When joblessness rates and food bank use soared during the first year of the COVID-19 pandemic, many Canadian social purpose organizations realized they needed better data in order to respond well.

Researchers in Canada have known for decades about how racialized communities, women, newcomers to Canada, and working-class neighbourhoods all suffer disproportionately bad health compared to their whiter, wealthier counterparts. The pandemic was no exception. Perhaps the starkest example came out of Toronto Public Health’s findings that the city’s most racialized regions – such as Scarborough – had among the highest rates of COVID-19 infections and deaths.

Social impact organizations sometimes struggle to interpret data collected by Statistics Canada, academics, think tanks and private research organizations. But Shalini Sharma, director of research and policy at the Canadian Council for Youth Prosperity (CCYP), says disaggregated data is available through Statistics Canada. Through the Long-form Census, issued every five years, the federal government asks Canadians a plethora of questions useful for gathering disaggregated data: What is your race? Your ethnicity? Country of origin? Gender identity?

“That’s great for looking at long-term trends,” Sharma says of the Long-form Census, “but what we do need to know in a short-term way are the short-term fluctuations.” Comprehensive as the census may be, it hasn’t yet captured all of the job loss, food insecurity, mental health episodes, financial insolvency, or infection of the last 21 months.

If Canadian non-profits, charities, foundations, INGOs and other social purpose organizations want to address the intersectional nature of COVID-19 – how racialized communities are more vulnerable to infection, death, and job loss as a result of the pandemic – they’ll need all the data they can get. Disaggregated data in particular can be used by social impact organizations to improve programs and services, better connect with communities about their needs, or tell better stories to donors. The trick for agencies such as Statistics Canada will be issuing data in a way that sector leaders can understand – and teaching the sector about the use and context behind major trends.

Smarter program and service design and delivery

Project Work, a Toronto-based employment charity that connects intellectually disabled people to jobs, quickly launched programs to address the COVID-related mental health challenges of its clients when the pandemic first arrived. Haris Blentic, Project Work’s executive director, says the charity offered these services because it was clear their clients needed them. But much of Project Work’s data comes from its own programming.

Blentic says Project Work does get some outside data on labour market statistics, as well as more sector-specific figures from industry organizations. They work with the Ontario Chamber of Commerce to try and find placements for their clients. “What would have been even more powerful,” Blentic told Future of Good, “is having data on the percentage of the population in Toronto that is disabled – and with intellectual disabilities.”

Having that information at hand could have helped CCYP drill down on broad, aggregate numbers about youth job loss during the pandemic to find overlooked clients who might need very specific help. Sharma says there is a lot of anecdotal evidence that international students who study at Canadian colleges are employed in the service sector – unsurprising, given their age. “If students are picking up the slack, we need to know,” Sharma says, especially given the pandemic-related job losses among youth in Canada’s service sector. 

If CCYP had disaggregated data to accurately track college-attending international students, they’d be able to not only respond with programs tailor-made for their needs – which might include language barriers, a lack of family in Canada, or visa issues – but also pass that information along to other like-minded youth organizations. 

Better information for grantmakers

Along a similar vein, Canadian community foundations with access to good disaggregated data can get a better sense of what their specific cities, towns, villages, or regions need beyond broad national figures. “Once you have that information, you can really target the issue with your granting or your advocacy or consultations,” explains Alison Sidney, director of strategic initiatives at Community Foundations of Canada.

Sidney says CFC tries to find data that is disaggregated by sex and race whenever possible. “Intersectionality is so important when you’re doing any sort of research and that’s something we stress to our community foundations and anybody who reads our reports,” she says. 

Through the pandemic, CFC started to do more community consultations than they ever had before. Sidney says only then did they start to understand the living conditions of different demographics across Canada — and how they needed help. The resulting Emergency Community Support Fund, run through the Canadian government in partnership with the United Way Centraide Canada and the Canadian Red Cross, delivered $350 million to equity-seeking groups. All of the work involved in meeting with communities, working through grant applications, and making decisions was thanks to consultations. “It’s good information for us to have,” Sidney says — and not just for the fund itself. “Who are we reaching? Who do we still need to figure out how to reach? It’s a continuously evolving process.” 

Understanding the specific needs of a community in all its complexities through disaggregated data could help grantmakers like CFC and its members not only figure out what is needed, but how best to deliver it to maximize impact. 

More compelling donor stories

Retaining donors is critical for any charity or non-profit at the best of times. During the early months of the COVID-19 pandemic — when demand for shelter, food, and mental health supports were at record highs — social impact organizations found themselves facing steep revenue drops. Events like the Stronger Together coast-to-coast-to-coast concert series, organized by Food Banks Canada, secured millions in donations, but maintaining steady fundraising has been a challenge. 

Good disaggregated data on what non-profits and charities are doing in their communities already (and what remains to be done) could have helped boost donor dollars at critical times during the pandemic. Richard Daneau, general manager of Moisson Montreal, a non-profit that distributes donated food across the city, says that knowing the circumstances of who receives food donations can help them tell their story to donors — and solicit more support. 

“It is through relationship-building with donors that were in a position to give $120 million worth of food last year,” Daneau says. “In order to keep moving, we need to be able to tell stories on what the agencies are seeing.” Better disaggregated data could show organizations like Moisson Montreal which users stop at multiple food banks, how race or gender affects the circumstances behind food bank use, and which neighbourhoods have the highest rates of food bank use. Those stories, in turn, could drive better donor engagement. 

Daneau says Moisson Montreal has a pilot project with a few dozen of its agencies to start tracking food donations in its system. The project isn’t meant to interfere with local community agencies, he says – rather, it may help donors to Moisson Montreal better understand local dynamics around food insecurity. “At the end of the day, all non-profits are stuck with the same problem when they visit donors to beg for money,” Daneau says. “And they say — what is the money for?”

CONCLUSION

Disaggregated data is already gathered by Statistics Canada, public health officials, and some charities and non-profits. It played a role in highlighting stark inequalities triggered by the COVID-19 pandemic, and will undoubtedly be used to map out long-term implications for recovery. 

But for some social impact organizations, using disaggregated data is tricky. Half the battle for disaggregated data is understanding it in the first place. Sharma says that sector professionals sometimes don’t understand how to interpret statistics or place them in context.

It doesn’t help that Canada’s best sources of disaggregated data, such as Statistics Canada’s Labour Force Survey and the Long Form Census, release data that is often years old. They’re quite good at capturing long-term trends, but when disasters like the COVID-19 pandemic strike, organizations like CCYP and Project Work are forced to design programs, services, and resources based on what their clients are telling them.

“The information that we need to inform our services is not very accessible,” Blentic says. “It does exist out there, but accessing it in the best way possible and getting to it is a challenge.”

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