Social Identity Toolkit



Social Identity Toolkit


The purpose of this toolkit is to disaggregate the indicators used in Raising the Village by two key community determinants: race and gender. This toolkit provides a deeper understanding of the factors that impact children's well-being. When differences in child outcomes are seen among social or demographic groups, they are considered inequitable.

In the future, other social determinants of well-being such as newcomer status, disability and family status will be added, as well as an intersectional analysis that shows the impact of multiple identity factors.

Communities, system leaders, direct-service providers, teachers, parents and children can use this data to inform the development of programs, services and strategies that address inequities. Understanding patterns, trends and differences in outcomes across gender and race can inform targeted outreach, needs assessments, and actions that address structural inequities at all levels. We encourage children, families, service providers and communities to use this data in the ways that make sense for them. Most importantly, this data can be used by children, families, service providers and communities in the ways that meet their needs.

Race

Data analysis that highlights the ways racism and marginalization affect people of colour is critical to the development of anti-racist and equitable policy, programs and services. Disaggregating data by racial identity helps show who may be at increased risk of experiencing poor outcomes.

Not all data sources can be analyzed by race. Of the datasets currently available to us, only the TDSB parent and student census can be disaggregated by race. Racial identity is not collected in EQAO or EDI data. This toolkit below shows the TDSB student and parent census data disaggregated by race.

More consultation and research is needed to understand the complexities of how some children face barriers when others do not. When moving to action, please consider that the best solutions to address inequities come from children and families who experience marginalization.


Race Toolkit

The Raising the Village Race Toolkit provides data that can illustrate how race impacts well-being. We have included the Race Chart below that disaggregates all TDSB student and parent census data by race. First, we will walk through how to use the chart.



* ”By how much” is the degree to which the racial group that is faring the least favourably is doing in comparison to the group faring the most favourably.

How to use the Race Chart

For each indicator, racial groups are ranked from performing most favourably (green) to least favourably (red). Between these two values, all other colours reflect placement toward the top or bottom of the range.



Looking down the columns of the toolkit, you can understand how each racial group is doing overall and in each indicator. Looking at the data this way shows that White and Mixed-Race students scored relatively well (mostly green and yellow boxes) across many of the indicators in both the TDSB Student and Parent Census. In contrast, scores for Aboriginal, Black, Latin American and Middle Eastern students are considerably less favourable (mostly orange and red boxes).

Looking down the columns of the toolkit, you can understand how each racial group is doing overall and in each indicator. Looking at the data this way shows that White and Mixed-Race students scored relatively well (mostly green and yellow boxes) across many of the indicators in both the TDSB Student and Parent Census. In contrast, scores for Aboriginal, Black, Latin American and Middle Eastern students are considerably less favourable (mostly orange and red boxes).



Looking across the rows of the chart, you can focus on a single indicator and understand how each racial group is faring in this indicator compared to other racial groups. For example, looking at students who “rarely or never” feel safe at school, we see that Black students feel the most unsafe compared to White students. In fact, Black students are 2.4 times more likely to feel unsafe at school than White students. In contrast, when we look at the emotional well-being indicator, we see that Black students are doing the most favourably, and are the least likely to score “low” in well-being.



Another way this tool can be used is to compare the responses to similar or related questions between the TDSB Student Census (self-reported by Grades 7 and 8 students) and Parent Census (parent-reported for Grades K to 6 students). For example, when we compare the parent reported responses to feeling nervous or anxious with the student reported well-being index we see that parents of East Asian students were the least likely to report that their child seems nervous or anxious. Yet, East Asian students were the most likely to score low on the well-being index.



These examples are initial observations gleaned from looking at the data disaggregated by race. Explore the chart on the following page to begin your own analysis.


Racial Demographic in Toronto

Racial identity is complex and hard to quantify. Categories that are created for surveys may not sufficiently represent people's social environment and personal experiences.

That said, the racial make-up of Toronto is diverse. The 2016 Census showed that the majority (51.5%) of the City’s total population self-identified as a racialized group member. Moreover, Statistics Canada has projected that the percentage of racialized people will continue to increase. Figure 1 shows the top visible minority groups in Toronto in 2016. Of racialized group members, 25% were South Asian, 22% were Chinese, 17% were Black, 11% were Filipino and 6% were Latin American. Figure 2 shows that in the TDSB, the largest school board in Toronto, children of colour make up 70% of the student population.



Figures 3 and 4 highlight where people of colour live in Toronto. Map 1 tells us which neighbourhoods in Toronto have the highest percentage of residents who are a visible minority based on the 2016 Census. Map 2 shows the geographic distribution of the four largest racial groups in the TDSB (Kindergarten to Grade 8). Both maps highlight that there are large pockets of White people living in central areas and areas along the lake, while parts of Scarborough and North York have higher concentrations of people of colour. The TDSB map provides further insight into where particular ethno-racial communities may be living. A large number of South Asian students are seen in parts of Scarborough and North Etobicoke. East Asian students are seen in North York, Chinatown/Kensington, and parts of the lower Danforth. Many ethno-racial groups are seen throughout the City.

Map 1: Percent of total neighbourhood population who is a visible minority, Statistics Canada, 2016

Map 2: Geographic distribution of TDSB student population by ethno-racial background



Gender

Disparities in well-being based on gender persist despite changing understandings of the socialized nature of gender. Gender socialization starts at the earliest stages of a child’s life when gender role stereotypes and expectations are placed on a child based on their birth sex. Disaggregating data by gender supports the development of policy and programs that help reduce inequities. . However, when responding to gender inequities, caution should be taken tomitigate further stereotyping or accentuating gender constructions. In fact, research has shown that where gender constructions are less accentuated, gender differences in achievement are reduced.

Gender can be analyzed for all datasets used in the Raising the Village Outcomes project. The EQAO dataset can only be analyzed by gender at a School-board or Province-wide level.


Gender Toolkit

Considering the ways that gender may influence and shape well-being is important for creating and advocating for policy, programs and services that address gender disparities. Looking at the data by gender helps us to understand what areas of well-being are most impacted by gender. The Gender Chart below shows the data used in the Raising the Village initiative disaggregated by gender.



How to use the Gender Chart

The gender chart has 5 columns. The first column identifies the indicator, followed by responses for the indicator by girls and boys, the fourth column indicates which gender is faring least favourably on the indicator, and the final column identifies how many times more likely that gender is to fare least favourable. In the example below, 11.9% of girls are vulnerable in physical health and development compared to 17.5% of boys. Boys are faring the least favourably in this indicator and are 1.5 times more likely to be vulnerable in physical health and development than girls.


Percent of children who: Girls Boys Who’s doing worse? By how many times?
Physical Health & Development
Are Vulnerable in Physical Health & Development (EDI) 11.9% 17.5% boys 1.5

Looking down the columns of the chart you can understand how gender begins to impact well-being. At a quick glance, we can look down the “Who’s doing worse?” column to see that on the majority of indicators, boys are faring worse than girls. In particular, boys are more vulnerable than girls across all EDI domains. In emotional maturity, boys are almost 3 times more likely to be vulnerable than girls. Similarly, the EQAO results show that across all subjects boys are faring worse than girls.



Despite these gender disparities, across many of the indicators there are small differences between girls and boys. By looking down the “By how many times?” column we can see a number of indicators where girls and boys are faring similarly (i.e. “1.0” or close to). These indicators include getting more than 2 hours of screen time, not meeting fruit and vegetable consumption guidelines, seeming nervous or anxious, not meeting provincial standard in Math, and not participating in early learning or care programs.

These above examples are initial observations gleaned from looking at the data disaggregated by gender. Explore the chart on the following page to begin your own analysis.


Gender Demographic in Toronto

Toronto’s total population is 48% male and 52% female according to the 2011 Census. However, according to the TDSB Census, there are slightly more male students attending TDSB schools than female, with 51% male and 49% female. This is also reflected in Province-wide EQAO data where 51% of Grade 3 students are male and 49% female.