Dominique Riviere explores the spatial dimensions of urban inequality in Toronto, Canada, and suggests some new ways of thinking about poverty
This January, I participated in a meeting with a local Member of Provincial Parliament (MPP), in which my associates and I were trying to convince him to rethink his party’s proposed wage freeze for Ontario’s public sector employees. It was our position that the “wage freeze” was really a set of drastic corporate tax cuts in disguise, which would only serve to widen the (growing) economic inequality gap in Ontario.
Expecting not a small amount of political spin and double-speak from the MPP, I wanted to prepare some compelling evidence against sacrificing Ontario’s most vulnerable workers and families on the altar of corporate gain. Colleagues at the Cities Centre here at the University of Toronto had recently released their report on the “three cities” within Toronto. This report uses census data from 1970 – 2005 to divide Toronto’s neighbourhoods into smaller “cities”, based on their degree of economic affluence. As I was thinking about how I could best use it to make my argument, I realized that the Toronto District School Board’s Learning Opportunities Index (LOI) would also be useful.
The LOI is a measure of the degree of social and economic need of the community in which a given school is located. Released biannually, it is calculated using a combination of median neighbourhood income, the percentage of families whose income is below the Low Income Measure, the highest education levels of the adults, and the proportion of single-parent homes in the neighbourhood. The lower a school ranks on the LOI, the needier it is.
The three “cities” in the Cities Centre report are based on changes in average individual income over the course of thirty-five years. City 1 consists of homes whose incomes increased by 20% or more; City 2 consists of homes whose incomes increased or decreased less than 20%; and City 3 consists of homes whose incomes decreased by 20% or more. Between 1970 and 2005, City 2 shrank almost to non-existence, City 1 grew slightly, and City 3 exploded (and is continuing to do so) rapidly.1
As I looked at both documents, it occurred to me to try to “map” their data onto each other: I figured that if I could demonstrate a clear relationship between the forms of inequity, my argument for not implementing the wage freeze would be that much stronger. Indeed, I discovered that almost all of the lowest-ranked schools on the LOI were located in City 3.2 It was a near perfect match.
Truthfully, I was not that surprised by the fact that the Three Cities and the LOI reports confirmed each other’s findings; after all, they use similar indicators to arrive at their conclusions. What interested me were the policy implications of this for understanding what inequality looks like “on the ground”. As an urban education researcher with strong critical ethnographic and narrativist methodological leanings, I have often found that policies for addressing inequality are woefully removed from the contexts in which they are to be implemented. There are myriad reasons for this, of course, but, in general, “inequality” is frequently conceptualized in an objective, almost abstract, manner. This is problematic, because it then leads to policy interventions that are not as effective as originally intended. Instead, as Sara Ahmed has argued so eloquently, “you end up doing the document rather than doing the doing”. So, I wondered if there was something significant about layering data in this way to draw a portrait of inequality that spoke to the lived experiences of people who were the most negatively affected by it, and use that portrait to develop inequality policy from the ground up. Consider the following example:
For the 2007 – 2010 academic years, the Parent Councils of the twenty lowest elementary schools on the LOI collectively raised about $140,000.3
How much did the Parent Councils of the twenty highest elementary schools raise, collectively, over the same period of time?
About $4,900,000. 4
As staggering as this information is, it makes sense, given what is now known about income distribution in Toronto. What matters, then, is how the policy frameworks for addressing this kind of systemic inequality are developed. I am proposing an inductive and iterative process, wherein critical questions were asked about how people might actually experience inequality in their daily lives.
So, if educational researchers and policymakers were to “map” the Three Cities, LOI, and Toronto District School Board fundraising data onto each other, they could then begin to generate a list of questions about the day-to-day schooling experiences for both the students who attend the lowest twenty elementary schools on the LOI, and the ones who attend the highest twenty elementary schools. These questions could include:
- What kinds of enrichment opportunities might these students be afforded?
- What is the physical state of their school buildings and, if in need of repair, what funds are available to do so?
- What types of educational resources might be made available to them?
- How might the economic realities of their lives affect their perspectives on schooling and education? Or on academic success?
- What messages might they be internalizing about their potential to make significant contributions to their communities?
- What messages might they be internalizing about their overall place – and worth – in society?
The answers to these questions could then become concrete points of reference – “touchstones”, if you will – which researchers and policymakers would continually revisit and expand upon as they developed the policy to address this particular form of educational inequity. The policy would reach “saturation” when no new critical questions could be generated.
Since this is a thought experiment, there are many practical questions about whether and how my proposed policy development process would work in the real world: would it only be effective for small scale, neighbourhood-level policy interventions, or could it have a broader impact? Would it only apply to educational inequity, or could it be applied across disciplines? Is it simply reinventing the wheel of policy development, or could it lead us closer to “doing the doing” instead of “doing the document”? I don’t as yet know the answers to these questions, but I think we owe it to ourselves – and to the people we are hoping to serve – to find out.
1 It is noteworthy that City 3 is also the most racialized of the “cities” in Toronto, home to many immigrants and Canadians who are visible minorities.
2 This conclusion is based on the 2009 LOI, as the 2011 version had not been released at the time. It is available now and, with a few exceptions, the positions of the lowest-ranked schools have not changed much.