Status of Women Committee on March 26th, 2015

[The Chair, NDP, Hélène LeBlanc]

According to my Blackberry, the time is now 11:01, so I call the 52nd meeting of the Standing Committee on the Status of Women to order.

We are continuing our study on women in skilled trades and science, technology, engineering and mathematics occupations, and what an interesting study it is. We are pleased to have with us, today, Alison Hale, from Statistics Canada. She is the director of the Labour Statistics Division.

Ms. Hale, we are eager to hear what you have to say. You have 10 minutes for your presentation, after which we'll get into questions and answers. Over to you.

[Alison Hale, Director, Labour Statistics Division, Statistics Canada]

Thank you very much, Madam Chair.

I'd like to thank the committee for the opportunity to speak with you on information related to your study. Using data from the 1991 census of population and the 2011 national household survey, I'll provide information on the number and proportion of women holding a certificate in a skilled trade, mechanic and construction, or a diploma or a degree in a STEM-related field of study, also the change over time and the share of women working in skilled trades or an occupation requiring a STEM-related field of study diploma or degree, as well as labour market outcomes of women versus men in skilled trades or in occupations requiring a STEM-related field of study degree or diploma.

Young women are more likely to choose non-STEM fields of study and non-traditional trades. Generally, women's educational attainment has increased over the last decades. Based on the 2011 national household survey, women aged 25 to 34 were in the majority among college and university degree holders. As shown in this chart, young women—in this presentation we're considering young women 25 to 34—tend to concentrate in non-traditional trades, i.e., not mechanic and construction trades, and non-STEM fields of study at college and university. For example, the proportion of women in traditional or skilled trades, such as electricians and carpenters, was 18% compared with 36% for other trades. Women represent 22% of college STEM graduates and 39% of university STEM graduates.

As I realize the committee is interested in women who are in STEM-related occupations, I am now going to switch to look at women working in occupations that are STEM-related.

There has been progress in participation in STEM-related occupations by young women, so now we're looking at data over time, comparing data from 1991 to 2011. Women's higher education is reflected in the fact that they have increased their presence among most occupations that typically require college or university qualifications. Although young women aged 25 to 34 are still in the minority among college and university STEM occupations, making up 27% and 28% of the total employed in these occupations in 2011, their share has increased compared with 1991.

One thing I must point out is that, while there is a common definition of STEM-related fields of study in college and university, there is no equivalent definition of STEM-related occupations. However, for the purpose of this presentation, we used for occupation the group of natural and applied sciences and related occupations, because those in general are equivalent to STEM-related occupations since those are ones where you do require, generally, STEM-related fields of study.

Young women continue to represent a small proportion of young workers in skilled trades. Looking at data comparing 1991 to 2011, again I'm continuing through this presentation with young workers being workers 25 to 34. In both 1991 and 2011, women represented only 5% and 4% of the total young workers employed in mechanic and construction trades. Although the proportion of young women workers remains barely changed over the 20-year period, some occupations did show an increase in their proportion of women, namely cabinet makers, painters, and decorators. However, the proportion of women in occupations such as plumbers, electricians, and motor vehicle mechanics remained unchanged.

Similar to the previous slide, as I mentioned, there is no group called skilled trades in the national occupation classification. For this presentation we used the group mechanic and construction trades since this is what closely corresponds to a skilled trades group.

Going to the next slide, again looking at workers 25 to 34, the proportion of women in college STEM occupations almost doubled from 1991 to 2011. The portion of young workers who are women in college STEM occupations increased from 16% in 1991 to 28% in 2011. In some occupations, women were in the majority and also showed a large increase as a proportion of the total. This is the case for agriculture and fish product inspectors as well as biological technicians. For others, such as mechanical engineering technologists and electronic technicians, the proportion of women is still below 10% and showed little increase though this 20-year period.

One thing I should point out is that when I'm looking at occupations, I am looking at occupations where there was a substantial number of women working in them. I wasn't taking cases where there was only a small number who were working in occupations.

As mentioned earlier, there is no equivalent definition of STEM occupations, so we're using occupations in the group of natural and applied sciences and related occupations where the skill requirement is equivalent to a college-level skill requirement.

Going to slide 6, from 1991 to 2011 the proportion of young workers in university STEM occupations who are women increased from 18% to 26%. Now, looking at university STEM occupations, for some occupations women were in the majority of young workers and showed a large increase over the 20-year period from 1991 to 2011. This is the case for landscape architects and biologists, in addition to mathematicians and actuaries.

Others, such as mechanical and mining engineers, have a relatively small share of women but showed some increase over the 20 years. However, some, such as computer engineers, remained relatively stable over the 20-year period. Similar to what I mentioned in a previous slide, in this case there's no definition for STEM occupations, so we're using occupations in the natural and applied sciences where the skill requirement is equivalent of a university level.

Going to slide 7, partly due to their choice of field of study, young women with a STEM diploma or degree have higher unemployment rates than other women. Often, the better labour market outcomes of young graduates with a STEM degree are used as motivational factors to encourage students to choose a STEM program. Of course, this will vary depending on individual circumstances. Holding a college STEM diploma or a university STEM degree does not necessarily guarantee young women an advantage in terms of unemployment rates. For example, in 2011, young women—again here we're looking at women 25 to 34 who are employed with a STEM qualification from either college or university—had a higher unemployment rate than their counterparts with a non-STEM qualification.

I know there's a lot of information on this slide but the relatively higher unemployment rate of female STEM graduates can be explained at least in part by their program choice. For example, the most common field of study for men with a STEM university degree was engineering, while for women it was sciences. The unemployment rate for men in engineering in May 2011 was 4.3%, while the unemployment rate for women in sciences was 6.6%.

Going to the next slide, another labour market indicator, contrary to young men, there was no difference in the skill mismatch for young women university degree holders whether or not they had a STEM degree. The proportion of young women holding a university degree but working in an occupation requiring a high school diploma or less, i.e., those who have a mismatch between their education and the skill level of their occupation, is not different whether they had a STEM degree or not. This proportion was 18% in both situations.

On the other hand, young women holding a university stem diploma had a mismatch of 12%, considerably less than the 22% for young men with a non-STEM university diploma.

Going to the next slide, young women in STEM occupations, however, do have higher employment incomes than other young women, but not higher than young men. Despite the results in terms of unemployment and skill mismatch rates, young women working in STEM occupations have higher employment incomes than do their counterparts working in non-STEM occupations. For example, when they are in college STEM occupations, their employment income is 19% higher, whereas for men the equivalent gap is 12%. So there is a benefit, from an employment income point of view, to working in STEM occupations. Women in a university STEM occupation earn 12% more than their non-STEM counterparts do. For men the gap is slightly higher at 15%.

That was just a bit of information.

[The Chair, NDP, Hélène LeBlanc]

Thank you very much. You did great.

[Alison Hale]

I think that's the first time I've ever managed that.

[The Chair, NDP, Hélène LeBlanc]

That's good. I appreciate it.

We'll now move on to questions.

Ms. Truppe, you may go ahead for seven minutes.

[Susan Truppe, Conservative, London North Centre, ON]

Thank you for being here today for our study.

I'm not sure what other statistics you have with regard to programs that are available for women pursuing either skilled trades or STEM. Maybe I should ask a different question first.

When you ask all these questions to get your data, how is that done in the first place? Is it through a census or a questionnaire that goes to just college and university students? How do you actually get that feedback?

[Alison Hale]

Basically, it's part of the national household survey and part of that was in the long form census. Everybody was asked about their highest level of schooling and what field of study they took. That was across the board, for anything they'd taken. The responses were then classified according to what they reported. Then for the job they were doing in the reference week, they reported what their major duties were. That was all classified according to a standard classification and then comparisons were made across various occupations.

[Susan Truppe, Conservative, London North Centre, ON]

This goes up to 2011. When approximately would information for 2012, for example, normally come out?

[Alison Hale]

Basically we're using the national household survey and the census, so those are every five years, and the labour force survey collects occupation data on a monthly basis. In order to do this sort of study in which you're looking at both field of study at a very detailed level and occupation data at a very detailed level, you need the depth of information that you can get only from the national household survey, which is done every five years.

[Susan Truppe, Conservative, London North Centre, ON]

Okay.

In your position do you summarize and evaluate information specifically for STEM and skilled trades, or do you have knowledge of it just because you're here and you have the statistics in front of you? I just want to know what type of questions to ask.

[Alison Hale]

The interest of the committee gave us an opportunity to dig into the data. We have produced studies previously—and I believe the committee may have seen these—looking at field of study information, looking at what sort of fields people had based on their level of educational attainment, but we hadn't actually pursued looking at STEM-related occupations, so it was an opportunity for us to dig into the data bit.

[Susan Truppe, Conservative, London North Centre, ON]

I was wondering when we were looking at the slides—I think it was the one showing that mechanics and construction had barely changed in 20 years and then we were using different names, because there was no skilled trades name and no STEM name—whether you see that changing in the future in order to collect data for those specific industries. How would we get that changed?

[Alison Hale]

Basically I think it's not so much that we would need more information. It would probably be a matter of doing more investigation as to how we would want to classify the occupations we already have into those that are truly STEM occupations and those that are not. There could be more investigation into what is truly a STEM occupation. Internationally there has been a certain amount of work on that, but it's not clear cut what is truly a science. For engineering it's fairly clear cut, but for scientific technology occupations, it isn't. There is no international definition of what those are, but as much as these things are hot topics, that's very much a hot topic.

[Susan Truppe, Conservative, London North Centre, ON]

Do you see that changing, so that it would be an add-on on the questionnaire at some point—

[Alison Hale]

There's not really any issue—

I'm sorry. I apologize for cutting you off.

[Susan Truppe, Conservative, London North Centre, ON]

—just to get the correct skilled trade jobs or the correct STEM jobs? I know it is hard. You are right about engineering. Math is a little more difficult. You could have a list that's three or four pages.

[Alison Hale]

I would say that we have all of the jobs correctly identified. It's about classifying those jobs as STEM jobs or not. It's more a theoretical exercise of saying, is that truly a STEM job? It's much more of a research issue of determining what you would consider. For example, is teaching physics a STEM job or not? It's a bit of a philosophical issue.

[Susan Truppe, Conservative, London North Centre, ON]

It must make it somewhat difficult to take the information off the sheet you have and know where to put it or what to do with it.

I don't have the questionnaire here. Were there questions asked that may help us with what other courses or careers would help them go into STEM or skilled trades? For example, say somebody wanted to pursue a skilled trade but didn't know how to go about it or wouldn't have any information about skilled trade there because they may not be in that position at that point. Is there a question there that would say “Where do you see yourself in the future?” or “What type of career would you like to go into in the future?” so that we know if people are even thinking about that going forward?

[Alison Hale]

There have been some studies using other information. There are some international studies that have looked at how well schoolchildren at 15 years of age are doing in math and science and where they end up later. I can send you some actual examples. For instance, one study found that young men with lower marks in high school were more likely to choose a STEM program than young women with higher marks were. That's actually produced, and I can forward it to the researchers. I think you may be aware of that. There are a few like that that are out.

[Susan Truppe, Conservative, London North Centre, ON]

Sure, that would be great. Thank you.

Did you say that was an international study? What was that study?

[Alison Hale]

It's a program for international student assessment, but it was looking at Canadian results, so equivalent information. It's taking advantage of an international evaluation.

[The Chair, NDP, Hélène LeBlanc]

Thank you.

Ms. Freeman, your turn for seven minutes.

[Mylène Freeman, NDP, Argenteuil—Papineau—Mirabel, QC]

Thank you, Madam Chair.

Thanks to our presenter.

The data that you've used sourcing for this presentation comes from the 2011 national household survey, as you mentioned. The government decided to cancel the mandatory long form census in 2010, which means that this data from 2011 was under the new ways of collecting data that we have. Is that correct?

[Alison Hale]

Yes.

[Mylène Freeman, NDP, Argenteuil—Papineau—Mirabel, QC]

The long form census did provide detailed sex-disaggregated data on issues like division of labour, poverty, and differences between populations in Canada. It has been replaced by this voluntary national household survey.

Do you see a difference in terms of what questions can be addressed and what kind of gender-disaggregated data you have access to in order to build this presentation, as compared to the kind of data that would be available in the mandatory census?