation of racial minorities in official stop and search statistics as evidence of bias, others might assume that this data “proves” that certain racial groups are more crime-prone than others. Stop and search data, in other words, might increase racial stereotyping within Canadian society. This logic is similar to the justification for banning all “race-crime” statistics in Canada (see Wortley 1996).
   
   
   
   It is interesting that this paternalistic justification for banning race-based data collection also serves to prevent the effective identification of racial bias in the justice system. Furthermore, the current ban on race-crime statistics has in no way prevented crime-related racial stereotypes from emerging in Canada. Indeed, racialized images of crime dominate the news media – where the vast majority of citizens get their information on crime-related issues. It fact, even with the current ban on race-crime statistics, Canadians actually tend to greatly over-estimate the involvement of racial minorities in criminal activity (see Wortley and Owusu-Bempah 2011).

These are but a few of the arguments that have been put forward by people who reject or resist calls for police data collection on stop and search activities. Finding a consensus on this issue is only a distant hope. In many ways, the debate is split between people who prioritize the interests of the racial minority community members and researchers who want data collection, and people who are more sympathetic to the interests of the police and police organizations.

One might argue that many – if not all – of the arguments against race-based data collection within policing have been overcome and are thus not worthy of further discussion. Indeed, over the past two years, the TPS and several other Ontario police services appear to have recognized the need for race-based data and have subsequently developed policies promoting the collection and analysis of this type of information. Finally, a quarter-century after race-based data collection was recommended by the Commission on Systemic Racism in the Ontario Criminal Justice System (1994), it appears that police services in Ontario are recognizing that data collection may help reduce racial bias, improve public perceptions of the police, and promote racial equity within law enforcement – I am cautiously optimistic. In the past two years, I have witnessed more positive change on the race-based data collection front than during the previous 25 years. However, there is also cause for cynicism. In my opinion, arguments against data collection may still exist, especially among front-line officers. Furthermore, resistance to data collection may still cause serious delays with respect to the collection and release of race-based data and the quality of the race-based data that is ultimately compiled. 

How do front-line officers view the issue of race-based data collection? Do they feel that such data collection is necessary? Do they feel that such data collection might have a negative impact on their careers? Will the race-based data that is produced by the police be of high or low quality? Will the type of data collected enable or impede advanced analysis of the racial profiling issue? Unfortunately, at the time of finalizing this report (September 2021), the TPS has not yet released any of the race-based data mandated by the TPSB’s

Policy on race-based data collection, analysis and public reporting (Toronto Police Services Board 2019). Furthermore, as discussed below, plans to collect data on police stop, question and search tactics have yet to be finalized. Thus, in the last section of this report, we highlight a possible multi-method strategy for collecting high-quality data dealing with the issue of racially biased policing in Toronto.

 

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Recommendations for data collection on police stop, question and search activities

As the above review suggests, no study is perfect. Different types of methodologies have different types of strengths and weaknesses. The strengths of qualitative studies (contextual detail, information on emotional impact, etc.) are different than the strengths of quantitative studies (large sample size, replicability, etc.). As a result, researchers often recommend a multi-method approach when addressing complex issues such as police stop and search practices. This strategy is sometimes referred to as triangulation (see Hammersley 2008; Denzin et al. 2006; Bryman 2007). The argument is that by using multiple research methods to address the same topic, we are better able to understand social realities.

Furthermore, if different research methods tend to yield the same types of results, we can have more confidence in their accuracy. For example, both survey data and official police statistics, including data from several Toronto studies, suggest that Black people are more likely to be stopped, questioned and searched by the police than White people, even after other relevant factors have been taken into account. The fact that such findings were produced by two very different research methodologies should strengthen our confidence that these findings reflect reality. Furthermore, findings using one type of method may help us understand the results of a study that used an entirely different research strategy. For example, qualitative interviews will help us understand the emotional impact of racial profiling and help explain survey research findings which suggest that racial minorities have a lower opinion of the police than White people.

Also, while official data collection may help us measure the extent of racial disproportionality in police stop and search activities, qualitative methods may help us better understand police decision-making processes. As Tillyer et al. (2010: 87) note:

Future research may have to advance beyond quantitative analysis and explore qualitative studies to address the underlying motivations for officer decision-making. This alternative approach to studying the existence and extent of bias-based policing likely will require asking officers to describe their decision-making process through the use of interviews or focus groups.

In light of these findings, we recommend that all Canadian police services adopt a multi-method approach to race-based data collection and research into diversity issues and

anti-racism initiatives. It should be noted that, in spirit, the TPSB’s Policy on Race-based

Data Collection, Analysis and Public Reporting (www.tpsb.ca/policies-by-laws/board-policies/177-race-based-data-collection-analysis-and-public-reporting) is largely consistent with many of the following recommendations:

1. The first step in the research process should involve the formation of a research or evaluation committee. This committee would be responsible for
   
   the development and implementation of the research and evaluation plan. This committee should consist of police personnel, community representatives and academic researchers. It is important that researchers be involved from the beginning of the research process, as they should have the methodological training to ensure the development of a sound methodological strategy.
   
   As discussed above, the use of university-based academics, trained in social science methodology, will likely be much less expensive than the use of private consultants. Furthermore, the use of university researchers might contribute to the perceived objectivity of the project.^[27]
   
   
   
   The selection of the researchers is an important step. Ideally, researchers should be approved or accepted by both the police and community representatives of the research committee. If a consensus on a single researcher or research team cannot be found, the committee should ultimately form a research team that consists of both researchers that are acceptable to the police, and researchers that are acceptable to community members. Priority should be given to Black, Indigenous and other researchers of colour who have lived experiences with the issues. Caution should be directed at researchers who have long established relationships with policing organizations. Indeed, critics have noted that some “evidence-based” researchers, popular with government and police officials, have a pro-police bias that ensures access to data and lucrative research contracts.

2. We recommend that police services establish a permanent data collection system to record information on all stops of civilians. This data system should record information on both traffic stops and stops involving pedestrians. The information to be collected on each stop should include: the date of the stop,
   
   the time of the stop, the location of the stop (x-y coordinates), the reason for the stop and the outcome of the stop (no action, warning, ticket, summons, charges, arrest, etc.). The documentation of stop outcomes is particularly important
   
   as it can be used to calculate race-based “hit rates” (the proportion of stops that result in the discovery of illegal activity). Such rates are an important measure of racial profiling and can be used to highlight the proportion of each racial group who are subject to unnecessary police attention. Data collection strategies should also document whether the person or vehicle involved in the stop was subject to a pre-arrest or post-arrest search. The age, gender and racial background of the person stopped should also be recorded. Ideally, the data collection procedure would also record the full name and home address of the individuals stopped. This would help the researchers identify individuals who are stopped multiple times, in a given time period,
   
   as well as individuals who reside outside of the study jurisdiction.
   
   
   
   Such information would help researchers determine if people are more likely to be stopped in their own neighbourhoods or when they travel to other areas of the city. For example, previous information suggests that Black people in the United States are most likely to be stopped when they travel into predominately White neighbourhoods – a finding that is consistent with
   
   the “out-of-place” hypothesis (see Meehan and Ponder 2002). Of course, the research committee might identify other information that should be recorded.^[28]

3. We recommend the development of a permanent data collection system for the following reasons:
   
   1. A permanent system will allow for comparisons over time. Trend data could be used to identify emerging patterns related to police stop and search activities and evaluate the effectiveness of anti-racism policies
   2. Data monitoring of stop and search activities may reduce racial profiling (as discussed above). Thus, the benefits of data monitoring would be severely limited if police services only engage in a time-limited pilot project
   3. During a time-limited pilot project, the police may change their normal activities to avoid allegations of racial bias. However, they may return to normal activities after the study is complete.

4. We recommend that the performance of front-line officers be based on the quality and reliability of the race-based data that they collect. Unfortunately, some officers may have a negative attitude towards race-based data collection and research. Others may be reluctant to record the racial background of the people they interact with because they want to avoid allegations of racial bias. Thus, without making data quality part of officer performance evaluation, the likelihood of missing or low-quality racial data increases.

5. We recommend that police services perform periodic reliability checks to determine the quality of race-based data and identify officers who are non-compliant with race-based data collection policies. Officer reports of civilian race, for example, could be compared with licence photos, dashboard camera footage, body-camera footage or civilian self-reports. Data reliability could be determined through a correspondence analysis that compares officer racial classifications with classifications made by an independent third party or by the civilian self-reports of racial identity.

6. In addition to census and adjusted census benchmarking (which will capture per capita stop rates), we also recommend the use of one or more advanced benchmarking techniques (see Wortley 2019)). The exact benchmarking techniques to be employed should be decided by the research committee. However, we recommend the use of observational benchmarking, because it has the best chance of capturing other factors that may be related to police decisions to stop and search civilians (including street availability).
   
   
   
   Due to the high cost, it would be impossible to conduct observational benchmarking on a continual basis. Thus, we recommend that observational benchmarking sub-studies be conducted periodically (perhaps every two to five years) to supplement the regular collection of stop and search data.
   
   
   
   It would also be impossible to conduct benchmarking in all neighbourhoods. Thus, we suggest that observational benchmarking should be conducted on a random sample of both high- and low-stop areas within the study jurisdiction.
   
   
   
   Finally, if possible, we recommend that the research committee work with academic researchers to secure external funding for these benchmarking sub-studies.

7.  We recommend that police managers use internal benchmarking techniques
   
   to identify individual officers who are possibility engaging in racially biased stop and search practices. Once identified, these officers can be brought in for discussion, re-training, discipline, or termination. Although the research committee may assist police supervisors in the development of internal benchmarking techniques, the names of individual officers do not have to be released to the research committee or the general public. The use of internal benchmarking could remain an internal strategy for identifying problematic officers. However, the research committee may want to know how many officers have been identified as potentially biased through internal benchmarking techniques and how these officers were dealt with. The release of such raw numbers would not reveal the identity of individual officers.

8. The collection of official police data should be supplemented with periodic surveys of the general public. General population surveys should collect information on self-reported contacts with the police, as well as respondent attitudes and perceptions of the police and wider criminal justice system. Survey data on self-reported stops could be compared with official stop data in order to identify significant commonalities or differences. Surveys could also be used to conduct multivariate analyses and determine whether racial differences in stop and search activities can be explained by other factors including age, area of residence, local crime rates, driving habits, use of public spaces, self-reported drug and alcohol use and self-reported involvement in criminal activity. Importantly, if such surveys are conducted on a periodic basis (every two to five years), the data could be used to determine if racial differences in stop and search activities are declining or increasing and if attitudes towards the police are improving or getting worse. In other words, survey research data over time could be used to evaluate the effectiveness of anti-racism and anti-profiling policies.

9. Periodic surveys should also be conducted on the police themselves. Such surveys could be used to measure the impact of data collection on officer morale and job satisfaction, officer attitudes towards anti-racism programs or policies, and officer decision-making with respect to stop and search tactics. Such surveys could be expanded to measure prejudice and stereotyping, attitudes towards specific racial minority groups and racial minority crime and opinions about the effectiveness of various anti-racism policies. Of course, these surveys could address any other topics of interest to the research team or police managers. We recommend that such officer surveys be conducted every two to five years to better facilitate the evaluation of anti-racism initiatives.
10. We recommend the periodic implementation of qualitative research methods. These methods should include interviews and focus groups with both community members and police officers. Such strategies could collect more detailed information about public perceptions of police stop and search tactics; the impact of police stops on individuals and communities; opinions about whether police anti-profiling and anti-racism strategies are working; and how anti-racism strategies might be improved.
    
    
    
    Such qualitative strategies could also measure public awareness of data collection efforts and research results, and gauge the impact that research is having on public opinion. As discussed above, qualitative methods could also be used to examine the impact of anti-profiling policies and data collection on officer morale and how such policies have impacted police behaviour on the street. Furthermore, interviews and focus groups could be used to investigate police decision-making and how race and other factors influence –
    
    or do not influence – the actions police take as they perform their patrol duties.

11.  Finally, we propose that reports documenting the results of all data collection and research activities be released to the public on an annual or biannual basis. This is the only way to guarantee transparency. However, we also feel that reports should not be released until the research team has conducted a full analysis of the data. Furthermore, reports should not be released until police officials have been fully briefed. Reports should be released during a coordinated press conference in which the data can be fully explained. This will reduce the chance that the data will be used inappropriately (although that possibility can never be totally eliminated).

12. De-identified police datasets, documenting all police stop and search activities, should be released to the general public on an annual or biannual basis. This process will increase transparency and permit data analysis and interpretation by researchers and community members not involved in the formal, police-led research process.

In conclusion, it is quite apparent that high-quality, race-based data collection by the TPS

is needed to fully examine police stop, question and search activities and evaluate the effectiveness of TPS anti-racism policies. In recent years, police services have sometimes modelled themselves after major corporations. They have started to develop “mission statements” and “business plans,” and have started to refer to the public as clients or customers. It is hard to imagine a major corporation developing a major policy without also developing a strategy for evaluating the effectiveness of that policy. Police services need to follow the same path. Anti-racism policy without proper monitoring and evaluation can be dismissed as nothing but symbolic window-dressing. Without proper monitoring, little will change with respect to police-race relations over the next decade.

A note regarding TPS plans to collect stop data

According to information provided by the OHRC, the Toronto Police Service was slated

to begin collecting race-based data on traffic and pedestrian stops on January 1, 2021. However, at this stage, the TPS only plans to collect data on stops that actually result in written warnings, tickets, charges or arrests. In other words, it only plans to collect data

on “successful” stops that clearly uncover evidence of illegal activity. If true, this plan is highly deficient and highly inconsistent with best practices in racial profiling research. This strategy is also inconsistent with Justice Tulloch’s focus on the elimination of “carding.” If you recall, Justice Tulloch defines carding as random or arbitrary police stops or interactions that result in the documentation of civilian personal information for police intelligence purposes. Clearly, police stops that result in formal warnings, tickets, charges or arrests can never be considered “carding” incidents because the legal justification for

the encounter is transparent. In other words, although the TPS may want to eliminate “carding,” they appear to be designing a data collection strategy that will not in any way document “carding” incidents.

As discussed above, an important element of racial profiling research is the documentation of all police stops and post-stop activities (e.g., vehicle searches, pat down searches, case outcomes, etc.). At the heart of racial profiling debate are claims that Black and other racialized people are more likely to be subject to unnecessary or unwarranted police stops and searches: race-based “fishing expeditions” that rarely uncover illegal activity. Researchers have recently argued that one strategy for uncovering racial bias is the analysis of race-based hit rates: the proportion of all stops that result in the discovery of illegal activity.

While Canadian data is not available, we know from American and British research (discussed above) that police stop, question and search activities rarely uncover direct evidence of criminal activity. The research record is worth repeating. Between 2004 and 2012, the NYPD conducted approximately 4,135,000 stop, question and frisk investigations.^[29] Only 46,000 of these stops – a mere 1.1% – resulted in the seizure of illegal contraband and only one out of every thousand stops (0.01%) resulted in the seizure of an illegal firearm (see Torres 2015). A similar picture emerges in England. As documented by Bowling and Phillips (2007), the per capita police stop rate in England and Wales is approximately 6.5 times greater for Black people than for White people. However, the hit rate for both Black and White people is almost identical – about one percent of stops for both groups result in the discovery of illegal activity. The fact that these hit rates do not vary by race might be interpreted as an absence of racial bias. However, the hit rate figures, combined with the per capita stop and search rate, shed light on another reality: every year – innocent Black people in England and Wales are 6.5 times more likely than innocent White people to endure an unnecessary stop and search encounter with the police.

At this stage, the TPS is not collecting race-based data on police stops – arguably the majority of police stops – that do not result in legal action. Such an approach would prevent the collection of data on “carding” incidents and also prevent an analysis of race-based hit rates. In other words, the TPS plans would prevent an adequate examination of the racial profiling issue and ultimately contribute to more confusion, denials and delay.

As discussed above, the TPS originally stated that they would begin data collection on police stops in January 2021. However, in correspondence dated September 8, 2021, the TPS clearly indicates that data collection on police stops still has not commenced. The correspondence notes: “The TPS is currently working on updating its systems capacity and resource workflow to collect stop data, including both traffic and pedestrian, and lower uses

of force. These areas are important to get right for sustainable collection that supports robust and actionable insights.” In order to truly address racial profiling, the TPS must collect information on all stops and searches – especially stops and searches that do not result in the identification of illegal activity.

 

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Samuels-Wortley, K.  2021. The weight of fitting the description. Using Critical Race Theory to explore Black and Indigenous youth perceptions of the police. Doctoral Dissertation, Department of Sociology, University of Waterloo.

Wortley, S. 2019a. Halifax, Nova Scotia: Street Check Report. Halifax, Nova Scotia Human Rights Commission. https://humanrights.novascotia.ca/sites/default/files/editor-uploads/halifax_street_checks_report_march_2019_0.pdf.

Wortley, S. 2019b. Appendix A: Street Checks, Racial Profiling and Police Community Relations:

A Review of the International and Canadian Literature. Halifax, Nova Scotia Human Rights Commission. https://humanrights.novascotia.ca/streetchecks.

Wortley, S. 2006. Police Use of Force in Ontario: An Examination of Data from the Special Investigations Unit – Final Report. Toronto: Attorney General of Ontario (Ipperwash Inquiry), Governmnent of Ontario.

Wortley, S. 1996. "Justice for All? Race and Perceptions of Bias in the Ontario Criminal Justice System – A Toronto Survey." Canadian Journal of Criminology and Criminal Justice 38 (4): 439-467.

Wortley, S., Laniyonu, A., and Laming, E. 2020. Race and the Use of Lethal and Non-Lethal Force by the Toronto Police Service: Final Report. Toronto: Ontario Human Rights Commission (187 pages; Not listed in previous activity reports).

Wortley, S., and Jung, M. 2020. Documenting Racial Disparity: An Analysis of Arrest and Charge Data from the Toronto Police Service. Toronto: Ontario Human Rights Commission (148 pages; Not listed in previous activity reports).

Wortley, S., and Owusu-Bempah, A. 2020. Race and Criminal Injustice: An Examination of Public Perceptions of and Experiences with the Criminal Justice System Among Residents of the Greater Toronto Area. Toronto: Canadian Association of Black Lawyers.

Wortley, S., Bundy, J., Tanner, J., and Lodge-Tulloch, K. 2019. “Race, Street Checks and Perceptions of Police Among Disadvantaged Toronto Youth.” Paper presented at the Western Criminology Association Annual Meeting, Honolulu.

Wortley, S., Macmillan, R., and Hagan, J. 1997. “Just Des(s)erts? The Racial

Polarization of Perceptions of Criminal Injustice.” Law and Society Review 31: 637-676.

Wortley, S., and Owusu-Bempah, A. 2011a. “Crime and Justice: The Experiences of Black Canadians.” In Barbara Perry (Ed.) Diversity, Crime and Justice in Canada. New York: Oxford University Press: 127-150.

Wortley, S., and Owusu-Bempah, A. 2011b. “The Usual Suspects: Police Stop and Search Practices in Canada.” Policing and Society 21 (4):395-407.

Wortley, S., and Owusu-Bempah, A. 2009. “Unequal Before the Law: Immigrant and Racial Minority Perceptions of the Canadian Criminal Justice System. “Journal of International Migration and Integration 10: 447-473.

Wortley, S., and Tanner, J. 2008. “Money, Respect and Defiance: Justifying Gang Membership in a Canadian City.” Pp. 192-210 in Frank van Gemert, Dana Peterson and Inger-Lise Lien (Eds) Youth Gangs, Migration and Ethnicity. London: Willan Publishing.

Wortley, S., and McCalla, A. 2008. “Racial Discrimination in the Ontario Criminal Justice System: 1994-2007.” Pp. 187-207 in Julian Roberts and Michelle Grossman (Eds.) Criminal Justice in Canada: A Reader – 3^rd Edition. Toronto: Thomson-Nelson.

Wortley, S., and Tanner, J. 2005. “Inflammatory Rhetoric? Baseless Accusations? Responding to Gabor’s Critique of Racial Profiling Research in Canada.” Canadian Journal of Criminology and Criminal Justice 47 (3): 581-609.

Wortley, S., and Tanner, J. 2003. “Data, Denials and Confusion: The Racial Profiling Debate in Toronto.” Canadian Journal of Criminology and Criminal Justice 45 (3): 367-389.

Wortley, S., and Kellough, G. 2004. “Racializing Risk: Police and Crown Discretion and the Over-representation of Black People in the Ontario Criminal Justice System.” Pp. 173-205 in Harriott, A., Brathwaite, F., and Wortley, S. (Eds.), Crime and Criminal Justice in the Caribbean and Among Caribbean Peoples. Kingston, Jamaica: Arawak Publications.

Wortley, S., and Marshall, L. 2005. The Kingston Police Stop Pilot Project: Final Results. Kingston: Kingston Police Services Board.

Yogaretnam, S. 2015. “Street Check Data About Racialized Men Concerning to Civil Liberties Advocates.” Ottawa Citizen (July 26).

Zimring, F. 2012. The City that Became Safe: New York’s Lessons for Urban Crime and Its Control. New York, NY: Oxford University Press.

Zhao, J., Lai, Y., Ren, L., and Lawton, B. 2011. “The Impact of Race/Ethnicity and Quality of Life Policing on Attitudes Towards Racially Biased Policing and Traffic Stops.” Crime and Delinquency 6 (3): 350-374.

Zatz, M., and Krecker, R. 2003. “Anti-gang Initiatives as Racialized Policy.” In Hawkins, D., Myers, S., and Stone, R. (Eds.), Crime Control and Social Justice: The Delicate Balance. Westport, CN: Greenwood Press.

Zimny, K. 2015. “Racial attitudes of police recruits at the United States Midwest Police Academy: A second examination.” International Journal of Criminal Justice Sciences 10 (1): 91-101.

 

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