Thanks, Mike.
I am going to focus on this question of measurement.
We started off in this meeting talking about the complexity of poverty, and certainly that's what we grapple with, but our starting point here is trying to understand the animal we're working with. The quality of life reporting system has been around now for over a decade. One of its strong features is trying to report on what's happening within municipal boundaries. Typically when data are released, they're released nationally or provincially, and sometimes what are described as cities and communities are in fact typically something like census metropolitan areas, CMAs. CMAs are not cities. They're almost never cities or municipalities. So one thing we try to make sure of is that we are reporting on municipal boundaries.
There are two reasons for that. One is that, as Mike mentioned, in many circumstances municipal governments, whether they're mandated to do it or not, are at the front line, and so it's important for those same municipal governments to understand what's happening in their communities. How do they measure poverty and understand it? That's one reason.
The other is that what's also very apparent when you do measure a range of issues at the municipal level is that poverty takes a very different face when you're looking from coast to coast to coast.
So those are two reasons why measuring poverty at a municipal level is important: because municipal government needs to know what's happening within its boundaries, and because poverty varies very significantly across the country whether you're looking at Regina, Montreal, or Toronto.
Just by example of what I mean by a CMA not being a city, the Toronto CMA actually includes five municipalities: Peel, Halton, Durham, York, and Toronto. The face of poverty in, say, York region or Durham region, which includes places like Oakville and Burlington, would be dramatically different from poverty in Toronto. So really we're trying to break down those administrative boundaries into municipal governments. That's just a starting point.
The reporting looks at a wide range of social, economic, and environmental trends and factors. We have approximately 75 indicators, but underlying those indicators is a pretty big repository of social, economic, and environmental data. These are trends that have been going on now for about 15 years, since 1991. So we do try to look at poverty from a multiplicity of dimensions.
We don't actually use the word “poverty” all the time either. We're looking at issues and trends. We released a theme report, as we called it, in 2004 that looked at income, basic necessities, and housing. In a sense, it was our poverty report, but we weren't using those terms.
I'm going to talk mainly about the ways in which, in effect, we do talk about poverty and the way we measure poverty. Just as a final note, though, on this quality of life reporting system, it is membership-based and the members are municipal governments. At present there are 22 municipalities, and typically they are the larger communities in Canada. So the Communauté métropolitaine de Québec and the Communauté métropolitaine de Montréal would be two of the larger entities in terms of size. Ottawa, Calgary, Edmonton--there are 22 cities representing about 50% of Canada's population. Those are the members. Because it's membership-driven, we are able to ensure that the data get used. The trends that we're talking about are actually used by those municipalities. So they're used both at a local level and also, we hope, at a national level in order to report on what's going on nationally at a local level.
That 2004 report raised a few highlights that are worth noting. One of them was essentially an attempt to get a handle on the risk of homelessness, not a count of homelessness but the factors that might explain homelessness. So we looked at things like social housing waiting lists and levels of unemployment, and lone-parent families-- about seven indicators in all--and we tried to understand, city by city, what was going on and what had been going on over time. So that was one example.
I'll just focus on four areas--because I assume there will be a chance to talk about these things if there's a desire for clarification--in which we are trying to measure poverty. I'll talk a bit about data, if that's okay with everybody.
We rely quite a bit on the Statistics Canada census, and we use that for the well-known LICO, the low-income cut-off. LICO is not a line of poverty; it's just an indication of where you are. If your household has an income below this amount, then you're considered to be living in poverty.
We look at LICO by city across Canada in terms of different kinds of families--single-parent families, couples with kids--and for different demographic groups, such as urban aboriginal communities, for example. There's a range of ways of looking at LICO. There will be one example using Statistics Canada census data, which can get expensive. The price is coming down a bit, but it's still expensive. That's an issue I'll come to later.
So that's LICO--the closest we have to a poverty line.
Another source for measuring poverty is tax filer data, the actual administrative data. This is administrative in the sense that it's not produced for purposes of policy; it's produced because you are required as a Canadian citizen to fill out your income tax form and submit it. There is a whole host of data sitting in there that is quite rich.
We use this tax filer data, again from Statistics Canada, to look at things like the income gap--the relationship between those with the highest income and those with the lowest income--in individual communities to determine how that gap is growing or shrinking. It's relative poverty.
We also use it to get a better handle on working poverty. The income tax forms tell us where you receive your money. Are you getting social assistance? Are you getting employment income? What ratio of that did you get over the year? That helps us construct an understanding of working poverty.
Again, one of the challenges we face is the cost. A single table that provides a richness of data can cost $10,000, which is pricey. But we invest in that sort of data from tax filer information.
A third source, which we consider to be a bit of value-added in the municipal world, is municipal governments and the administrative data they collect. If you've ever signed your kids up for swimming, you have to fill out a form, or at least an application form, and there is data there that gives some information on recreation. We do use recreation. But in terms of the focus we're talking about here, one thing we've been trying to get a handle on is the issue of homelessness and social housing.
Where municipalities fund emergency shelters, they have access to data on shelter usage and on the number of permanent beds by shelter type. That gives you a sense of whether there are more single women or more families going into the shelter system. The social housing waiting lists give you a sense of how many people are actually.... If you have a thousand people on the waiting list and it's been growing over the last 10 years, it gives you a sense of where you're going with social housing.
Again, the point of complexity is that any one of these doesn't really paint a very full picture. What we're trying to do is assemble a few dozen to try to understand what's happening in terms of poverty at a local level. To collect that data, we use a municipal data collection tool, an online survey, that reaches municipal staff.
I'm going to wrap up quickly.
Community-based data is the last source. As an example, FCM will work locally with food banks and seek to compile data from community organizations.
Those are just four examples of how we measure that. I'll just hand this back to Mike for the 45 seconds we have left.