:
Thank you for inviting us today.
I'm from Statistics Canada, and I'm here with my colleague, Louise Marmen. We're very pleased to have the opportunity to give you a brief overview of Statistics Canada’s approach to gender statistics and how our data can be accessed.
I'll begin with a brief introduction on the Canadian context for gender statistics. The implementation of gender-based analysis throughout federal departments and agencies has ensured demand for gender statistics at Statistics Canada. This was an important development coming out of the 1995 federal plan for gender equality. Our main contribution is the provision of gender statistics, which are then used by policy departments to conduct gender-based analysis.
Here are the definitions we work with when we talk about gender statistics. Gender statistics are data that reflect the situation of women and men, taking into account their different socio-economic realities. Gender statistics are then used in gender-based analysis to assess the differential impact of policies, programs, and legislation on women and men.
As a statistical agency, our gender-based analysis involves assessing existing sources of data and questioning the assumptions underpinning statistical concepts and collection methods, ensuring that we provide sex-disaggregated data as well as data relevant to both men’s and women's experiences.
Statistics Canada collects and analyzes a wealth of gender statistics. They're available in tables, in microdata form, and in analytic publications. I want to talk about each of these sources of information and provide some examples of each type.
First, let me say that a broad range of gender statistics is available on the Statistics Canada website and all of the agency’s outputs are announced in The Daily, which is Statistics Canada’s official release bulletin.
In preparing for today's session, I conducted a quick search of The Daily for the word “gender”, and I had 82 hits on that particular day. I've put a couple of examples in here. There are many data tables as well as studies. Among the data tables were tables broken down by sex on public colleges and institutions, enrolments, and graduates. There were also data tables on shelters for abused women. Those are just a couple of examples. There were many studies, analytic studies, including recent studies on the rising education of women and the gender earnings gap, gender differences in quits and absenteeism, and employment growth among lone mothers in Canada and the U.S.
Also on Statistics Canada’s website are statistics by subject. Under the subject “Society and Community” you'll find “Women and Gender”, where there are links to the latest releases, data tables, publications, and analytic studies. So there's a wealth of information there.
A joint project between Statistics Canada and Status of Women Canada is a publication called Finding Data on Women: A Guide to Major Sources at Statistics Canada . I've brought copies that I can leave with you in both languages. This excellent resource was recently updated and released in March 2007, and it has summary information on a wide range of surveys and administrative data sources that can be used for gender-based analysis. This publication is available for free on the Status of Women Canada website.
Sex-disaggregated data tables are one of our most important sources of gender statistics. These tables include both statistics and indicators and can be found, through links on or after their release, on the Statistics Canada website under “Summary Tables”. For example, you'll find tables on topics such as days lost per worker by industry and sex and many others. Or you can find them in CANSIM II, which is Statistics Canada’s socio-economic database, for a small fee. In CANSIM II you'll find tables such as the number of women and children residing in shelters by facility type and reason of admission, together with types of smokers by age group and sex. Those are just a couple of tables
These tables are prepared with policy-makers and the general research community in mind, so they're very easy to use. They're broken down not only by sex, but also, as often as possible, by geography and age. They are the basis for much of the gender-based analysis being done across the Canadian federal and provincial governments.
After each census, sex-disaggregated table series are produced, based on the analytic themes for census releases, including labour, families, income, and so on. These are another source of data tables disaggregated by sex.
Finally, if among all of those existing resources government departments and researchers have specific needs that aren't addressed, then custom tables can also be purchased directly from Statistics Canada. It's also possible for policy departments to access microdata to do their own analysis, and many policy departments do this.
For cross-sectional surveys we have a process of assessing disclosure risk that enables us to protect the confidentiality of individuals while releasing the majority of information to the public as public use microdata files. These files are available for the general social survey, the Canadian community health survey, the census, and more are made into public use files.
Statistics Canada has established research data centres across the country where academics and government researchers can access more detailed longitudinal microdata, as well as many fully detailed cross-sectional data files. Access to these microdata files allows researchers to use much more complex, multivariate methods. Some examples of those are the national longitudinal survey of children and youth, the aboriginal peoples survey, the national population health survey, and so on. So it's possible to access the microdata in detail there.
Statistics Canada also produces a range of analytic products using gender statistics. One key publication, which I know you're probably aware of, is a statistical compendium called Women in Canada, and again I've brought copies that I'll leave with you, in both languages. It's been produced every five years since 1985. This report paints a comprehensive gender-based portrait of the Canadian population and it includes sections on population, family status, health, education, paid and unpaid work, and detailed sections on sub-populations such as immigrants, aboriginal people, seniors, and others.
The census tables and analytic releases include gender analysis on such topics as labour, education, and place of work, which complement the table products I talked about earlier.
Other highlights in Canadian gender statistics have included the measurement and valuation of unpaid work and the measurement of family violence and spousal violence.
A full list of the analytical work on gender can be found, as I mentioned, on the website under The Daily, or under the subject link of “Women and Gender”.
I will just mention one more analytic product.
The federal, provincial, and territorial ministers responsible for the Status of Women commissioned a report from Statistics Canada in 1997 called Economic Gender Equality Indicators. These indicators were updated in 2001 and published in our flagship journal of Canadian Social Trends.
Statistical programs are funded either by base funding or by cost-recovery funding. In both situations the norm at Statistics Canada is to collect sex as a variable. Canada has been a leader in the field of gender statistics, largely because of its long history of household surveys, where data are routinely disaggregated by sex. Examples of base-funded surveys specifically addressing issues of gender include the time use survey and the victimization survey, and the census can be seen that way too, because there are many variables in there on family and income. Examples of cost-recovery projects on gender-related issues include the maternity experiences survey, which was funded by the Public Health Agency of Canada, and the transition homes survey, which was funded by the family violence initiative. Those are just a couple of examples.
Although Statistics Canada does not have a special division dedicated to the promotion and production of gender statistics, much expertise in gender analysis exists across the agency. For example, the agency provides resources for our involvement in interagency and expert group meetings of the United Nations Economic Commission for Europe on gender statistics--that's a long name. As well, we represented at the UN global program for gender statistics meetings. Resources are also dedicated to special partnership projects such as the Women in Canada publications, which I mentioned, with Status of Women Canada, and the gender and work database project with York University. Those are a couple of examples. That is currently being updated to 2006.
It is through continuous consultation and collaboration with stakeholders and data users and a willingness to innovate that we've made important advances in gender statistics.
First, I'd like to thank the committee very much for the opportunity to answer some of the questions I believe you have related to statistics and data for gender budgeting, especially with regard to three publications, a couple of which Heather has already mentioned: Women in Canada, the Economic Gender Equality Indicators, and a smaller version we call the mini women and men report, which is an at-a-glance publication based on a Swedish model.
I also understand that the committee is interested in both the content of these initiatives and the processes and mechanisms by which they came to be. And I was involved in all three of these, going back to the early eighties, as well as the sort of international version of Women in Canada, the United Nations' The World's Women. So I'm kind of the dinosaur in some of this, I think.
I want to use my presentation time, however, not to talk too much about those specific publications but to put them in a larger context. My current position is as director of the National Council of Welfare, where my focus is on poverty. There are clear links, however, between this work and gender equality, and I'm sure the committee is well aware of this. I don't need to tell you that.
But I also deal with questions of process and mechanisms, as well as content, in this job. In fact, the council concluded that the persistence of gender inequalities and poverty in Canada is very much about governance and values. I'm not going to talk to you a lot about data. These people can do that.
This conclusion was reached after an evaluation of 25 years of poverty statistics and countless recommendations that have gone on a shelf. The council advised the government very recently, based on this work that we did, and I'll quote a phrase that's often quoted in the newspapers and elsewhere.
If there is no long-term vision, no plan, no one identified to lead or carry out the plan, no resources assigned, and no accepted measure of results, we will be mired in the consequences of poverty for generations to come.
And I would contest that this is equally true of gender inequality.
Our recommendation for a national plan to solve poverty is in fact the subject of hearings that have just started in another committee of this House. And I want to draw on a couple of parallels. They've only had two meetings, but already gender is very high on the list there.
So there are three points I'd like to highlight that I think are important to this committee. First, all the traditional poverty indicators—and we've had big arguments about these for the last 15 years—do not do a very good job of capturing the situation of women. This is very important to you, I think, because the economic gender equality indicators project that Heather mentioned does fill in some of those gaps.
Second, aggregate indicators are important, but finding the perfect ones should never serve as a diversion from actually doing something. What matters is the impact that programs and policies are having on people and how we can make them better.
Third, indicators are based on values. And numbers will not speak for themselves; human beings need to do that.
And I want to offer here a very short but powerful story that was told to me in a very different context and it makes so many points that I have to tell somebody, and you're my victims.
This is about a project on an aboriginal reserve. The federal government, concerned about accountability as it is, noticed that this project listed ten employees but only one was getting paid and that person was getting a huge pay cheque. So to Ottawa this is an indicator of a problem, maybe even corruption. It could be huge. It's an indicator; that's all the information Ottawa had. They needed to actually go out and find out what was going on, so they talked to people.
It turned out that the nearest bank for this community was three hours away and this group of people decided it was not the best use of time to have all 10 people take a whole day off to go and cash their pay cheques. So one person received the cheque and distributed it to the others and, by the way, this included court-ordered support to ex-wives, who got paid first.
They had it all figured out, but it wasn't a traditional way of doing things. There was a fix found, and it was quite a simple one. But that's not the point. The point is that there are so many lessons--for example, that time is as much a resource as money, and that you need to talk to people.
The next little section I'd like to talk about deals specifically with gender budgets and program data. To me, this is the biggest gap that exists now.
If you start with an objective like advancing gender equality or solving poverty, then you need to know whether programs are bringing you closer to that objective and how they could improve. Employment insurance is one example. I won't go into detail, but I think many people think that clearly this program has been going in the wrong direction recently. The women with low income who need it are now paying in, but their odds of getting anything out are slim. Nobody would buy a car insurance plan like that.
Similarly, mothers of newborns, who need income the most, have the greatest difficulty accessing maternity benefits and get the least out of them. The program works best for the elites like me who designed it.
EI, however, does do a relatively good job of reporting information, and this is in stark contrast to the personal income tax system, which is increasingly being used as a vehicle for social policy. There are some really good reasons for that, but we don't know a lot about the impacts of that, and they're not regularly published.
I think the taxfiler database is probably something that contains a wealth of information that Canadians should know about, which is quite underutilized. I think the Department of Finance, in particular, is unique in having the capacity to do extremely sophisticated, thorough gender analysis of exactly how some of these impacts work.
I would just very quickly draw the committee's attention to a National Council of Welfare publication, which is a report on the income tax system. It's from back in 1976, so it's really old. Nobody else has really done anything like this since.
I will skip the next little bit and leave it to questions. I was going to talk a bit about the background of women in Canada, and I will certainly entertain questions on that.
The point I would like to make about that publication is I think the greatest value of this compendium is that it helps fill in the detail behind key indicators in order to analyze what's happening. So you can have big indicators, but you need more detail. For many years, the only consistently reported gender equality indicator was the full-time, full-year wage gap. That's really inadequate to understanding the situation. You need to bring things together to look at women's fertility, labour force patterns, education, violence, unpaid work--all of those things.
On the little mini “women and men at a glance”, I don't know if you are aware or have seen this one, but the point of doing that when it was initiated at Status of Women Canada was to make sure that in between this major publication that comes out every five years a key set of indicators could be updated much more frequently for people to use readily.
On the economic gender equality indicators, again, I will talk at only a very surface level about this, but I think the point that's most important for this committee here is that in this FPT ministers' project, the conceptual framework of this document took far more time to develop than the technical data work. This is the way it should be, because the selection of any set of indicators is about values, and in this case the different jurisdictions did not come to a common framework easily. I have some examples here that I can give later if people have questions.
The final thing I would like to say is particularly about the unpaid work--though I don't like using that word and prefer the term non-market work--indicators that are there. They're a critical part of the value system that's really going to work for gender equality, recognizing that women do work of economic value that benefits others, but for which they currently receive little or no monetary compensation.
If Canadians and Canadian politicians decide not to continue to use an indicator like that or don't formalize it and regularize it more, then that's basically like saying that we, as Canadians, know that everybody needs money to live, but some women simply will not get enough money, and that's fine with us. I don't think many people in this room or anywhere else in Canada, when it is put that way, would say that's fine, but tragically our policies make it so.
Thank you.
:
I'd like to thank the committee for having me here today.
I'm a research analyst with Status of Women Canada and I am responsible for the gender equality indicator project, so I'll be providing you with a brief overview of the project as requested by the committee. I think you all have a deck to follow along with.
The Government of Canada has, as we have seen from our previous presenters, a wealth of statistics disaggregated by sex; however, we have discovered that there is a need to create a link between these sources of statistics and a development of a clear set of indicators. This development of a clear set of indicators really builds on the previous work, which was outlined by Sheila and Heather, on economic gender equality indicators and violence indicators put out by the FPT forum of ministers responsible for the Status of Women.
We see that gender equality indicators are being increasingly recognized as an important tool for establishing the state of equality between women and men, both nationally and internationally. We're also starting to see elements of these indicators in other countries. For example, Britain and Ireland have started preliminary work on the creation of gender equality indicator sets, and multinational organizations such as the United Nations and the Commonwealth have also started.
For decision-makers, gender equality indicators could be quite beneficial. They provide evidence for setting policy direction; for monitoring progress on equality for women and men; for taking corrective action; for communicating any progress to a wide variety of audiences, such as policy-makers and the general public; and they support federal GBA policy.
The purpose of the current gender equality indicator project is really to develop a policy tool that tracks the situation of women and men over time in certain key domains--which I'll review shortly--on an annual basis; to monitor key gaps in progress between women and men, and of course, diverse groups of women and men; as well as to provide data to conduct gender-based analysis. We often hear from other departments that they lack the ability to access gender disaggregated data, so this project will address some of those concerns.
We are currently in the preliminary stages of the gender equality indicator project. Status of Women Canada, as the lead on the project, does coordinate a working group that has representation from a number of different government departments. I've listed them here: Agriculture Canada, Citizenship and Immigration, Health, HRSDC, Indian and Northern Affairs, National Science and Engineering Research Council, Statistics Canada, and Treasury Board Secretariat.
The role of the working group is to finalize the draft domains and indicators and present them for approval to our interdepartmental committee on gender equality, who set up the working group; to provide ongoing support to the project and work collaboratively to identify gaps; to liaise with line departments to bring in relevant expertise, feedback, and support--and of course, that includes liaising with our own research and evaluation units to bring in that expertise to help us identify the types of resources and data available. As well, working group members advise on the overall design, measurement, and plan of the project.
The working group has a number of principles that have guided its work. For example, the indicators should be consistent with international reporting, and of course domestic priorities. A key for us was addressing the interrelationship of gender with diversity factors such as race, disability, age, all that kind of thing, as well as addressing data gaps--there may be a need, for example, to collect new data for particular groups. They need to be accessible to users--the policy-makers, the general public, for example. They need to be based on the frequency and availability of data, and provide, of course, data for trends over time--we're not interested in just a finite snapshot in time, but in trends--as well as be selected in key domains. This is basically a notion that less is more. We can't measure everything under the sun, so we have to focus on the areas where women are particularly lagging.
What I'm going to present to you very quickly are the domains we have identified. They are draft domains. If you have questions about them after, I can certainly answer them.
The first one is personal safety and security, which basically looks at improved physical and mental well-being of individuals, a reduced occurrence of violence, and an increased perception of safety. Elements to measure under this domain could be things like health and well-being--so health status, including mental and physical health--rates of violence between women and men--sexual abuse, physical abuse, that sort of thing--and access to justice in trafficking. Other elements to measure in terms of personal safety and security are things like housing and homelessness, not only affordability of housing but also accessibility to housing and shelters.
Another domain is economic security and prosperity. It's basically looking at gender differences in economic prosperity. Elements to measure here would be financial security, so income and earnings, the wage gap potentially, incidents of low income, among other things—as Sheila was saying, it's not exclusive. We would also look at the work in labour markets, so labour force participation; occupational segregation, the segregation of women into what are called pink collar jobs, such as teaching and nursing; unemployment, as well as underemployment; and also measuring things under learning, not only degree attainment as youth, but lifelong learning.
The third domain—and unfortunately Sheila won't like the terminology—is unpaid work. It's the equality of women and men in terms of unpaid work. Although unpaid household work is not an indicator of economic equality, it certainly will have an impact on economic variables. So that's why it was decided to have it as a domain in itself. And of course the elements to measure here are domestic work, such as housework; care work--not only in terms of the care of children, but also care of the elderly, as well as people with long-term disabilities--to illustrate how that can affect the sandwich generation, particularly women; and looking at the impact of unpaid work on labour and income. What are the negative economic consequences of care work for women and men?
The final domain is social-political engagement. What is the nature and level of women's and men's participation in civic activities and in decision-making? Some of the elements to measure here under social and civic participation are voting participation--how many women and men voted in the last municipal, provincial, and federal elections, for example--as well as looking at social networks: What kinds of groups are they involved in? What sorts of social clubs are they accessing? What is the size and composition, for example?
Finally, look at power and decision-making: what's the representation of women and men among elected officials; senior officials in the public service, such as ADMs and DMs; as well as CEOs in the private sector; and in academic institutions, not only presidents and vice-presidents, but also tenured versus non-tenured faculty?
So those are, in a nutshell, the draft domains and indicators. They're bigger than what is probably presented here.
I do want to highlight the crosscut issues and that this project has really focused on the importance of including disaggregated information by diversity factors, particularly because we know that certain groups of women are particularly vulnerable to the effect of inequality.
In terms of next steps for the project--as I've indicated, it is very preliminary, as we just started convening the working group in September—we will finalize the draft domains and indicators in 2008. There will be a verification of these domains and indicators with key stakeholders, and of course that would include this committee as well. We would build on the input to identify specific data to populate the indicators once they're finalized and identify the forum and format indicators. Will they be one publication? Will they be concept papers? Will they be web-based? I hope selected indicators will be available in 2008-09.
That's a brief overview. I'll stop there, and I'm open to any questions the committee might have.
Thank you.
:
We're not doing check-off lists. There are some countries who go for the check-off list. We felt it was not efficient. A check-off list never tells you if you actually have reached people and if you've changed their behaviour.
I know that you've had discussions about training. Training is only one element. Internationally—and Canada follows this model also—it's a set of things. I suppose this is where you're going, with respect to model and processes. We're just starting to be able to work with departments, not just from an individual capacity. With individual capacity, you never know if you're going to have the result you want at the end of the day. You have a critical mass, and it could take forever to train everyone. We are moving towards organizational capacity.
This means you need things like political will, certain structures inside of a department, a governance structure. I think Sheila Regehr spoke of governance structures. These are things we are exploring with the departments. These techniques seem to work in other countries.
Right now, what's the best model? I don't know if I would call it wrong or right. I think we're calling it the best-fit model. What's good for an organization like the Department of Finance may not be good for another organization like Health Canada. That's what we're exploring right now.
I think there was an attempt in the past. I remember, for example, in 2005 the government thought it would be a good thing to have a GBA champion in every department. Is that a good model? Is that a best-fit model? Not sure. Some people will argue that it's much better—I think this is where we're leaning—to have an inherent understanding and a change of behaviour throughout a department, instead of keeping it in the hands of one person or in one unit.
These are things we are exploring. They are part of the accountability approach we're looking for. I think that's where we're at now. We're saying we can train till the cows come home, but we need to make sure that there's accountability with respect to the change in behaviour in a department.
:
That's a really easy question.
It's very difficult. When I was speaking about recommendations, I was speaking more specifically about the National Council of Welfare's recommendations related to poverty. Obviously there is a large gender-equality dimension in that and in the work we do. The same is true of many recommendations, specifically on gender equality, that have been shelved.
It's hard to explain everything. What we find encouraging now on the poverty front is that, probably in the last two years, there's been a huge convergence in understanding that we have to tackle this issue. There's a significant amount of perhaps embarrassment when we start looking at other countries.
There was a very good presentation on poverty this morning by Alain Noël at the Breakfast on the Hill series. He talked about the situation in Europe. We all recognize that the Scandinavians are far ahead of us in many areas. He was talking about the traditional Anglo-grouping, which includes Britain, Ireland, and Canada, and it being on kind of a different path than the others. The United Kingdom, Ireland, and Scotland are now moving in a different direction, too. It is towards different governance models.
The things we've been talking about, as Ms. Minna said, are tools. To be able to use the tools, you need several things in place. This is what the National Council of Welfare tried to do when it analyzed what was going on around the country and around the world on poverty. It applies to any issue: You need a vision; you need some measurable objectives to aim for; you need the indicators so you know whether you're getting there; you need a comprehensive plan so you know that one program isn't going to give with one hand and another, either in the same jurisdiction or in another jurisdiction, is going to take it away. We do these things.
There's a convergence now. I think there's real hope and real learning from other countries and other examples that the solutions are there. He also said this morning that many people are saying that they see some things changing. I would hope this includes gender equality, as well.
:
Yes, I'll do it from the perspective of gender-based analysis processes, and Suzanne may want to add to that from the standpoint of indicators, perhaps, if it's of interest.
This tiraillement, this pulling of the blanket—I'm trying to find the right word in English—has been historical and has been with us for many years. I think it's the difference between the notion, carried by a lot of non-governmental organizations, I would say—people from outside the government—who think that gender-based analysis is not a valid tool because it does a comparison between men and women.... I think the groups would rather see a woman-specific tool used in practice, looking solely at the situation of women and not doing any kind of comparison work.
The premise for us, and for many countries around the world—and you're right, we have countries that come to Status of Women Canada practically on a weekly basis to ask for help on their governance structure—is to take the approach of integration into the policy development process, so that the responsibility to consider gender in all policy development and policies is not just the responsibility of a specific group inside government or inside a department, but of policy makers, and it is in all areas of government business, including decision making.
I think some groups would rather have this done more from what they would call an integrated feminist framework, one in which there's a premise.... I'll take an example. I once heard something like if women make up 52% of the population, they should therefore have 52% of the resources out of the budget. They would have premises and then build the process to achieve the premise. This is not something that is conducive to government making.
Perhaps when I retire, I'll switch sides, but I don't think so. My long term in the public service has shown me that when your average policy analyst, who may never have heard of gender, may never have heard or thought that what he or she is about to develop will have a negative impact on women, changes that behaviour, we've reached a result there. In this, Canada is the envy of the world.
:
Shall I answer the question?
Just thinking about models and the way Canada is doing things generally, compared to some other countries, and to answer the first part about vision, I think at the federal level we really don't see this, but it is happening in other parts of Canada. Obviously, on the poverty front, it's in Quebec and in Newfoundland and Labrador. And now we have Ontario and Nova Scotia all going in the same direction. All of this reflects a model of governance that's more similar to what the European Union is doing, and there are several elements that I think are important. They have been outlined in documents that we've produced. One is called Solving Poverty. But it's not about poverty, it's about everything. It's about a social and economic plan for the country. It's about gender equality. It's about poverty and exclusion. It's all of those things, so you're not doing piecemeal efforts.
There were common objectives. They have indicators they've agreed on that they're all going to measure. So they all know what the goalpost is. They all know where they're going. They all know they have to develop a plan. They all have to report regularly. They all have to consult. There's a transparency and a coordination.
However, interestingly, as this presenter at the Hill this morning indicated, England and Ireland actually moved faster than some of those measures that were put into place in the Lisbon accord because they recognized how severely poverty, in particular, was limiting their economic development.
Now, all of those poverty plans that are working have gender equality embedded right in them. They're all the same thing. It's not we do one thing here and one thing there. It's a common governance model, basically, and there is this open method of coordination. It's interesting, too, because you have an intergovernmental structure. In Europe it's different nations. In Canada we have different jurisdictions. For example, they would have their common base set of indicators that everybody agrees on, and then each country in its own context would fill in detail. But they're all working towards the same thing, and they're all sharing information so they can build on each other.
I think more and more people are looking to that sort of model. We know that Newfoundland and Labrador have built their structure, in which gender equality is central, based very much on the Irish model. I know that directly. Their method of coordination is brilliant. So this idea of having a plan, of having sort of broad government commitment, some common elements, those are the things that seem to be working, no matter what the issue. Those are models that seem to be working.
:
To the first question, I think there's always more one can do. What you heard earlier from Status of Women Canada is true. I manage the general social survey, which has 25,000 respondents. So if we want to look at women in a particular geographic area, broken down by age and minority status, and so on, you will pretty soon have such low cell counts that the results are not releasable. So there's always more you can do. There is a wealth of data that probably isn't being adequately used, so there's a fine line there.
As to how we collect the data, we have administrative data that comes from the provinces, for example, health data on visits to doctors, and education data on enrolments. We also have survey data, usually developed in collaboration and consultation with all of the key stakeholders, including consultations with academics and expert researchers in the area. And we fall under a structure of an advisory committee, which provides expert advice on all of our surveys; and steering committees are usually directly involved too, which include representatives from the policy departments. The advisory committees are broader; they're usually made up of academic researchers, and NGOs sometimes, or a variety of people who have a stake in the result. That's how we go about developing the survey content.
I think it's important for the committee to know that part of what we do in that consultation or what we are counting on from our key stakeholders is for them, having done their gender-based analysis, to raise with us the issues that we need to know about in order to prepare a good questionnaire. I'll just give you a quick example. We just did a survey on older Canadians, 45 and older, and one of the topics we were asking about was retirement. When we consulted with our partners at HRSDC, they told us that retirement readiness is a different issue for women and men, because women have perhaps had work interruptions through their careers, having taken time off to do care, and so on. So if we don't have an adequate sense from the data whether this has happened to the particular women we're looking at, then we won't really be able to answer some of our key policy questions.
Given that, we then develop a questionnaire that will allow them to do that kind of analysis. So that consultation process is where there's a real opportunity to provide better data on gender.
:
I'll try to answer quite briefly.
The comments I was referring to were made by Glenn Drover, who was representing the Canadian Association of Social Workers, which has done a lot of work on women in the economy recently. He was referring to standard measures that both Statistics Canada and HRSDC produce on poverty. There are LICOs, LIMs, pre- and post-tax--the standard kinds of things--and the market basket measure. All these things use household measures, which means that the power imbalances within households are not reflected. There may be women living in very straitened, almost desperate circumstances in households that actually do have some money and wouldn't fall under the thresholds for any of those indicators.
Now, there are only so many things you can do with any one indicator. Again, it seems to be an area of convergence among people working in indicators that we are not going to find the poverty line. We need several measures, a suite of measures, not a gazillion, but a few key ones, and more than one, that will give us a better understanding.
If you, for example, took key poverty measures, if we picked three--most countries seem to have done something like that--and complemented those with things like the economic gender-equality indicators that show what's going on in the labour force, how the tax system is impacting gender equality, and what time use looks like, then you'd get a much better sense of why and how women always end up featuring more prominently in the poverty statistics.
In that aggregate collection of things there's no one measure that's going to give an answer, but those couple of key things--unpaid work, Suzanne mentioned violence as the other key.... It's not just a matter of disaggregating. It's making a deliberate attempt to build statistics about something that we traditionally didn't do for a long time. Those are the two key areas--the non-market and whatever--and with those, I think we could do a good job.