Introduction

On January 29, 2017, a lone gunman entered the Islamic Cultural Centre, a mosque in the Sainte-Foy neighborhood of Quebec City, Canada and opened fire on numerous unsuspecting worshippers. The callous attack resulted in the deaths of six Muslim men and left nineteen other worshippers injured. All the victims had just finished the evening congregational prayer. A lone suspect was arrested shortly after the crime and was subsequently charged with six counts of first-degree murder. While a motive from the gunman has not been clearly identified, friends and former classmates of this man suggest that he held xenophobic, anti-Muslim, and anti-immigration sentiment. As one of the gunman’s friends explains of a recent interaction with him on Facebook, “[the gunman] told me that in the long run, this non-white, non-European immigration may perhaps lead to the marginalization of whites” (Montpetit, 2017). These hateful perceptions of non-white groups were the fuel that led to Canada’s most recent act of mass gun violence. As Brax (2017) explains, crimes which are motivated by a form of hate and bias towards an identifiable group is an example of a “bad motive – attacking a person because of his/her connections to a certain racial, ethnic, religious, etc. group” (Brax, 2017, p. 60).

Although this crime was not labelled as a hate crime (or an act of terror) due to the evidence available for assessment by the crown prosecution in the case (see Chin, 2017), the communities and victims impacted by the act cannot help but feel this was an act motivated by hate. Shortly after this attack, Muslims in Quebec mentioned feeling afraid, scared and intimidated (CBC, 2017). This hesitation the justice system has towards labelling an act as a hate crime does not come unwarranted. Police and other justice serving agencies must be certain that a crime was motivated by an act of hatred. The reason for this is often due to successful prosecution of the charge. As a result, real and perceived victims of hate start to lose trust in the justice system, creating the potential for victims of hate to not report these incidents to the police or other governing bodies. In a society that claims to be as multicultural and inclusive as Canada does, there are great ramifications to the social fabric of a nation when a crime is labelled as motivated by hate. Hate crimes are socially disruptive because they showcase an ugly part of society many do not wish to acknowledge. The hate crime label can create division between groups through a process of identity formation. In doing so – to the extent that we conform to normative conceptions of identity – we reinforce the structural order (Perry, 2009). In this context lies the challenge around naming and labelling hate as crimes. As a result, recording, documenting, and creating visibility on the extent of hate crimes become challenging, as current reporting mechanisms might not highlight the real extent on the prevalence of hate crimes or other incidents motivated by hate.

Another related challenge of current reporting mechanisms is the delayed time between asking questions regarding the experiences of victims of hate crimes. In Canada, the General Social Survey on Victimization includes a question on hate crime victimization every five years. According to the last time this question was asked (2014), Canadians self-reported having been the victim of over 330,000 criminal incidents that they perceived as being motivated by hate. Two-thirds of these incidents were not reported to police” (Police-Reported Hate Crime 2016, p, 1). In addition to not having trust in the justice system, victims of hate crimes also do not report the crimes to the police due to “potential cultural and language barriers or a fear of additional victimization by both the police or the community at large” (Woods, 2013, p. 87). This issue is not only unique to Canada. A recent US Department of Justice study found that nearly two in three hate crimes in the US are not reported to the police as victims doubt police can or will help (Sandholtz, Langton, and Planty, 2013). A 2013 survey of 2,500 lesbian, gay, and bisexual people across Britain found that more than three-quarters of gay, lesbian, and bisexual victims of hate crimes did not go to the police for fear they would not be taken seriously (Davies, 2013).

To try to counter the under-reporting of hate crimes, a growing number of non-governmental organizations are developing innovative methods to encourage the reporting of hate and help fill the gap of documenting a set of ambiguously defined behaviors. Examples include TellMamaUK,1 the Southern Poverty Law Centre,2 and the StopHateAB.ca website – an initiative by the Alberta Hate Crimes Committee (AHCC)3 in Canada. The purpose of the StopHateAB.ca website is to fill a gap for reporting hate incidents by creating a central space to document and highlight hate incidents in Alberta. This paper critiques the online hate incident reporting tool StopHateAB, discussing the strengths and challenges of creating an online hate incident reporting platform, as well as highlighting the importance of third-party hate reporting tools to counter hate and bias by making hate visible in order to support strategies that foster a public social environment of justice, equity, and human rights.

Understanding hate: crimes vs. incidents

As Perry (2015) reminds us, “hate crimes are a direct threat to the principles of Canadian multiculturalism” (Perry, 2015, p. 1637). When a criminal act in Canada is motivated by hate, it is considered a hate crime. Hate crimes can be either violent or non-violent in nature and affect not only the individual victims of the crime but also the communities targeted. In Canada, three specific offences are listed as hate propaganda offences or hate crimes in the Criminal Code of Canada: advocating genocide (section 318), public incitement or the willful promotion of hatred (sections 319(1)(2)), and mischief motivated by hate in relation to religious property (section 420 (4.1). In addition, subparagraph 718.2(a)(i) of the Criminal Code allows for increased penalties when sentencing any criminal offence (such as assault or mischief) where there is evidence that the offence was motivated by bias, prejudice or hatred toward a particular group as listed in the Criminal Code. It is important to point out, however, that while the term hate crime is commonly used, little consensus exists as to its exact meaning. The failure of academics, legislatures, and state agencies to find a common definition of hate crime means that the community at large continues to struggle with what exactly a hate crime is (Perry, 2009). As Janhevich highlights, if one examines hate, the original issue was prejudice of some sort which then took on a more dramatic meaning in the form of hate literature and hate propaganda, followed by hate-motivated violence (Janhevich, 1997). As Perry explains, a hate crime is behavior that,

“involves acts of violence and intimidation, usually directed toward already stigmatized and marginalized groups. As such, [hate crimes are] a mechanism of power, intended to reaffirm the precarious hierarchies that characterize a given social order. It attempts to recreate simultaneously the threatened (real or imagined) hegemony of the perpetrator’s group and the appropriate subordinate identity of the victim’s group” (Perry, 2001, p. 10).

As the above quote highlights, a key component of the “hate” definition relates to the power structures involved, where certain groups or individuals reaffirm their dominance through the hateful act. The Quebec mosque shooting example referenced earlier was clearly an expression of hate, where a frustrated young white man who was concerned about immigration and the perception of “being taken over”, took his aggression out on the community he perceived to blame in an effort to ‘even out” the power imbalance. Other less fatal examples where this balancing act occurs include people being physically abused due to skin color, or religious institutions being defaced with graffiti.

Where things begin to get a little murky, however, is when a hateful act targeting marginalized communities does not meet the threshold of a criminal act. A racial or other derogatory slur being hurled at someone, for example, does not meet the threshold of a criminal act, even though it may be motivated by the same hate and bias as a crime. Consequently, these behaviors are more appropriately labelled as hate “incidents” due to the lack of a criminal element. The Facing Facts Guidelines for Monitoring of Hate Crimes and Hate Motivated Incidents (2012) defines a “hate motivated incident as an act that involves prejudice and bias motivated by hate, based on race, national or ethnic origin, language, colour, religion, sex, age, mental or physical disability, sexual orientation, or any other similar factor but which does not amount to a crime” (p. 9). The difference between crime and incident is a crucial one which requires further attention. The heart of this distinction speaks to the elementary nature of how we define crime: mens rea and actus reus (the guilty mind and the guilty act). Criminal law has long struggled to define the criminal intent that transforms a harm into a crime (Jacobs, 1993). Defining criminal motivation is even trickier as it requires getting to the source of an offender’s intent. In the case of hate crime, prosecutors of hate crime cases must not only prove that the defendant was prejudiced, but that the prejudice motivated the crime. It is perhaps this difficulty that minimizes the use of hate crime law in Canada (see: Ross, 1994; Janhevich, 2001).

An added difficulty to understanding the definitional issues surrounding hate crime deals with the way the law (attempts) to police prejudice and bias, while at the same time trying to protect citizens’ rights to freedom of expression. For example, in interracial cases, should the police routinely investigate the offender’s prejudices – what publications he subscribes to, what organizations he’s a member of, what jokes he tells, what stereotypes he holds? (Jacobs, 1993). While defenders of civil rights might suggest that the police should do this, the fact of the matter is this form of “policing prejudice” goes beyond the scope of most police officers’ duties.

Because of the challenges in defining hate, some might argue what merit capturing and documenting this information has. The ambiguity of hate, for example, is just one of the many causes of confusion about its meaning (Brudholm, 2017). Berk, Boyd, and Hammer, for example, have defined it as entering a “conceptual swamp” (Berk, Boyd, and Hammer, 2003, p. 51). Therefore, some might doubt the validity of any information related to hate being captured, as its definition is not clear. Much of the available data on hate-motivated crime, however, rests on unclear definitions. While most police services in Canada document and report on hate crimes, very few, if any, record and publicly release data related to hate incidents. Part of the reason for this is due to the ambiguity of the definition, and another part of it is due to law enforcement’s focus on criminal activity. If no crime has occurred, police are very limited in their ability to be involved. Another reason for not publicly disclosing information related to hate incidents relates to these statistics being potentially socially disruptive, especially if the information has not been validated. Those opposed to their collection and dissemination may feel that the issue of hate is “not real” (due to their social construction) and is difficult to adequately measure, since definitions of hate crime are also socially constructed, and perhaps too vague to have any tangible value (see Jacobs and Henry, 1996). Nonetheless, the importance of capturing information related to hate incidents cannot be overstated. B’nai Brith Canada and the League for Human Rights, for example, have been tracking and examining antisemitic incidents (and crimes) in Canada since 1982 via The Annual Audit of Antisemitic Incidents report. The (2016) annual audit report explores “a wide variety of types pertaining to anti-semitic incidents and includes incidents reported directly to B’nai Brith’s 24/7 anti-hate hotline” (B’nai Brith Canada, 2016, p. 9). As the report highlights, capturing hate incidents (in addition to crimes) is “significant because the vast majority of incidents of anti-semitism fall below the threshold of being considered criminal hate, but are still clear examples of hate-motivated behavior” (B’nai Brith Canada, 2016, p. 9).

Capturing hate incidents ensures that hate motivated acts that do not meet a criminal threshold are still reflected in data capturing and reporting. Some events, such as “shouting racially charged slurs or posting derogatory comments online would not meet the hate crime threshold and would not be captured in police statistics despite that [they] are clearly an expression of societal [hate and discrimination] that should still be noted” (B’nai Brith Canada, 2016, p. 9) when trying to assess the “climate of hate” that is present in Canada (and elsewhere). Tracking these non-criminal hate incidents allows for independent monitoring and documenting of “troubling and dangerous occurrences that are considered non-criminal in Canada” (B’nai Brith Canada, 2016, p. 9).

Another important reason to capture hate incidents is to understand the motivations for hate, even if no crime has occurred. Examining the motivation – or the bias indicators present during the act – can provide further awareness of what conditions related to hate and bias led to the incident. According to the Facing Facts Guidelines for Monitoring Hate Crimes and Hate Motivated Incidents (2012),

“Bias indicators are objective facts that should be considered in determining the presence of a bias crime [or incidents]. They do not, in themselves, confirm that any incident was a hate incident. However, a bias indicator provides an indication that further investigation with a view to establishing motive may be required. It is vital to record this information in order to evidence the possibility that an incident was bias-motivated. Without this information, investigators are unlikely to take the allegation seriously and organizations will not report it. This is also important for the purpose of data collection” (Facing Facts, 2012, p. 13).

Examples of bias indicators include perceptions of the victim or witness that an act was fueled by bias and hate, the location of the incident, or a history of previous bias crimes and incidents in the area. For example, at the mosque in Quebec where the shooting occurred, police had responded to the mosque seven times over recent years in relation to hate-motivated acts – the most recent (prior to the shooting) was in 2016 during the Islamic month of Ramadan where a gift-wrapped pig’s head was left in front of the mosque with a card saying “bon appetit” (Shingler, 2017). Table 1 below provides the full list of bias indicators, as defined by the Facing Facts Guidelines for Monitoring Hate Crimes and Hate Motivated Incidents (2012).4

Table 1

Facing Facts EU List of Bias Indicators.

Bias Indicator Description

Victim perception The victim perceives the incident was motivated by bias
Witness perception The witness perceives the incident was motivated by bias
Difference between suspect and victim Do the suspect and victim differ in terms of racial, religious, ethnic/national origin, gender, or sexual orientation?
Location Was the victim in or near an area commonly associated with or frequented by a particular group?
Timing Did the incident occur on a date of particular significance for the target group? Examples include religious holidays, cultural celebrations, or PRIDE day.
Language and words used Did the suspect make comments, statements, or gestures regarding the victim’s background?
Organized hate group Were objects or items left at the scene that suggest the incident was the work of an organized hate group?
History of previous bias incidents/crimes Is there a history of similar incidents in the area?

Providing a platform for users to document and report hate incidents increases the potential of encouraging people to report hate. As a 2014 report from OSCE/ODHIR on the collection and monitoring of hate crime data suggests,

“in order to increase victim and community reporting of hate crimes, police forces and other civil authorities need to develop strategies to encourage victims to report. As long as victims under-report hate crimes, any official system for identifying and recording them will fall short” (OSCE/ODIHR, 2014, p. 24).

This is a significant point to consider, as it alludes to the importance of reporting hate incidents. Without providing official and alternative mechanisms for victims of hate to report, hate crimes and incidents will continue to be under-reported. The literature that has been written about the under-reporting of hate crimes suggests that victims are less likely to report their victimization to the police when compared to other crime victims (Janhevich, 2001). Additionally, research conducted in both Canada and The United States suggests under-reporting of hate crime victims who are targeted based on their sexual orientation is particularly high when compared to other groups who are often the victims of hate-motivated offences, such as ethnic or religious groups (see: American Psychological Association, 1998; Roberts, 1995; Comstock, 1999). As a result of this under-reporting, alternative methods are needed to support victims of hate.

Reporting hate online

One such platform to encourage the reporting of hate (and other potentially criminal incidents) is the Internet. While many police services around the world provide an option for reporting crime online, very few provide opportunities for victims and witnesses to report hate. In fact, in Canada, only one police agency (the Ottawa Police Service) provides citizens with the option of reporting hate crime online.5 As Woods (2013) explains, online hate/bias reporting has the potential to avoid common obstacles and barriers to reporting hate crime, such as fear of public exposure or mistrust of the police. The Internet, Woods argues, “may also be a more appealing method for [hate]/bias reporting for youth, who are more inclined to use computer technology” (Woods, 2013, p. 88). Other benefits of online hate/bias reporting include informants having as much time as they need to formulate a detailed account of the incident, and the use of private electronic communication for follow-up contact information (Woods, 2013).

Despite the positive attributes in reporting hate and bias online, there are several challenges. First, the subjective nature of hate and bias makes it difficult to accurately capture the validity of the incident, especially if limited information is included in an initial report. Second, if potential respondents believe that law enforcement will be reviewing the information, some might be hesitant to report incidents due to fear of additional victimization by the police (Perry, 2001). While police services certainly have a role to play in providing additional methods for those impacted by hate to report (see Woods, 2013), “outsourcing” the creation and maintenance of an online hate and bias reporting portal might be better suited to non-law enforcement entities. As a 2016 study of hate crime reporting by Wikes et. al found, numerous groups victimized by hate and bias suggest that reporting via a third party (i.e. non-law enforcement) mechanism is a possible way forward to increase reporting of hate and bias (Wikes et al, 2016). While Chakraborti et al. (2014) caution on the effectiveness of utilizing third-party platforms for improved hate and bias reporting, “the important characteristic of online hate and bias reporting is that it serves as an important springboard” (Woods, 2013) for supplementary spaces for victims and witnesses to document incidents of hate and bias. It is in this context of providing supplementary methods for reporting hate and bias (incidents) that the StopHateAB.ca online hate incident reporting tool was created.

Overview: The StophateAB.ca Online Hate Incident Reporting Tool

The StopHateAB.ca website is an initiative of the Alberta Hate Crimes Committee (AHCC). Established shortly after 9/11, the AHCC is a collaboration of community, law enforcement, and justice representatives committed to bringing comprehensive insight to the issue of hate crimes and incidents in Alberta. Each partner organization of the AHCC provides a unique view for addressing hate. For example, the law enforcement partners provide legal expertise as well as a “direct line” to address hate crime, while the community/non-governmental partners provide subject matter expertise (related to diversity, inclusion, and human rights) and a “direct line” to concerns from the broader community regarding hate. The justice representatives (who are often from various areas of the provincial government) provide awareness of grant and funding opportunities for the group to consider to support their work. As a result of the multifaceted points of views, the AHCC is well suited to address hate in all its forms. One such form involves hate incidents and the reporting of those incidents. As mentioned above, the main difference between hate crimes and hate incidents is the criminal element involved. Hate incidents are non-criminal acts committed against a person or property, the motive for which is based in whole or in part upon hate, based on race, national or ethnic origin, language, colour, religion, sex, age, mental or physical disability, sexual orientation, or any other similar factor. While hate crimes reported to the police are documented and captured in Statistics Canada’s annual hate crime report, hate incidents often go undocumented. In response to this, the AHCC created the StopHateAB.ca website in 2017 to capture and document hate-fueled incidents which do not meet the criminal threshold. Documenting and sharing information related to hate incidents provides clear examples of “hate-motivated behavior” (B’nai Brith Canada, 2016, p. 9) and highlights the importance of considering bias indicators (Facing Facts, 2012) to shed light on incidents of discrimination.

The StopHateAB.ca website provides visitors to the site with a space to report and document hate incidents which occur in the province of Alberta. When visitors enter the website, they are directed to a form in which they can share information related to the incident. The form was created in collaboration with AHCC stakeholders, and follows best practices identified in theFacing Facts Guidelines for Monitoring Hate Crimes and Hate Motivated Incidents (2012), Hate Crime Data-Collection and Monitoring mechanisms: A Practical Guide (OSCE/ODIHR 2014,; and the FBI Hate Crime Data Collection Guidelines and Training Manual (2015). Figure 1 is a screenshot of the online form from the StophateAB.ca website. As the figure shows, the form is designed to be simple and easy to use and not take too much time to complete. Respondents are free to fill in as much information as they deem appropriate. Part of the reason for keeping the form as simple as possible was to encourage people to use the form. An initial review of other similar online hate reporting platforms showed that some of the available forms were too long and asked for far too much information that a victim or witness of hate and bias might be comfortable in filling out.

Figure 1 

Screenshot from StopHateAB online reporting tool “Document a Hate Incident” page.

The form asks the visitor to the site to select (via a drop-down menu) the type of incident. This list includes threat, hateful material, vandalism, slur, graffiti, hate speech, and “other”. The list was compiled after reviewing reported hate incidents through media reports as well as in consultation with law enforcement partners of the AHCC. The reporting tool’s second drop-down list asks visitors to identify the motive behind the incident. Types of motives include race, ethnicity, religion, sexual orientation, disability, and “other”. This list was generated by using the most common motives for hate crimes as reported in annual hate crime reports from Statistics Canada. The final drop-down list asks the person reporting to select the location that “best describes” where the hate incident took place. This includes transit stations (bus/train), private residences, private vehicles, places of worship, public streets, online, University/College campus, places of business, shopping malls, shared public spaces (such as a park or a recreation center), and “other”.

It is important to note that the motive list does not allow the person reporting to provide further information, nor does it provide an opportunity to select multiple motives (something which the website is currently working on). The reason for limiting the amount of information under the “motive” drop-down list is to allow for information to be captured in a logical way in order to avoid confusion prior to the validation stage (which will be discussed in more detail below). This function, however, does not limit the effectiveness of the reporting tool, as it still allows users to document “a range of bias motivations that may form the basis of hate” (OSCE, 2014, p. 14). Within the form itself, users can go into as much detail as they wish when they fill out the section asking them to describe what happened. Once the form has been completed, users have the option of providing their email address for follow-up. They also can share ideas on how they think incidents of hate and bias should be addressed. Neither of these fields, however, are mandatory.

Once the online form has been submitted, the information is captured in a spreadsheet which only the website developer and the primary researcher for the AHCC have access to. The spreadsheet is connected to the form on the StopHateAB.ca website, which allows for easier data capturing and analysis. Once a report comes through, the “coders” (which includes the principal researcher and another volunteer who has been trained in the validation process) read through the narratives provided for each report. (If no narrative has been provided, the report is still accepted, however, it is not reflected in the StopHateAB.ca quarterly reports to the community and stakeholders). Through reading the supplied narratives, the coders look for bias indicators. As mentioned above, bias indicators are objective facts that should be considered in determining the presence of a bias crime [or incidents] (Facing Facts, 2012). If two or more bias indicators are present in the narrative, and both coders agree, then the report is captured as a validated hate incident. This process allows for a thorough review of the information provided and establishes a threshold for how information is validated. While some might argue that this process still allows room for error due to the subjective nature of interpreting bias indicators, traditional methods of hate and bias reporting pose similar risks (Woods, 2013).

Through this vetting process, verified information is shared via public reports and through the hate incident map available on the StophateAB.ca website. As Figure 2 showcases, the hate incident mapping tool allows users to see where documented hate incidents have occurred. Users can click on the “hotspot” to receive further information about the incident. Through this process, the StopHateAB.ca website follows practices identified by the OSCE/ODIHR 2014 Hate Crime Data-Collection and Monitoring Mechanisms guide where data-collection on hate provides a better understanding of the prevalence and nature of hate, as well as a mechanism to communicate the broader impacts of hate to affected communities and the wider public (OSCE/ODIHR, 2014).

Figure 2 

Screenshot from StopHateAB interactive map.

Analysis: Documented Hate Incidents from StopHateAB

Since its launch on February 13, 2017, the StopHateAB.ca website has had over 6792 unique visitors and a total of 23,782-page views. From February 13 to March 30, 2020, there were 264 incidents reported on the website. Of the 264, 109 documented incidents were omitted from analysis. Reasons for this include duplicate entries due to user error (when a person entered the same incident more than once), frivolous entries (users who visited the website to claim the website itself promoted hate, and therefore, are reporting the website as an example of a hate incident), and entries not verified as a hate incident (due to a lack of a narrative or the reported incident was not fueled by hate). Through this vetting process, 155 documented hate incidents reported through the website have been validated as legitimate hate incidents. The most common “type” of hate and bias incident documented was “derogatory slurs” (40 percent) and the most common “motive” was race/and or ethnicity (70 percent). In terms of where the documented hate incidents occurred, shared public spaces were the most common places identified.

In addition to the quantitative data the online reporting tool provides, narratives included in each reported hate incident highlight interesting qualitative insights that provide further context to what people are experiencing or witnessing. Table 2 provides examples of what users have reported so far.

Table 2

Hate motive and example narrative from StopHateAB reports.

Motive Narrative Provided

Religion “Stranger walked by woman in hijab, spat at her and said ‘go home’”.
Race/Ethnicity “Found a blood and honor sticker at the campus transit station”.
Race/Ethnicity “Threat made to physicians wife and two children to get rid of a black physician”.
Sexual Orientation “Wasa guest in someone’s home, they knew I was bisexual made multiple ‘jokes’ using the word fag, at one point said ‘f***ing fags complaining. F**k their pride week’.”
Race/Ethnicity “The text “White Power” was written on a whiteboard in a public hallway of a department at the University. It was accompanied by a swastika. Thereis belief it is targeted at Indigenous women scholars.”

These narratives provide insights into the types of hate and bias occurring in Canada. What these documented hate incidents tell us is that much work is needed from our collective multicultural society to address factors contributing to hate – whether they be a crime or an incident – and the power dynamics at play in the presence of these hate fueled interactions. As Perry (2015) meticulously explains,

“[An indicator] of the challenges of multiculturalism is hate crime [and incidents], and its underlying prejudices and relations of power. Hate, in many respects, is a reaction to the “fact” of increasing diversity in Canada. Faced with dramatic shifts in the demographics of the nation, along with the increasingly strong voices of those long silenced, many Canadians fear loss of long-standing privilege and supremacy. One readily available mechanism by which to express their hostility is indeed [through] hate” (Perry, 2015, p. 1642).

Through online reporting tools such as the StopHateAB.ca website, hate incidents can be made visible in order to showcase the reality of the situation in order to challenge narratives that overt forms of discrimination are a thing of the past.

Discussion: Lessons Learned creating an online hate incident reporting tool

The StopHateAB.ca website was created to fill a reporting gap present in incidents of hate and bias. By providing an alternative space outside of law enforcement and official government databases for members of society to document, report, and share trends related to hate, the StopHateAB.ca website furthers the importance of collecting and maintaining reliable data and statistics on hate as an essential tool in countering hate-motivated incidents from a policy and resource allocation point of view (OSCE/ODIHR, 2014). One of the intended purposes of the data collected from the StopHateAB.ca website is to share the findings with government stakeholders in order to lobby for further support and resources from provincial and federal orders of government. “In the absence of official data-collection mechanisms, civil society organizations are often the only sources of information about the nature of hate, their impact and the barriers to justice and safety victims face” (OSCE/ODIHR, 2014, p. 2). More importantly than their collection, however, is the sharing of the information because it helps fill in the gaps of an ambiguously defined set of behaviors. By making information related to hate accessible for wider public consumption, members of civil society are better aware and informed of the reality of hate. While some might argue that collecting and sharing information on hate that is not criminal in nature “leads to an obfuscation of the reality” (B’nai Brith Canada, 2016, p. 21) of hate in Canada, the information captured within online hate incident reporting tools allows civil society to track more than just what the justice system deems as forms of hate. Additionally, online reporting tools related to hate and bias should be seen as supplementary to what official databases on the same topic share (Woods, 2013), as this provides a holistic and broader understanding of hate and bias. When taken together, official and non-governmental organizations data related to hate and bias can act as a barometer to help determine the climate of hate in Canada.

Moving beyond data collection, however, is the opportunity online hate incident reporting tools provide for victim support. The relative ease of use and safety of reporting a hate or bias incident online allows the reporter to comfortably report what they either witnessed or experienced in their own safe space. “Tools that measure unreported hate and their impact on victims can provide a better indication of the true volume of hate, as well as valuable information about the impact of hate on victims” (OSCE/ODIHR, 2014, p. 33). While some countries, such as Canada, provide official data on victims of hate crime every five years through the General Social Survey (GSS), data captured through online hate incident reports provides further information which might not be shared through the GSS. The ease of use for documenting an incident of hate online cannot be overstated. As Woods (2013) explains, “bias informants can take as much time as they need to formulate a detailed written description of incidents in their own words, especially if the victims and witnesses are hesitant to use in person or telephone reporting methods” (p. 93).

Another important positive aspect of online hate incident reporting tools is community engagement. As many hate and bias data collection guides highlight (see Facing Facts, 2012; OSCE/ODIHR, 2014; and FBI Hate Crime Data Collection, 2015), the importance of sharing the information with wider community stakeholders is a key contribution in making hate visible. Since the StopHateAB.ca hate incident reporting tool launched, the Alberta Hate Crime Committee has hosted a number of community engagement sessions, particularly in rural areas, in order to share data reported, raise awareness of the reporting tool, and build relationships and learn from community stakeholders on how general civil society can counter hate and bias. What these types of engagement sessions provide is a space to reflect and dialogue on the impact of hate using data collected through the online reporting tool and encourages further reporting of hate through the discussion sessions.

While the above examples cite initial successes of online hate incident reporting tools, there are several barriers to overcome as well. Firstly, one of the major issues when engaging with the topic of hate in general is the “slipperiness of the term and the lack of consistency in the way it is used” (Sheppard et al., 2015, p. 4). Boundaries of what is or is not hate largely depend on one’s positionality and how behaviors that might seem like hate to one group are valid criticism to another (Sheppard et al., 2015, p. 4). Because of this subjectivity, reports which come through online hate incident reporting mechanisms must be assessed to ensure validity and legitimacy. This is where utilizing the lens of bias indicators (as discussed above) becomes a very useful assessment tool. Secondly, another challenge of online hate incident reporting tools relates to the “trustworthiness” of the information provided. For example, when the StopHateAB.ca website first launched and started to receive reports, questions from committee members regarding the authenticity and truthfulness of the reports started to surface. While a valid concern, researchers such as Woods suggest that this should not discourage the use of online hate and bias reporting, as traditional methods of bias-crime reporting pose similar challenges (Woods, 2013). Finally, an ongoing obstacle with online hate incident reporting tools relates to awareness. Put quite simply, if people do not know the tool exists, they obviously do not report through the online form. Constant promotion and awareness activities are required if the online tool is to be effective.

Conclusion

This paper highlights the development and early learnings from the StophateAB.ca online hate incident reporting tool. Through a discussion of the strengths as well as challenges of developing online hate incident reporting tools, this paper provides a suitable blueprint for which other jurisdictions can consider when thinking about implementing similar tools for their own communities. The StopHateAB.ca website is just one of a number of online hate incident reporting tools, however, what makes it different is its transparency for how information reported through the website is validated and shared for wider consumption. Although this online tool is limited to one Canadian province, similar tools can be developed for other areas.

Perhaps the most important consideration for the StophateAB.ca website is the fact that it is inclusive to all groups who experience hate, and not specific to one group or one community. What this provides is a broader perspective and understanding of how hate impacts a wider spectrum of individuals and what civil society can do as a collective to address the issue. The importance of including key stakeholder in the development of similar tools is also important to consider. While non-law enforcement entities can be the developmental hub for these initiatives, the inclusion and subject matter expertise of law enforcement is vital if these reporting tools are to succeed. As showcased by the StopHateAB.ca website, having the perspective of law enforcement at the development table ensures that their subject matter expertise is valued, and creates an important pipeline of support when incidents that are criminal in nature get reported through the tool.

Broadly speaking, online hate reporting tools, when done in partnership with a cross section of stakeholders, provides additional options for victims and witnesses of hate to document and report these occurrences. Broad implementation of online hate reporting tools allow for government and non-government entities interested in addressing hate in their community additional information which provides a holistic understanding of the climate of hate occurring in various cities around numerous countries. Tools such as this take the onus away from law enforcement to “solve everything” and empowers non-governmental organizations and civil society as a whole to collectively come together to understand and counter the hate occurring in our communities and provides the advocacy and allyship required to meaningfully #StopHate.