We need more race-based data to tell stories that matter

For years, anti-racism advocates, researchers, policy experts, and politicians have called for better race-based disaggregated data collection from different levels of governments in Canada.

Without better data, evidence-backed policymaking is difficult, and the public isn’t able to get the full scope of racial and ethnic disparities and progress to tackle it.

Grace-Edward Galabuzi, associate professor in the Department of Politics and Public Administration at Toronto Metropolitan University in Toronto, talks to Monitor Online about why it’s important to have such data.

Why is it important to have disaggregated race-based data?

Disaggregated race-based data helps to identify and address racial disparities. It supports evidence-based policymaking and allows us to determine what approaches to delivering services work and don’t work. It provides the kind of detailed, reliable information we can use to build towards racial equity.

Organizations aware of service practices that result in racial or implicit bias, for instance, can make changes to training. Evidence-based policymaking and service delivery also provides transparency and accountability and helps build trust and public confidence.

Race-based data collection allows us to study, review, and explain our actions. Public institutions such as hospitals, post-secondary institutions, school boards, police forces, and social services can better communicate with their communities and track whether their organization strategies are successful. 

Finally, it supports teaching and learning. We can use best practices from other jurisdictions that are already collecting and using race-based data to achieve more effective and equitable practices and outcomes. Data collection and training should be embedded within a broader anti-racism strategy that is sustainable, renewable, and accountable.

What stories are we able to tell and not tell with and without such data?

Race-based data allows us to tell the stories of challenge and triumph in minority communities and populations that are often hidden from view due to neglect from mainstream institutions and media. We can validate the anecdotal stories we hear about everyday experiences of racialization and address the tension between service providers and communities that arises from these experiences.

We can track the systemic impacts of racism and anti-Black racism that create disparities in various experiences with public institutions, such as overrepresentation in the criminal justice system and child welfare systems, disparities in poverty rates, and those with lower socio-economic status. It can also inform us about differential access to leadership opportunities, such as corporate board and public appointments, affordable and safe housing, and disparities in educational and mental health outcomes.

During the COVID-19 pandemic, we couldn’t tell the story of differential impacts based on race without race-based data. As it was, according to Toronto Public Health reports detailing race and income in Toronto, Black, Indigenous, and people of colour are over-represented in the infections and deaths from the virus.

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Race-based data allows us to tell the stories of challenge and triumph in minority communities and populations that are often hidden from view due to neglect from mainstream institutions and media.

Black and Brown Torontonians make up 73 percent of the COVID-19 cases while representing only 36 percent of the population. Black individuals make up nine percent of the city’s population but accounted for 34 percent of the COVID cases by August 2020.

Similar results were reported from Peel Regional Public Health Unit from mid-April to July 2020: Residents of South Asian, Black, and Latin American origin were over-represented in COVID-19 cases, while white residents were under-represented compared to their proportion of the population.

We were able to understand that precarious employment and income insecurity were killing people of colour.

It seems like other countries, such as the United States, do a better job of collecting race-based data than Canada. What is the history of such data collection in this country?

Other jurisdictions have been collecting race-based data for a long time and use it effectively to guide the delivery of services. This is the case in most American jurisdictions as well as in the United Kingdom, particularly with policing.

In the U.K., the Race Relations Act mandates all police forces to collect self-defined ethnicity data in police stops and searches. Police forces also require data collection of officer perception of ethnicity using a smaller number of categories, namely the identity code system. That data has been used to address disparities in police stop and search practices, known as stop and frisk in many U.S. jurisdictions. They have demonstrated that these practices disproportionately focus on Black and Brown people in many cities.

Police in Canada have historically not been required to collect race data in stop-and-search practices.

However, the Toronto Star has investigated racial profiling using arrest data from the Toronto Police database. The data analysis shows that Black individuals are three times as likely to be stopped as white individuals. A public debate about carding led to some police forces introducing reforms.

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Police in Canada have historically not been required to collect race data in stop and search practices.

Kingston, Ont. police undertook a data collection project in the 2000s, working with criminologist Scott Wortley. It involved the quantification of racial and ethnic origin of individuals stopped by Kingston Police officers in non-casual situations between 2003 and 2004. It found Black male residents of Kingston, aged 15 to 24, were three times more likely to be stopped by Kingston Police than any other racial group. Black individuals were also slightly more likely than other racial groups to be arrested and charged during police stops.

It was the first police force in Canada to collect and analyze race-based data pertaining to police stops. It was also the first police force in Canada to acknowledge the prevalence of racial profiling and make a commitment to adopting bias-free policing.

In 2019, the Toronto Police Services Board passed a policy to require its collection.

What specific and urgent areas of data are we currently missing?

Race-based data collection is essential in all public services such as education, health, justice, housing, child protection, and other social services. But is it also critical in the employment and labour market, in immigration and settlement services, in business, and the broader private sector

A critical piece of the puzzle is Statistics Canada. As Canada’s primary institution for data collection, it collects data in a disaggregated format for all the many uses its data can be put to. Labour market data is increasingly being collected to reflect the differences in the experience of racialized populations after decades of community and academic demands for such data. This will have a significant difference in how policy and program development are undertaken going forward. The same has to be done for health to ensure health equity, as COVID-19 clearly demonstrated, and for other sectors where disparities define the experience of Canadians.

Do you believe we will see more and improved disaggregated race-based data collection in the near future?

There is likely to be more collection of race-based data going forward. In particular, Ontario has now legislated a framework for data collection. There has also been longstanding calls from the community for race-based data collection, which dates back to the 1970s, and a number of reports have called for collecting race-based data, including the Ontario Human Rights Commission’s (OHRC) interim reports on racial profiling and Ontario’s Office of the Independent Police Review Director’s Breaking the Golden Rule report on strip searches.

The Ontario Human Rights Commission has established a protocol for collecting and analyzing data in a human rights-safe way—what it calls “code-consistent purposes”—with the objective being to further the purposes of enforcing the Ontario Human Rights Code and advancing human rights protection. Among other things, this includes monitoring, measuring and addressing gaps, trends, progress and perceptions so as to improve opportunities for disadvantaged groups to enjoy full access to Ontario life and citizenship.

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We shouldn’t forget that race and identity-based data collection is as much about tracking what service providers are doing well, as they are about potentially uncovering racial disparities.

The 2017 Province of Ontario Anti-Racism Act mandates the collection of race-based data for the purposes of addressing systemic racism and promoting racial equity. It created a set of standards for consistent collection, analysis, and reporting. These include standardized requirements to collect personal information about Indigenous identity, race, religion, and ethnic origin to allow for comparisons across sectors, and over time. It also includes privacy protections to prevent the misuse of personal information, analysis requirements to identify and monitor racial inequalities in public sector policies, programs, and services, and open data and reporting to enable public transparency and accountability.

The act also identifies public sector organizations required or authorized to collect race-based data and takes a phased approach covering organizations in justice, child welfare, and education. Police services are also required to collect race-based data for use-of-force reports, which began in 2020.

Ontario’s framework for race-based data collection provides a foundation to help the government and the public sector identify, understand, and monitor whether specific segments of the population are experiencing adverse impacts of systemic racism and barriers in programs and services.

We shouldn’t forget that race and identity-based data collection is as much about tracking what service providers are doing well, as they are about potentially uncovering racial disparities. Going forward, the collection, analysis, and use of race-based data will become a mainstream effective tool for addressing racial disparities in service delivery and beyond.

This Q&A has been edited and condensed for style and clarity.

Jolson Lim (he/him) is a communication specialist for the Canadian Centre for Policy Alternatives. He was previously a news reporter on Parliament Hill. Follow him on Twitter at @JolsonLim.

Grace-Edward Galabuzi (he/him) is Associate Professor in the Department of Politics and Public Administration, and a member of the Yeates School of Graduate Studies at Toronto Metropolitan University. He is on the CCPA Board of Directors.