Evictions are a leading cause of housing insecurity in cities worldwide, disproportionately affecting lower-income households and non-white racialized groups. In Canada, although attention to evictions is growing, there is limited research available. As the most populous city in the country, Toronto is home to a diverse set of households while also being one of the country’s most unaffordable places to live. Given the nation’s ideological focus on multiculturalism, differences across racial and ethnic groups are often muted or rendered invisible.
While policymakers and housing actors advocate for more supply, less attention is paid towards discrimination and displacement. Framing evictions solely as an outcome of market pressures obscures their deeper role in (re)producing racial inequities. Recognizing eviction as a racial justice issue requires shifting administrative practices and policy approaches to address systematic discrimination embedded within housing systems. Bannerji (1996) argues that “the discourse of multiculturalism, as distinct from its administrative, practical relations and forms of ruling, serves as culmination for its ideological construction of ‘Canada’.” Both academic and policy discourses often overlook, and underestimate, the racialized dimensions of displacement pressures. This continued oversight collapses the experiences of different racialized groups, not only for Black and Indigenous communities, but also South Asian, Filipino, and Chinese households, among others.
One way Canadian society invokes this discourse lies within its data practices and its identification of non-white people through the category of “visible minority.” This stems from a widespread multiculturalist ideology that lies at the heart of Canadian identity. Kay Livingstone coined the term “visible minority” in 1975 to serve as an organizing tool for the Canadian Negro Women’s Association to challenge discriminatory institutional practices in the areas of immigration, policing, and education. Years after Livingstone’s passing, the Canadian government implemented the term through the Employment Equity Act in 1986 to denote non-white, non-Indigenous people—a common practice to this day. At the time of origination, the term served a political purpose. Wharton-Zaretsky (2000) notes that “[a]lthough the term has become a contentious issue today, at the time of its inception it was seen as a ‘radical’ descriptor of [minority groups’] location in Canadian society.” Since then, the country’s population has grown to over 40 million, encompassing a range of cultural and ethnic origins. While a “radical” idea 50 years ago, today this classification is increasingly critiqued for its homogenizing effect, which obscures the varied and unequal experiences of different racialized groups.
Over the past decade, federal immigration targets in Canada have driven population growth in urban and suburban areas, particularly in the Greater Toronto Area (Dantzler and Urban Policy Collective 2022). Many newcomers settle in older, lower-cost rental housing, from which inhabitants are increasingly at risk of eviction as landlords seek to remove long-term tenants and raise rents. Although rent control in Ontario is designed to protect tenants from excessive rent increases, extant research on eviction patterns shows that rent control is not working for low-income tenants, and that its failures are experienced more among non-white racialized groups. Leon and Iveniuk (2020) showed that eviction rates vary widely ; Toronto neighborhoods with higher rates of poverty and larger Black populations are at higher risk. These neighborhoods are facing disproportionately high rates of eviction filings—two-and-a-half times and twice the average rate, respectively. When comparing eviction rates across Toronto political geographies, Leon (2021) found that wards with the highest number of Black households had the highest numbers and rates of eviction applications. Similarly, Mah (2021) found that areas with larger proportions of Black and newcomer households – groups that may overlap – experience higher rates of eviction filings. Other research has highlighted the risk of evictions for encampments (e.g. Rady and Sotomayor 2024) and the stark increase of such evictions during Covid‑19 (e.g. Brown et al. 2023). Chum (2015) found that evictions are more common in Toronto neighborhoods undergoing early stages of gentrification. Yet, given the reliance on aggregate data in a rapidly changing multicultural environment, quantitative approaches to the study of racialized displacement use census tracts as proxies for individualized experiences. Associations with aggregate measures are substantially weaker than with more micro-level measures, and more sensitive to sampling and times of data collection, especially in denser, rapidly changing neighborhoods or between census cycles.
These eviction studies typically combine data from the Landlord and Tenant Board (LTB) and census data from Statistics Canada (StatCan) to conduct their analysis. StatCan identifies race primarily through the “population group” and “visible minority” variables on the census. The population group question asks respondents to self-identify from single or multiple ethnoracial categories. From this, StatCan derives the visible minority classification, a legislated category that groups all non-white, non-Indigenous populations together (Statistics Canada 2021). However, the LTB—Ontario’s housing tribunal responsible for adjudicating landlord–tenant disputes—does not collect race-based data. Gupta (2022) highlights that the lack of race‑specific administrative data, such as tenant race, poses a major obstacle to understanding structural inequities in housing tenure. Without this data, scholars can only approximate the racialized impact of eviction by merging LTB case data with census racial demographics at neighborhood levels. Our analysis builds on this critique by disaggregating the category to highlight distinct eviction risks while highlighting the need for better data practices. This research explores the hypothesis that landlords are disproportionately targeting particular racialized groups, especially Black households.
Using eviction data from the LTB and census data from StatCan in 2016, this exploratory research examines the relationships between eviction filings and neighborhood racial diversity, property conditions (proportion of private dwellings in need of major repair and proportion of private households living in unsuitable housing conditions), and local housing economic factors (proportion of lower-income households ; proportion of households spending 30% or more of their income on shelter ; post-tax household income) across Toronto’s 140 designated social planning neighborhoods. These neighborhoods were chosen as the unit of analysis, given their role in municipal policy initiatives such as the Toronto Strong Neighborhoods Strategy and broader government investment in urban equity. As Calderón-Figueroa et al. (2022) note, many cities have created official neighborhood boundaries for target policy interventions.
We focus on L1 applications (for non-payment of rent and to collect rent the tenant owes) as it is the most common eviction filing (Figure 1).
To illustrate the importance of racial identification, we compare the statistical significance of the “visible minority” classification versus more disaggregated racial identifiers. We focus on the relative composition of Black, Chinese, Filipino, and South Asian households, given their relative population size across the city. Table 1 provides the descriptive statistics for our analysis.
Figure 2 illustrates the marginal plots of neighborhood eviction filings and their relationship to the proportion of visible minority households within a neighborhood. As the proportion of visible minority households increases within a neighborhood, we find a statistically significant positive relationship with the rate of eviction filings.
However, when exploring diversity within the visible minority group, the results show a more nuanced story. Figures 3 through 6 exemplify the relationship between the proportion of racialized groups and the rate of eviction filings at the neighborhood level.
Our results reveal an interesting story. As the proportion of Black, South Asian, and Filipino households increases in a neighborhood, the rate of eviction filings increases as well. However, as the rate of Chinese households increases in a neighborhood, the rate of eviction filings decreases. These bivariate relationships illustrate the unevenness of eviction risk for racialized households across the City of Toronto. Further exploration through regression analysis (using a log–log function) reveals additional insights when controlling for local property and economic conditions. Table 2 highlights the differences, and relative importance, of racial identification.
Our results provide nuance to existing research on the spatial distribution of evictions across Toronto. First, neighborhoods with higher rates of properties in need of serious repair also have higher rates of evictions filings. This relationship is relatively consistent across both models ; however, this finding is not surprising. Many of these properties tend to be older, below-market-rate units. With funding and regulatory reform enabling higher levels of construction, it is unclear to what extent older properties are serving as a form of affordable housing. It is quite plausible that landlords of older properties are employing strategic techniques, such as renovictions (i.e. displacement through major renovations or repairs) or demovictions (i.e. displacement through demolition), to displace tenants for the hopes of raising rents or replacing older, low-cost housing with new housing that, while possibly “affordable,” is more expensive than that which it replaces (Dantzler and Urban Policy Collective 2022).
Second, neighborhoods with higher ethnoracial diversity experience higher rates of eviction filings. However, the level and directionality of the effect depend on which racialized group is in question. In Model 2, like other studies, we find a strong, robust positive relationship between neighborhoods with higher proportions of Black households and higher rates of eviction filings. We also found a positive, although weaker, relationship between neighborhoods with more South Asian and Filipino households and the rate of eviction filings. Yet we found an inverse relationship when examining eviction rates in neighborhoods with higher proportions of Chinese households. That is, neighborhoods with higher proportions of Chinese households are associated with lower rates of eviction. Although this finding was not statistically significant, it raises questions about the extent to which Chinese households’ experiences may be distinct from that of other “visible minorities,” especially given their relative higher level of homeownership. This finding suggests the need for further exploration into how tenure status, migration histories, and cultural networks mediate eviction risk.
Third, local economic conditions did not fully explain the unevenness of eviction risk. Once our proxy for race was disaggregated, our measure for average household income was no longer statistically significant. This finding suggests that income does not fully explain the rate of eviction filings at the neighborhood level. Surprisingly, the proportion of lower-income households and the proportion of households spending 30% or more on shelter were not statistically significant. Yet the proportion of homes in need of repair was statistically significant across both models. As mentioned earlier, it is plausible that lower-income, non-white households are occupying older, deteriorating units. This finding also supports other work that argues that, much like the US, landlords in Toronto’s rental market exhibit pro‑white/anti‑Black bias towards where, and to whom, they lease rental units (See Hackworth et al. 2025).
This study has several limitations that highlight the need for further research. First, data constraints limit the number of control variables at the neighborhood level, affecting the scope of the analysis. Moreover, our inability to include Indigenous households owing to missing data highlights critical issues of data governance and sovereignty. Addressing Indigenous housing insecurity requires recognizing the colonial legacies of displacement while respecting Indigenous-led data practices. Second, while mapping eviction trends provides valuable insight, real-time disaggregated data is essential for more responsive policymaking. Entities such as the LTB must begin to report race-based data. Demographic data on both landlords and tenants would help researchers identify patterns of discrimination, assess how eviction disproportionately affects racialized communities, and design more equitable and just housing policies. Finally, this study focuses on eviction filings from 2016, offering a snapshot rather than a gradual change over time.
Future research should adopt a longitudinal approach, examining how eviction trends evolve over time and across different geographic scales, while incorporating indicators such as informal evictions and landlord harassment to capture the full scope of housing precarity in Canada. Future research should also pay more attention to Canadian cities’ rapidly changing urban morphology to understand the relational nature of local changes (e.g. how are neighborhood changes reflective of regional shifts ?). Moreover, additional questions emerge about housing insecurity and the roles that different types of housing actors (e.g. small- versus large-scale landlords, nonprofits) and housing models (e.g. social housing, housing allowances, community land trusts) play in mitigating or reinforcing it.
While not all filings result in tenant displacement, research suggests that landlords may use the legal process strategically to pressure tenants into leaving without formal eviction orders (Mah 2021). Yet, despite these racialized patterns, the phenomenon of eviction remains largely muted in discussions of racial inequality in Canadian housing policy. As Toronto and other cities push forward with housing supply expansion, policymakers and municipal leaders must consider how urban development strategies risk exacerbating racialized displacement and deepening inequities (Dantzler and Urban Policy Collective 2022). If eviction research and policymaking continue to overlook race, they risk reinforcing the very inequalities they claim to address. A racial lens is not optional—it is essential for crafting housing policies that genuinely protect those most vulnerable to displacement.
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