Socioeconomic Inequality and Student Outcomes in Canadian Schools

  • Alana ButlerEmail author
Part of the Education Policy & Social Inequality book series (EPSI, volume 4)


This chapter examines how income inequality in Canada has contributed to an “achievement gap” between students from lower and higher socioeconomic backgrounds in Canada. The impacts of socioeconomic inequality in the preschool and elementary years can lead to significant differences in academic achievement between children from affluent and lower income families. The chapter surveys existing research regarding low socioeconomic status and childhood academic outcomes and then explores structural and sociocultural factors associated with socioeconomic achievement gaps. Next, the chapter examines how cultural capital deficits directly affect access to postsecondary education. In conclusion, the chapter discusses some of the evidence-based interventions aimed at eliminating the socioeconomic achievement gap in Canadian schools.


Student achievement Socioeconomic status Inequality Canada 

10.1 Introduction

The 2015 PISA results continued to highlight Canada’s high standing in terms of educational outcomes for its youths in comparison to other international jurisdictions. Since the inception of PISA in 2000, Canada has placed in the top 10 in each cycle across all three domains: Reading, Mathematics, and Science. The most recent results inspired the British Broadcasting Corporation (BBC) to call Canada an “education superpower” (Coughlan, 2017). These high levels of overall student performance have occurred in spite of Canada’s relatively high level of immigration (Cheng & Yan, 2018; Klinger, Volante, & Bilgili, 2018; Volante, Klinger, Siegel, & Bilgili, 2017). PISA results and other international comparative measures of student achievement have each illustrated that between-school variation in student performance is very low in Canada, reflecting a high level of educational equity (e.g., Coughlan, 2017; Organisation for Economic Co-operation and Development, 2016b). In spite of this overall relative success, the media and others have raised concerns about the lack of educational progress based on unchanging or decreasing PISA scores over time (e.g., Chu, 2017). Yet a review of PISA data demonstrates that very few high-performing countries have witnessed a growth in PISA scores over time (Organisation for Economic Co-operation and Development, 2018a). Overall, the ongoing high levels of relative performance coupled with the low between-school variation found across PISA cycles do indeed illustrate that children in Canada benefit from high levels of education.

In most industrialized developed countries, there exists an academic achievement gap between the wealthiest and poorest students (e.g., Organisation for Economic Co-operation and Development, 2017; Parker, Marsh, Jerrim, Guo, & Dicke, 2018; Schmidt, Burroughs, Zoido, & Houang, 2015; UNESCO, 2014). The Council of Education Ministers, Canada (2018) found that Canada has the second most equitable education system with respect to socioeconomic status (SES). As an example, evidence from the United States indicates that low SES has a significant effect on educational achievement among children and youths (Ainsworth, 2002; Evans, 2004; Fagan, 2017; Hoxby & Turner, 2013). Canadian studies show that the gap between low versus high SES families is not as wide as it is in the United States, where there are larger geographical areas with a concentration of low SES populations (Burton, Phipps, & Zhang, 2013; Ward & Belanger, 2010). Clearly, Canada has been able to ameliorate some of the educational impacts of socioeconomic inequity observed in other highly industrialized developed countries. One important consideration is that 6.0% of Canada’s gross domestic product (GDP) is allocated to educational institutions, which is substantially higher than the Organisation for Economic Co-operation and Development (OECD) average of 5.2% (Statistics Canada, 2017c). As a result, teaching in Canada is considered to be a valued profession and teachers are well compensated.

While there may be much to celebrate in terms of educational equity in Canada relative to many other international jurisdictions, educational inequities do indeed exist in Canada and these are associated with economic disadvantages. PISA results, and other measures of achievement throughout the country do highlight a relatively high level of within-school variation in Canada (e.g., Organisation for Economic Co-operation and Development, 2016b). These findings demonstrate that in spite of the high level of overall equity in terms of schooling, substantial portions of the student population do not equally benefit from such educational opportunities.

These inequities can be found amongst the provinces, between communities, and within schools, and in each instance, a fundamental difference appears to be associated with socioeconomic factors. Achievement differences due to income inequality have been identified in preschool and elementary children and evidence strongly suggests these early “achievement gaps” either remain stable or increase throughout, which contributes to differences in academic achievement in later years (Burton et al., 2013; Caro, McDonald, & Willms, 2009; Cleveland & Krashinsky, 2003; Finnie, Childs, & Wismer, 2011).

10.2 Provincial Jurisdiction of Education and the National Achievement Gap

In Canada, education is regulated by each province and territory, which in turn each develops its own curricula. As a result, there are some structural differences amongst the provinces (e.g., Klinger & Saab, 2012). Children begin formal schooling in Kindergarten in the year they turn 5. Ontario offers Junior and Senior Kindergarten. Students enter Grade 1 and continue their schooling until Grade 12 in all of the provinces except Quebec, where Grade 12 is replaced by the first year of the CEGEP (Collège dʼenseignement général et professionnel, and in English, College of General and Vocational Education). Schooling is typically divided into elementary and secondary components, although the grade at which the transition is made varies across provinces and many provinces further subdivide these two categories (e.g., primary and junior elementary, middle schools, junior and senior secondary). This transition typically occurs between Grades 7 and 9. The transition from primary to secondary is coupled with the shift from a single teacher to multiple subject area teachers. The vast majority of students attend publicly funded schools across Canada. These schools are non-sectarian, although Alberta, Saskatchewan, and Ontario provide full provincial funding for their religious-based Separate (most often Catholic) school systems. The secondary school graduation rate in Canada was 87% in 2015, slightly higher than the OECD average of 86% (Statistics Canada, 2017c).

While public schooling is free to all children, approximately 6% of children attend private schools in Canada, in which a portion or all of the student fees are paid for by the family (Frenette & Chan, 2015). These proportions vary by province, with the highest numbers attending private schools in Quebec, and much lower proportions in Alberta and Ontario, most likely due to the funding differences for Catholic education. While 94% of Canada’s children receive free public education until the completion of secondary school, postsecondary education, while indirectly subsidized by provincial governments, is not free to attend. In spite of the presence of tuition fees, Canadians report a high level of postsecondary education. The proportion of adults in Canada between the ages of 25 and 64 with postsecondary education is 57%, with 28.5% having a Bachelor’s degree or more, which is the highest among OECD countries (Statistics Canada, 2017c).

Nevertheless, these proportions vary by province, and these variations correlate with differences in educational measures. As an example, Table 10.1 illustrates the relationship between levels of education of adults and the PISA results of 15-year-olds for 2015. Acknowledging the error of measurement for the PISA 2015 scores varies by each province due to large differences in provincial sample sizes, and noting that the 2015 assessment had a primary focus on Science, these data illustrate positive correlations amongst the percentage of the provincial adult population (aged 25–64) where 0.55 was with Mathematics (1-tailed p <  0.05), 0.72 with Reading (p <  0.01), and 0.67 with Science (p <  0.05). The correlations were found to be slightly smaller for the percentage of the female adult population at 0.52 with Mathematics (p < 0.05), 0.71 with Reading (p <  0.01), and 0.65 with Science (p < 0.05). In contrast, correlations with other measures of provincial wealth such as median income and per capita GDP have insignificant correlations below 0.30 with PISA results.
Table 10.1

Provincial-level PISA results and % of population with Bachelor’s degree or more


Pisa math


Pisa reading


PISA science


% of adults with bachelor’s degree or more

% of females with bachelor’s degree or more

British Columbia




































New Brunswick






Nova Scotia






Prince Edward Is.


















Note Census data obtained from Statistics Canada (2017a, 2017b, 2017c, 2017d); Canadian PISA data obtained from O’Grady et al. (2016)

As noted previously, Canada has shown a relatively high level of educational equity. How does this compare to measures of economic inequity? The Gini coefficient is a measure of inequality of income distribution or inequality of wealth distribution. It is defined as a ratio with values between 0 and 1, in which 0 equates to every individual in a society having the same income, and 1 representing complete inequality (Organisation for Economic Co-operation and Development, 2006). Based on most recently available statistics, Canada has an after-tax Gini Coefficient of 0.306 (Statistics Canada, 2018a). Canada ranks 7 out of 17 peer countries for income equality (Organisation for Economic Co-operation and Development, 2018b). Breau (2015) found that income inequality between Canadian provinces was highly variable because of differing policy contexts, labor regulations, and taxation policies. Across all Canadian provinces, the highest income inequality was found in Newfoundland and Labrador, Alberta, Ontario, and British Columbia (Breau, 2015). Interestingly, the correlations amongst the Gini coefficient and the PISA results were lower and insignificant in comparison to the associations found for education levels of adults in each province. This may be partially explained by the relatively similar Gini coefficients found across the provinces, varying between 0.27 and 0.32. Thus, it appears that in Canada, broad measures of inequality are less predictive of children’s educational outcomes than measures related to adults (parents) and families and that measures related to education levels are the most predictive of educational outcomes. Who are these parents and families? And what are the barriers they face or the decisions they are making that may lead to the relatively high levels of observed within school variability in educational outcomes?

10.3 Between- and Within-School Variation

One of the challenges of large data sets is that they can often mask small but systematic differences. As an example, the Canadian PISA results have noted that the between-school variation in PISA results is small in Canada. Nevertheless, these same data have shown that 15-year-old students attending private schools attain higher PISA scores than their peers attending publicly funded schools, scoring 8–9% higher (Frenette & Chan, 2015). These are substantial differences (over 40 points) but the small proportion of children in private schools, and in the PISA sample, masks this substantial between-school effect. Interestingly, this observed inequity occurs along with a similar socioeconomic predictor. Specifically, the families of children in private schools have higher average incomes and are much more likely to have completed university education.

These same private school data provide an insight into the higher levels of observed within-school variation in educational outcomes found in Canada. Private schools tend to reflect relatively homogeneous populations in terms of social capital. In contrast, Canada’s public schools are much more heterogeneous given that 94% of children attend public schools. Thus, public schools across the country largely reflect the population of the country. Overall, the Canadian population is varied, certainly in terms of culture, as expected given the high rates of immigration in Canada, but also, and of relevance to our work here, in the dispersion of social and economic capital.

Which brings us back to the question of who are the parents and families who face economic disadvantages that may impact their children’s educational achievement and school engagement? According to the most recent Canadian census, 4.8 million Canadians live in poverty and 1.2 million Canadians under the age of 18 live in low-income households (Statistics Canada, 2017a). While Canada has no official definition of poverty, Statistics Canada defines low-income cut-offs (LICO) as income thresholds below which a family will likely devote 20 percentage points more of its income on the necessities of shelter, food, and clothing than the average family (Lightman & Gingrich, 2013; Satzewich & Liodakis, 2013). Hence Statistics Canada’s LICO figures serve as a proxy for poverty in Canada.

Three subgroups of the Canadian population appear to represent the greatest proportions of those falling below LICO thresholds. As found in other international jurisdictions, single-parental households are a strong predictor of socioeconomic inequality in Canada. The 19% of Canadian children living in a lone‑parent household are more than three times as likely to live in a low‑income household as children living in a two‑parent household (Statistics Canada, 2017a). In what has been termed the “feminization of poverty,” scholars have further noted that women face greater risks of poverty because of the male–female wage gap (Kwok & Wallis, 2008). Currently, there remains a gender pay gap between males and females in the Canadian labor market. Recent estimates are that women earn 74 cents for every dollar earned by a male (Statistics Canada, 2017c). Most of the variance in wages can be attributed to occupational sex segregation, since women tend to occupy lower paying, part-time, temporary positions more often than do males (Kwok & Wallis, 2008). In 2015, 18.9% of Canadian women were working part-time versus 5.5% of Canadian men (Statistics Canada, 2018b).

Approximately 21% of the Canadian population was born outside Canada (Statistics Canada, 2017b) and the visible minority population constitutes 22.3% of the total Canadian population. The majority of immigrants arrive as skilled immigrants through the federally regulated points system for immigration which allocates “points” for education, skills, language ability, and training. Despite this, many recent immigrants face barriers as they endeavor to enter the labor market due to official language fluency, foreign credential devaluation, and discrimination (Esses & Bhardwaj, 2006; Galabuzi, 2006; Lightman & Gingrich, 2013; Oreopoulos, 2011; Reitz, 2016). As a result, recent immigrants to Canada are also more likely to experience low SES (Picot & Hou, 2014).

Lastly, the Statistics Canada (2017b) census report indicated that the Indigenous population was 1,673,785 or 4.9% of the total Canadian population. Indigenous families living on reserves have the lowest standard of living in Canada (Statistics Canada, 2011, 2013). Current reserves in Canada have poor living conditions and many Indigenous families have low SES (Statistics Canada, 2013). Forty percent of off-reserve Indigenous persons live in poverty. A substantial proportion of Canada’s Indigenous population resides in “at-risk” communities. According to the 2011 National Household survey, only 9.8% of Indigenous persons held a university degree in contrast to the Canadian average of 27% and 36% had not completed high school (Statistics Canada, 2013). Statistics indicate that there is a large gap between Indigenous and non-Indigenous persons for all levels of education. The 2016 Canadian census indicated that 28.5% of Canadians between the ages of 25 and 64 had a Bachelor’s degree or higher, while only 10.9% of Indigenous persons between the ages of 25 and 64 had a Bachelor’s degree or higher (Statistics Canada, 2017d). Indigenous persons living on reserves have lower educational attainment than those living off-reserves (Statistics Canada, 2017d).

Added to these three predominant groups facing economic disadvantages, other sub-populations, while smaller in number, have also been shown to face economic challenges at a much greater rate than the “averageˮ Canadian family. As an example, and consistent with U.S. findings, Black Canadians, especially those from low-income communities, have lower rates of high school completion and university degree attainment (Abada, Hou, & Ram, 2009; Caldas, Bernier, & Marceau, 2009; Dei, 2008; James & Turner, 2017; Livingstone & Weinfeld, 2017). Similar disadvantages are found for adults with disabilities.

10.4 Low SES and Childhood Educational Outcomes

Evidence shows that Canadian children from lower socioeconomic backgrounds tend to have higher secondary school drop-out rates, lower academic achievement at all levels of schooling, and more emotional and behavioral problems in school (Belley, Frenette, & Lochner, 2014; Evans, 2004; Ferguson, Bovaird, & Mueller, 2007; Portnow & Hussain, 2016; Shaker, 2014). In Canada, some of the evidence to support these claims comes from longitudinal studies. An analysis of the most recent cycle from Statistics Canada’s National Longitudinal Study of Children and Youth (19942008) showed that children from affluent socioeconomic backgrounds score better academically on the CAT/2 standardized math test than children from economically disadvantaged backgrounds (Burton et al., 2013). The researchers noted that over 50% of children from low-income Canadian households had below-average math scores whereas 33% of children from high-income households scored below-average (Burton et al., 2013). Caro et al. (2009) used the same national data set to show that the academic achievement gap between low and high SES students was stable from ages 7 through 11, but widened between the ages of 11–15. They concluded that the advantages of high SES constitute a cumulative advantage that widens the gap over time (Caro et al., 2009).

As further evidence, Roos et al. (2006) conducted a longitudinal study using data from the Population Health Research Data Repository located in the province of Manitoba. The researchers studied all children born in the province in 1984 using 18 years of data that included standardized test results. They found that the standard examination pass rates of those students living in the poorest neighborhoods were less than half that of those living in the wealthiest neighborhoods (Roos et al., 2006). Similar results have been found across provincial testing programs in British Columbia and Ontario, in which associated demographic data are available. As one example, in Ontario, students from families earning less than $30,000 per year score 20–30% lower on the Grade 3 math and literacy tests than families who earn more than $100,000 per year (Education Quality and Accountability Office, 2017).

The previously discussed sub-populations of single parent, immigrant, and Indigenous families provide further insights into these relationships and some of the ongoing challenges and opportunities to address the impact of these inequities. In a cross-national study of PISA scores among 17 countries, Garriga and Martínez-Lucena (2018) found that growing up in a single-parent household had a negative effect on academic achievement in most developed countries. Research findings indicated that Canadian children who grow up in single-parent households are more likely to have academic, behavioral, and psychological problems (Ward & Belanger, 2010). The proportions of single-parent families vary across provinces and perhaps surprisingly, these proportions are moderately correlated with provincial PISA results, −0.58 with mathematics (p <  0.05), −0.65 with science (p < 0.05), and −0.70 with reading. These values are comparable to the correlations found between PISA results and the proportion of adults with a Bachelor’s degree or more. The 0.68 correlation between single-parent households and adult education levels (0.65 for education levels of females) suggest a substantial level of shared variance.

While PISA results are not subdivided based on indigeneity, data from provincial assessment systems highlight the association of these socioeconomic and educational data with Indigenous children’s educational achievement. For example, 2016–2017 data from the Foundation Skills Assessment (FSA) in British Columbia indicated that 35% of Aboriginal students failed to meet provincial standards for fourth-grade reading comprehension. For non-Aboriginals the percentage was 18% (British Columbia Ministry of Education, 2017). For numeracy, the percentage of Aboriginal test takers not meeting provincial standards was 45% compared to 23% for non-Aboriginal students (British Columbia Ministry of Education, 2017). While not all provinces obtain Aboriginal/Indigenous status from students in relation to their provincial testing programs, those that do highlight similar achievement gaps (e.g., Ontario, Quebec).

Educational achievement gaps between Indigenous and non-Indigenous peoples are recognized as a critical issue and a policy challenge in the Canadian context. Indigenous children and their families continue to face barriers to achievement at all levels, including access to postsecondary education. While measures highlighting economic disadvantages may be associated with the observed achievement gaps, they also hide much deeper issues that need to be addressed to resolve ongoing inequities and societal challenges. For example, funding for federally run schools for Indigenous communities is less than provincially funded schools, even when factoring in higher Northern or remote operating costs (Blatchford, 2016; Statistics Canada, 2013). Historical oppressions arising from colonialism have contributed to intergenerational poverty among Canada’s Indigenous peoples. The reserve system in the 1800s, followed by the system of forced residential schooling that separated children from their families—the “Sixties Scoop” of forced adoptions—and other injustices have resulted in intergenerational trauma. This history of intergenerational trauma related to residential schooling has contributed to perceptions of “not fitting in” within schools (Blue & Pinto, 2017; Cassidy, 2015; Guinan, 2016). These findings suggest that children from Indigenous families may experience a double disadvantage, due to economic inequity and historical injustices that continue to reverberate. Given this, efforts to reduce ongoing inequities and support Indigenous learning will require substantial effort. As an example, some scholars have argued for a curriculum that embeds content based on Indigenous cultures, perspectives, and histories. This would better serve Indigenous students and foster respect for cultural diversity among non-Indigenous students (Milne, 2016). Timmons (2013) and Restoule et al. (2013) suggest that Indigenous students require comprehensive cultural supports in order to succeed in non-Indigenous postsecondary institutions.

In contrast to the aforementioned findings for single parent and Indigenous families, the academic achievement of the children of Canadian immigrants is higher than would be predicted by SES, although it varies greatly by ethnicity (Abada et al., 2009; Clandfield et al., 2014; Glick & Hohmann-Marriott, 2007). Klinger et al. (2018) noted that internationally, “with rare exceptions, immigrant students have lower levels of academic achievement than their non-immigrant peers” (p. 199). An examination of Canada’s PISA results indicates that both first- and second-generation students in Canada have similar results as their Canadian-born counterparts, but there are provincial variations (Klinger et al., 2018). Abada et al. (2009) found that most Asian immigrant children performed as well or better than their Canadian counterparts on measures of academic achievement. The children of Filipino and Black immigrants performed less well, as did some European immigrant groups such as the Portuguese (Abada et al., 2009).

Given the large intake of immigrants to Canada, the federal government has implemented a series of policy initiatives to support immigrant families. The point system used to attract highly skilled workers has attracted immigrants with high levels of education. While these families may not be able to attain economic parity based on their training, it is not surprising that immigrant children have high postsecondary participation given the strength of parental education as a predictor of children’s educational attainment (Childs, Finnie, & Martinello, 2017). The majority of skilled immigrants to Canada in the past decade have come from Asian and South Asian countries. Hence the point system may also serve to attract skilled immigrants who value further education for their children.

Educational policies in Canada have also been implemented to support immigrant children. As Volante et al. (2017) assert, educational policies in Canada facilitate the integration of immigrant students by focusing on language, cultural development, and inclusion, which provides additional supports to ameliorate potential educational disadvantages, at least for a sector of the immigrant families who come to Canada. Similar policies are now being implemented to support the children of refugees, along with targeted resources to address the trauma refugee families and children often face.

10.5 Cultural Capital, SES, and Access to Postsecondary Education

In Canada, recent provincial policy initiatives have focused on the provision of financial support for low-income students to access postsecondary education (Policy Horizons Canada, 2017). This includes specific efforts (e.g., scholarships) to attract “first-generation” students who come from families with no history of postsecondary education. Nevertheless, postsecondary participation rates for low-income youths from “at-risk” communities have not risen significantly in spite of these increased financial aid options (Cassidy, 2015; Higher Education Quality Council of Ontario, 2017; Oreopoulos, Brown, & Lavecchia, 2017).

The Canadian research on barriers to postsecondary access for students from low-income families has focused primarily on financial barriers (Belley et al., 2014; Frempong, Ma, & Mensah, 2012; Imbeau, 2017; Jones, 2014; King, Warren, King, Brook, & Kocher, 2009). For low-income Canadian students, community college and apprenticeship programs appear to be promising and lower cost, but data from the most recently available Youth in Transition Survey (YITS) in 2009 showed that 25% of low-income students dropped out of community college and roughly 40% of students failed to complete vocational apprenticeship training programs (Shaker, 2014). Davies, Maldonado, and Zarifa (2014) reported that in spite of the fact that Canadian postsecondary participation rates are rising, the percentage of students who attend from low SES backgrounds has not risen. Berger, Motte, and Parkin (2009) found that only one-quarter of low-income 19-year-old Canadians enrolled in university while 46% of high-income 19-year-olds enrolled in university. Davies et al. (2014) also found that affluent youths sought to maintain their social class status through postsecondary selection, favoring more prestigious institutions.

Ability grouping or what is more commonly known as academic streaming is another barrier for certain low-income populations deemed “at-risk.” Most secondary school systems in Canadian provinces offer high school credit courses that are streamed into “general” (or “applied”) and “advanced” levels. The advanced level credit courses are required in order to gain entry to most 4-year university programs that offer Bachelor’s degrees or higher. Students from low SES are twice as likely to be streamed into “general” or “applied level” courses (Clandfield et al., 2014; James & Turner, 2017; King et al., 2009; Lyon, Frohard-Dourlent, Fripp, & Guppy, 2014). Educational sociologists argue that teachers may have lower academic expectations for students enrolled in applied or general academic streams and that students form peer relationships within their academic streams (Parekh, Killoran, & Crawford, 2011).

Curricular differentiation through tracking creates unequal learning experiences in similar topic areas. In some instances, the content is designed for the vocational workplace context. Theoretical content is not included that would adequately prepare students for postsecondary content. Schmidt et al. (2015) studied tracking internationally, and although tracking and curricular differentiation vary between contexts, they found that tracking perpetuates socioeconomic inequality. Similar findings were published by Chmielewski (2014), who studied the effects of course-by-course tracking and SES by examining PISA scores. The author concluded that this had the effect of segregating students by SES and recommended that more empirical research be conducted in the area of international course-by-course tracking (Chmielewski, 2014).

The most recently available provincial data tables on streaming were published by Krahn and Taylor (2007) who used information from cycle 1 of Statistics Canada’s YITS. They compared streaming by ability in Ontario, Saskatchewan, Alberta, and British Columbia. The results showed a strong parental education effect. Fifteen-year-old youths who were enrolled in courses that would leave their postsecondary options open were two and half times more likely to do so if they had at least one university-educated parent. The existing research shows a strong effect of parental transmission. One explanation provided by researchers is that parents are able to transmit cultural capital to their children. Cultural capital theory refers to the accumulation of cultural knowledge that confers privilege and facilitates social mobility in a particular society (Bourdieu, 1976, 1984; Bourdieu & Passeron, 1977). Recent Canadian research has begun to examine cultural barriers (Cassidy, 2015; Childs et al., 2017; Childs, Finnie, & Mueller, 2018; Finnie, 2012; Finnie et al., 2011; Guinan, 2016).

Perna (2006) found that parents transmit cultural capital to their children that strongly influences their postsecondary decision-making. Utilizing quantitative YITS data, recent Canadian studies have identified parental educational attainment as the most important predictor of postsecondary participation for youths (Childs et al., 2017, 2018; Finnie et al., 2011). Certain forms of cultural capital such as books, attending cultural events, and other educational resources facilitated postsecondary participation among youths. Indirect benefits were high parental expectations to pursue postsecondary education and its related socialization. Finnie (2012) has argued that youths must develop a “culture of postsecondary education” that begins in early adolescence in order to increase the probability that they will attend later on. The results of the YITS showed that 40% of students who attended university reported that they had “always known” they would attend (Childs et al., 2018; Finnie, 2012). The high postsecondary participation rates of certain Canadian immigrant groups like the Chinese, Japanese, and South Asians have been attributed to parental cultural expectations that place high value on postsecondary participation (Abada et al., 2009; Cox & Strange, 2016; Klinger et al., 2018).

10.6 Evidence-Based Solutions to Reduce the Socioeconomic Achievement Gap in the Canadian Context

Decades of studies have explored the academic achievement gap between different social classes. SES differences in educational achievement remain persistent. Systemic efforts to improve outcomes for children from low SES backgrounds must be comprehensive and sustainable. Researchers have attributed some of these disparities to a combination of structural and social factors which have a cumulative effect on child academic and life outcomes. These factors include a multiplicity of overlapping socioeconomic factors such as nutrition, housing, parenting styles, household stress, the environment, and family structure (Fagan, 2017; Keeley, 2015; Thomson, Guhn, Richardson, Ark, & Shoveller, 2017). As an example, PISA scores show that 15-year-old students whose parents often read books with them during their first year of primary school show markedly higher PISA scores than students whose parents read with them infrequently or not at all (Organisation for Economic Co-operation and Development, 2017). The challenge for low SES parents is that they may have irregular working hours and lack the time to devote to such tasks or may lack basic literacy skills themselves. This is one of the reasons why effective interventions must include the family.

Successful evidence-based interventions focus on addressing the structural and individual level challenges faced by low-income students and their families. Many evidence-based interventions emphasize the importance of the early years to support school readiness. Early years intervention programs are offered in most OECD countries (Fillis, Dunne, & McConnell, 2018; van Huizen & Plantenga, 2018). Canada is one of 36 member countries in the OECD. Unlike many European countries such as Sweden, Denmark, Iceland, Norway, or Finland, Canada does not have universal access to high-quality preschool programs in all provinces (Organisation for Economic Co-operation and Development, 2016a). As a result, many families cannot afford to access early childhood education and care during critical periods of child development. Some researchers have linked international performance on the PISA and TIMSS to countries that have made the largest investments in early learning relative to their GDP (Merry, 2013; White, Prentice, & Perlman, 2015).

Fillis et al. (2018) conducted a systematic review of early intervention programs in Canada and the United States for 2- to 3-year olds. The intervention programs studied provided a combination of family support, cognitive and emotional development, and holistic development. The researchers failed to provide empirical evidence to support the idea that there are effective interventions for young children aged 24–36 months. Similarly, a meta-analysis of 30 studies published by van Huizen and Plantenga (2018) found mixed results for early childhood intervention programs, although they suggested that intensive, high-quality programs offered the strongest evidence for long-term positive effects.

According to Canadian economists Cleveland and Krashinsky (2003) in their report entitled Fact and Fantasy: Eight Myths About Early Childhood Education and Care, early childhood education is a key factor in reducing overall poverty rates. The researchers have determined in many studies that the social and economic benefits of a publicly financed system for early childhood education and care (ECEC) for children between the ages of 2 and 5 exceed the costs by a margin of 2:1 (Cleveland & Krashinsky, 2005). One early intervention program that has gained global prominence is Head Start, which was introduced in the United States in 1965 to target low-income, urban children. The design of the program includes cognitive, nutritional, medical, and parental support (Deming, 2009; Koehler, 2012). The United States evidence indicated that the gains for disadvantaged groups are short-term and diminish upon entering adolescence (Koehler, 2012). Nevertheless, the program has proven to have long-term effectiveness in other contexts. In Canada, the federal government invested over $170 million to introduce Aboriginal Head Start programs in Canada in 1995 and the program still exists (Health Canada & Public Health Agency of Canada, 2017).

A recent systematic program evaluation of 2000 3- to 5-year-old Aboriginal Head Start participants found statistically significant improvements in language, motor skills, and academic skills (Health Canada & Public Health Agency of Canada, 2017). A longitudinal study by Laurin et al. (2015) found that children from low socioeconomic backgrounds who received high-intensity early learning at a daycare center had significantly higher reading and mathematics scores by age 12 than those children who did not receive high-intensity early learning and care. The researchers defined high-intensity as 35 or more hours per week at a quality child care center. While the research evidence for the effectiveness of early childhood education is mixed, the research does support the fact that early interventions may be of most benefit to those with a low SES.

National and provincial educational policies are needed to ensure that students succeed regardless of their SES. According to the Organisation for Economic Co-operation and Development (2017), “A student is classified as resilient if he or she is in the bottom quarter of the PISA index of economic, social and cultural status (ESCS) in the country or economy of assessment and performs in the top quarter of students among all countries and economies, after accounting for socio-economic status” (p. 47). In Canada, about one-third of 2015 PISA test takers from low SES backgrounds were considered resilient (Organisation for Economic Co-operation and Development, 2017). In many countries, resilient students account for about 40% of the low-income student population. The factors that support resilience in schooling have been found to correlate with teacher quality, opportunities for extra/tutorial support for both subject matter and language, disciplined learning environments, parenting support, and the provision of resource support—such as food, clothing, or financial aid (Organisation for Economic Co-operation and Development, 2017).

Teacher quality is another factor that has been shown to improve outcomes for low-income children. Many OECD countries with high rankings on international assessments have very selective criteria for the admission of teacher candidates and offer decent compensation (Tuovinen, 2008). Campbell (2017) has argued that teacher development in Canada has contributed to relatively high PISA scores and that teacher quality and professional learning will be critical for supporting low SES children in the future. Liebenberg et al. (2016) studied 1068 Canadian youths living in marginalized communities and found that a positive student–teacher relationship had a direct moderating effect on risk factors. The authors noted that for many low socioeconomic youths, school may be the only source of formal social support. Similarly, Ingvarson and Rowley (2017) compared the processes for teacher recruitment and selection in 17 countries and concluded that those countries with policies that ensured teacher quality had students with higher scores on international tests of mathematics achievement.

Many of the most successful intervention programs aimed at increasing the participation of low-income students in postsecondary education provide extensive cultural supports in addition to financial aid (Hoxby & Turner, 2013; Oreopoulos et al., 2017; Pathways to Education, 2017). Dei (2008) and Ladson-Billings (2014) argue that educational institutions should strive to affirm the cultural identities of all students. Latif’s (2017) Canadian study of educational mobility found that public spending on education helped to foster intergenerational social mobility. Strong public financing of education at all levels from preschool to postsecondary with comprehensive supports for low-income children and youths will help to reduce the probability that SES in Canada determines one’s academic achievement.

Overall, the Canadian achievement results and research suggest that access to postsecondary education may be a defining predictor and issue to address ongoing educational challenges associated with economic disparity. Admittedly, the broader Indigenous issues and challenges described previously, coupled with the lack of success of many of the current initiatives to increase participation rates do suggest caution against adopting simplistic efforts to increase access to postsecondary education. The previous policy options and interventions discussed suggest that Canada is attempting to address the structural and sociocultural factors that contribute to socioeconomic achievement gaps. Admittedly, the progress is less than stellar and will require the ongoing commitment of the national and provincial governments.


  1. Abada, T., Hou, F., & Ram, B. (2009). Ethnic differences in educational attainment among the children of Canadian immigrants. Canadian Journal of Sociology, 34(1), 1–28. Retrieved from
  2. Ainsworth, J. (2002). Why does it take a village? The mediation of neighborhood effects on educational achievement. Social Forces, 81(1), 117–152. Scholar
  3. Belley, P., Frenette, M., & Lochner, L. (2014). Post‐secondary attendance by parental income in the U.S. and Canada: Do financial aid policies explain the differences? Canadian Journal of Economics/Revue canadienne d’économique, 47(2), 664–696. Scholar
  4. Berger, J., Motte, A., & Parkin, A. (2009). The price of knowledge: Access and student finance in Canada (4th ed.). Montreal, QC: Canada Millennium Scholarship Foundation.Google Scholar
  5. Blatchford, A. (2016, December 6). Report by Parliamentʼs budget office finds on-reserve schools underfunded by thousands of dollars per student. CBC News. Retrieved from
  6. Blue, L. E., & Pinto, L. E. (2017). Other ways of being: Challenging dominant financial literacy discourses in Aboriginal context. Australian Educational Researcher, 44(1), 55–70. Scholar
  7. Bourdieu, P. (1976). Systems of education and systems of thought. In R. Dale, G. Esland, & M. MacDonald (Eds.), Schooling and capitalism: A sociological reader (pp. 192–200). London, UK: Routledge.Google Scholar
  8. Bourdieu, P. (1984). Distinction: A social critique of the judgement of taste (R. Nice, Trans.). Cambridge, MA: Harvard University Press.Google Scholar
  9. Bourdieu, P., & Passeron, J. (1977). Reproduction in education, society and culture. London, UK: Sage.Google Scholar
  10. Breau, S. (2015). Rising inequality in Canada: A regional perspective. Applied Geography, 61, 58–69. Scholar
  11. British Columbia Ministry of Education. (2017). Aboriginal report 2012/13–2016/17: How are we doing? Retrieved from
  12. Burton, P., Phipps, S., & Zhang, L. (2013). From parent to child: Emerging inequality in outcomes for children in Canada and the U.S. Child Indicators Research, 6(2), 363–400. Scholar
  13. Caldas, S. J., Bernier, S., & Marceau, R. (2009). Explanatory factors of the Black achievement gap in Montréalʼs public and private schools: A multivariate analysis. Education and Urban Society, 41(2), 197–215. Scholar
  14. Campbell, C. (2017). Developing teachers’ professional learning: Canadian evidence and experiences in a world of educational improvement. Canadian Journal of Education, 40(2), 1–33. Retrieved from
  15. Caro, D. H., McDonald, J. T., & Willms, J. D. (2009). Socio-economic status and academic achievement trajectories from childhood to adolescence. Canadian Journal of Education/Revue canadienne de lʼéducation, 32(3), 558–590.Google Scholar
  16. Cassidy, K. (2015). Barriers to post-secondary education: Perspectives from Niagara (NCO Policy Brief #22). St. Catharines, ON: Brock University. Retrieved from
  17. Cheng, L., & Yan, W. (2018). Immigrant student achievement and education policy in Canada. In L. Volante, D. Klinger, & Ö. Bilgili (Eds.), Immigrant student achievement and education policy: Cross-cultural approaches (pp. 137–153). Dordrecht, Netherlands: Springer.CrossRefGoogle Scholar
  18. Childs, S. E., Finnie, R., & Martinello, F. (2017). Postsecondary student persistence and pathways: Evidence from the YITS-A in Canada. Research in Higher Education, 58(3), 270–294. Scholar
  19. Childs, S., Finnie, R., & Mueller, R. E. (2018). Assessing the importance of cultural capital on post-secondary education attendance in Canada. Journal of Further and Higher Education, 42(1), 35–57. Scholar
  20. Chmielewski, A. K. (2014). An international comparison of achievement inequality in within- and between-school tracking systems. American Journal of Education, 120(3), 293–324. Scholar
  21. Chu, M. (2017, September 11). Why Canada fails to be an education superpower. The Conversation. Retrieved from
  22. Clandfield, D., Curtis, B., Galabuzi, G.-E., San Vicente, A. G., Livingstone, D. W., & Smaller, H. (2014, Winter). Restacking the deck: Streaming by class, race and gender in Ontario schools [Special issue]. Our Schools/Our Selves. Retrieved from
  23. Cleveland, G., & Krashinsky, M. (2003). Fact and fantasy: Eight myths about early childhood education and care. Toronto, ON: Childcare Resource and Research Unit.Google Scholar
  24. Cleveland, G., & Krashinsky, M. (2005). Financing early learning and care in Canada. Ottawa, ON: Canadian Council for Social Development. Retrieved from
  25. Coughlan, S. (2017, August 2). How Canada became an education superpower. BBC News. Retrieved from
  26. Council of Ministers of Education, Canada. (2018). Quality education for all: Canadian report for the UNESCO Ninth Consultation of Member States on the Implementation of the Convention and Recommendation Against Discrimination in Education. Retrieved from
  27. Cox, D. G. H., & Strange, C. C. (2016). Serving diverse students in Canadian higher education. Kingston, ON: McGill-Queen’s University Press.Google Scholar
  28. Davies, S., Maldonado, V., & Zarifa, D. (2014). Effectively maintaining inequality in Toronto: Predicting student destinations in Ontario universities. Canadian Review of Sociology/Revue canadienne de sociologie, 51(1), 22–53. Scholar
  29. Dei, G. S. (2008). Schooling as community: Race, schooling, and the education of African youth. Journal of Black Studies, 38(3), 346–366. Scholar
  30. Deming, D. (2009). Early childhood intervention and life-cycle skill development: Evidence from Head Start. American Economic Journal: Applied Economics, 1(3), 111–134. Retrieved from Scholar
  31. Education Quality and Accountability Office. (2017). Provincial assessment results. Retrieved from
  32. Esses, V., & Bhardwaj, A. (2006). The role of prejudice in the discounting of immigrant skills. In R. Mahalingam (Ed.), Cultural psychology of immigrants (pp. 114–127). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  33. Evans, G. W. (2004). The environment of childhood poverty. American Psychologist, 59(2), 77–92. Scholar
  34. Fagan, J. (2017). Income and cognitive stimulation as moderators of the association between family structure and preschoolers’ emerging literacy and math. Journal of Family Issues, 38(17), 2400–2424. Scholar
  35. Ferguson, H., Bovaird, S., & Mueller, M. (2007). The impact of poverty on educational outcomes for children. Paediatrics & Child Health, 12(8), 701–706.CrossRefGoogle Scholar
  36. Fillis, S., Dunne, L., & McConnell, B. (2018). Empirical studies on early intervention services for toddlers aged 24–36 months: A systematic review. International Journal of Educational Research, 89, 119–138. Scholar
  37. Finnie, R. (2012). Access to post-secondary education: The importance of culture. Children and Youth Services Review, 34(6), 1161–1170. Scholar
  38. Finnie, R., Childs, S., & Wismer, A. (2011). Access to post-secondary education among under-represented and minority groups: Measuring the gaps, assessing the causes (Working Paper No. 2011-2001). Ottawa, ON: Education Policy Research Initiative.Google Scholar
  39. Frempong, G., Ma, X., & Mensah, J. (2012). Access to postsecondary education: Can schools compensate for socioeconomic disadvantage? Higher Education, 63(1), 19–32. Scholar
  40. Frenette, M., & Chan, P. C. W. (2015, March 31). Why are academic prospects brighter for private high school students? Economic Insights (Statistics Canada catalogue no. 11-626-X-No. 044). Retrieved from
  41. Galabuzi, G. (2006). Canada’s economic apartheid: The social exclusion of racialized groups in the new century. Toronto, ON: Canadian Scholars’ Press.Google Scholar
  42. Garriga, A., & Martínez-Lucena, J. (2018). Growing up in a single mother family and studentʼs tardiness: A cross-national study exploring the moderating role of family resources. Journal of Divorce & Remarriage, 59(1), 1–24. Scholar
  43. Glick, J., & Hohmann-Marriott, B. (2007). Academic performance of young children in immigrant families: The significance of race, ethnicity, and national origins. The International Migration Review, 41(2), 371–402. Scholar
  44. Guinan, D. (2016). The social environment and Indigenous student success in a Canadian post-secondary institution (Doctoral dissertation). Royal Roads University, Victoria, British Columbia. Retrieved from
  45. Health Canada & Public Health Agency of Canada. (2017). Evaluation of the aboriginal head start in urban and northern communities program 2011–2012 to 2015–2016. Ottawa, ON: Author.Google Scholar
  46. Higher Education Quality Council of Ontario. (2017). Quick stats. Retrieved from
  47. Hoxby, C., & Turner, S. (2013, Fall). Expanding college opportunities. Education Next, 13(4). Retrieved from
  48. Imbeau, E. (2017). Saving for post-secondary education: Findings from the Canadian financial capability survey: Technical study prepared for the Canada education savings program summative evaluation. Gatineau, QC: Employment and Social Development Canada. Retrieved from
  49. Ingvarson, L., & Rowley, G. (2017). Quality assurance in teacher education and outcomes: A study of 17 countries. Educational Researcher, 46(4), 177–193. Scholar
  50. James, C. E., & Turner, T. (2017). Towards race equity education: The schooling of Black students in the Greater Toronto Area. Toronto, ON: York University. Retrieved from
  51. Jones, G. A. (2014). Building and strengthening policy research capacity: Key issues in Canadian higher education. Studies in Higher Education, 39(8), 1332–1342. Scholar
  52. Keeley, B. (2015). Income inequality: The gap between rich and poor Paris. France: OECD Publishing. Scholar
  53. King, A. J. C., Warren, W. K., King, M. A., Brook, J. E., & Kocher, P. R. (2009). Who doesn’t go to post-secondary education? Final report of findings for Colleges Ontario Collaborative Research Project. Toronto, ON: Colleges Ontario. Retrieved from
  54. Klinger, D. A., & Saab, H. (2012). Educational leadership in the context of low-stakes accountability: The Canadian perspective. In L. Volante (Ed.), School leadership in the context of standards-based reform: International perspectives (pp. 73–96). Dordrecht, Netherlands: Springer.Google Scholar
  55. Klinger, D. A., Volante, L., & Bilgili, Ö. (2018). Cross-cultural approaches to mitigating the immigrant student performance disadvantage. In L. Volante, D. A. Klinger, & O. Bilgili (Eds.), Immigrant student achievement and education policy: Cross-cultural approaches (pp. 197–206). Dordrecht, Netherlands: Springer.CrossRefGoogle Scholar
  56. Koehler, C. (2012). Effects of the Head Start program in the USA as indicators of ethnic inequalities. In Z. Bekerman & T. Geisen (Eds.), International handbook of migration, minorities and education (pp. 383–401). Dordrecht, Netherlands: Springer.CrossRefGoogle Scholar
  57. Krahn, H., & Taylor, A. (2007). “Streaming” in the 10th grade in four Canadian provinces in 2000. Education Matters, 4(2), 16–26. Retrieved from
  58. Kwok, S., & Wallis, M. A. (2008). Daily struggles: The deepening racialization and feminization of poverty in Canada. Toronto, ON: Canadian Scholars’ Press.Google Scholar
  59. Ladson-Billings, G. (2014). Culturally relevant pedagogy 2.0: a.k.a. the Remix. Harvard Educational Review, 84(1), 74–84. Scholar
  60. Latif, E. (2017). The relationship between intergenerational educational mobility and public spending: Evidence from Canada. Economic Papers, 36(3), 335–350. Scholar
  61. Laurin, J. C., Geoffroy, M., Boivin, M., Japel, C., Raynault, M., Tremblay, R. E., et al. (2015). Child care services, socioeconomic inequalities, and academic performance. Pediatrics, 136(6), 1112–1124. Scholar
  62. Liberal Party of Canada in Alberta. (2011, March 11). The Canadian learning strategy. Retrieved from
  63. Liebenberg, L., Theron, L., Sanders, J., Munford, R., van Rensburg, A., Rothmann, S., et al. (2016). Bolstering resilience through teacher-student interaction: Lessons for school psychologists. School Psychology International, 37(2), 140–154. Scholar
  64. Lightman, N., & Gingrich, L. G. (2013). The intersecting dynamics of social exclusion: Age, gender, race and immigrant status in Canada’s labour market. Canadian Ethnic Studies, 44(3), 121–145. Scholar
  65. Livingstone, A., & Weinfeld, M. (2017). Black students and high school completion in Quebec and Ontario: A multivariate analysis. Canadian Review of Sociology/Revue canadienne de sociologie, 54(2), 174–197. Scholar
  66. Lyon, K., Frohard-Dourlent, H., Fripp, P., & Guppy, N. (2014). Canada. In P. A. Stevens & A. G. Dworkin (Eds.), The Palgrave handbook of race and ethnic inequalities in education (pp. 170–204). Singapore: Springer.CrossRefGoogle Scholar
  67. Merry, J. J. (2013). Tracing the U.S. deficit in PISA reading skills to early childhood: Evidence from the United States and Canada. Sociology of Education, 86(3), 234–252. Scholar
  68. Milne, E. (2016). Educational issues and inequalities: Experiences of Indigenous Canadian students. In Y. Besen-Cassino (Ed.), Education and youth today (Sociological studies of children and youth, Vol. 20, pp. 65–89). Bingley, UK: Emerald Group.CrossRefGoogle Scholar
  69. O’Grady, K., Deussing, M.-A., Scerbina, T., Fung, K., & Muhe, N. (2016). Measuring up: Canadian results of the OECD PISA study (Statistics Canada catalogue no. 81-590-X).
  70. Oreopoulos, P. (2011). Why do skilled immigrants struggle in the labor market? A field experiment with thirteen thousand resumes. American Economic Journal: Economic Policy, 3(4), 148–171. Scholar
  71. Oreopoulos, P., Brown, R. S., & Lavecchia, A. M. (2017). Pathways to education: An integrated approach to helping at-risk high school students. Journal of Political Economy, 125(4), 947–984. Scholar
  72. Organisation for Economic Co-operation and Development. (2006). Glossary of statistical terms. Retrieved from
  73. Organisation for Economic Co-operation and Development. (2016a). PF3.1: Public spending on childcare and early education. Retrieved from
  74. Organisation for Economic Co-operation and Development. (2016b). PISA 2015 results (Volume I): Excellence and equity in education, PISA. Paris, France: OECD Publishing. Scholar
  75. Organisation for Economic Co-operation and Development. (2017). Educational opportunity for all: Overcoming inequality through the life course. Paris, France: OECD Publishing. Retrieved from
  76. Organisation for Economic Co-operation and Development. (2018a). Education GPS. Retrieved from
  77. Organisation for Economic Co-operation and Development. (2018b). OECD social and welfare statistics: Income distribution.
  78. Parekh, G., Killoran, I., & Crawford, C. (2011). The Toronto connection: Poverty, perceived ability, and access to education equity. Canadian Journal of Education, 34(3), 249–279.Google Scholar
  79. Parker, P. D., Marsh, H. W., Jerrim, J. P., Guo, J., & Dicke, T. (2018). Inequity and excellence in academic performance: Evidence from 27 countries. American Educational Research Journal, 55(4), 836–858. Scholar
  80. Pathways to Education. (2017). Community mapping tool: Mapping at-risk communities in Canada. Retrieved from
  81. Perna, L. W. (2006). Studying college choice: A proposed conceptual model. In J. C. Smart (Ed.), Higher education: Handbook of theory and research (Vol. 21, pp. 99–157). Boston, MA: Kluwer Academic.CrossRefGoogle Scholar
  82. Picot, G., & Hou, F. (2014). Immigration, low income and income inequality in Canada: What’s new in the 2000s? (Statistics Canada catalogue no. 11F0019M). Ottawa, ON: Statistics Canada. Retrieved from
  83. Policy Horizons Canada. (2017). Unlocking the potential of marginalized youth. Ottawa, ON: Government of Canada. Retrieved from
  84. Portnow, S., & Hussain, S. (2016). Income and cognitive stimulation: A reanalysis of the Minnesota family investment program. Prevention Science, 17(5), 565–571. Scholar
  85. Reitz, J. G. (2016). Towards empirical comparison of immigrant integration across nations. Ethnic and Racial Studies, 39(13), 2338–2345. Scholar
  86. Restoule, J., Mashford-Pringle, A., Chacaby, M., Smillie, C., Brunette, C., & Russel, G. (2013). Supporting successful transitions to post-secondary education for Indigenous students: Lessons from an institutional ethnography in Ontario, Canada. The International Indigenous Policy Journal, 4(4), Art. 4. Retrieved from
  87. Roos, N., Brownell, M., Guevremont, R., Levin, B., MacWilliam, L., & Roos, L. (2006). The complete story: A population-based perspective on school performance and educational testing. Canadian Journal of Education, 29(3), 684–705.CrossRefGoogle Scholar
  88. Satzewich, V., & Liodakis, N. (2013). The concepts of ethnicity and “raceˮ. In V. Satzewich & N. Liodakis (Eds.), Race and ethnicity in Canada: A critical introduction (pp. 9–28). Toronto, ON: Oxford University Press.Google Scholar
  89. Schmidt, W. H., Burroughs, N. A., Zoido, P., & Houang, R. T. (2015). The role of schooling in perpetuating educational inequality: An international perspective. Educational Researcher, 44(7), 371–386. Scholar
  90. Shaker, E. (2014). Our schools/our selves: Poverty, polarization, and the educational achievement gap. Ottawa, ON: Canadian Centre for Policy Alternatives.Google Scholar
  91. Statistics Canada. (2011, December 16). Postsecondary education participation among underrepresented and minority groups. Retrieved from
  92. Statistics Canada. (2013, November 25). The education and employment experiences of first nations people living off reserve, Inuit, and Métis: Selected findings from the 2012 Aboriginal Peoples survey. The Daily (Statistics Canada catalogue no. 99-012-X201100311849). Retrieved from
  93. Statistics Canada. (2017a, September 13). Children living in low-income households. Retrieved from
  94. Statistics Canada. (2017b, October 25). Ethnic and cultural origins of Canadians: Portrait of a rich heritage. Retrieved from
  95. Statistics Canada. (2017c, November 29). Does education pay? A comparison of earnings by level of education in Canada and its provinces and territories. Retrieved from
  96. Statistics Canada. (2017d, November 29). Education in Canada: Key results from the 2016 census. Retrieved from
  97. Statistics Canada. (2018a, March 13). Gini coefficients of adjusted market, total and after-tax income. Retrieved from
  98. Statistics Canada. (2018b, July 30). Women in Canada: A gender-based statistical report. Retrieved from
  99. Thomson, K., Guhn, M., Richardson, C. G., Ark, T. K., & Shoveller, J. (2017). Profiles of children’s social–emotional health at school entry and associated income, gender and language inequalities: A cross-sectional population-based study in British Columbia, Canada. BMJ Open, 7(7). Scholar
  100. Timmons, V. (2013). Aboriginal students’ perceptions of post-secondary success initiatives. Canadian Journal of Native Studies, 33(1), 231–236.Google Scholar
  101. Tuovinen, J. (2008). Learning the craft of teaching and learning from worldʼs best practice: The case of Finland. In D. McInerney & A. Liem (Eds.), Teaching and learning: International best practice (pp. 51–77). Charlotte, NC: Information Age.Google Scholar
  102. UNESCO. (2014). The diversification of post-secondary education. Retrieved from
  103. van Huizen, T., & Plantenga, J. (2018). Do children benefit from universal early childhood education and care? A meta-analysis of evidence from natural experiments. Economics of Education Review, 66, 206–222. Scholar
  104. Volante, L., Klinger, D. A., Siegel, M., & Bilgili, Ö. (2017). Making sense of the performance (dis)advantage for immigrant students across Canada. Canadian Journal of Education, 40(3), 330–361.Google Scholar
  105. Ward, M., & Belanger, M. (2010). The family dynamic: A Canadian perspective (5th ed.). Toronto, ON: Nelson.Google Scholar
  106. White, L. A., Prentice, S., & Perlman, M. (2015). The evidence base for early childhood education and care programme investment: What we know, what we donʼt know. Evidence & Policy, 11(4), 529–546. Scholar

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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Queen’s UniversityKingstonCanada

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