SRSR Committee Meeting

     Welcome to meeting number 61 of the Standing Committee on Science and Research.

    Today's committee meeting is taking place in a hybrid format, pursuant to the Standing Orders. Members are attending in person in the room. We also have members and witnesses here via Zoom.

     I'd like to make a few comments for the benefit of the witnesses and the members.

    First of all, please wait for me to recognize you by name before speaking. For those participating by video conference, click the microphone icon to activate your mike. When speaking, please speak slowly and clearly. If you're not speaking, please mute your mike. For those on Zoom, we have interpretation services. You have the choice, at the bottom of your screen, of floor, English or French. For those in the room, you can use your earpiece and select the desired channel.

     Although this room is equipped with a powerful audio system, we do have feedback from time to time. That can be very harmful to our interpreters and can cause serious injuries. Most commonly, the feedback happens because the earpiece being worn is too close to the microphone, so please keep your earpiece away from the mike. When your headset is plugged in, avoid manipulating the earpiece when it's not in use by placing it on the table and away from the microphone.

     In accordance with the committee's routine motion concerning connection tests for witnesses, I am informing the committee that all witnesses have completed the required connection tests in advance of the meeting.

    As a reminder, all comments, again, should come through me, as the chair.

    Now we'll get started.

    Pursuant to Standing Order 108(3)(i) and the motion adopted by the committee on Monday, December 5, 2022, the committee resumes its study on the long-term impacts of pay gaps experienced by different genders and equity-seeking groups among faculty at Canadian universities.

    It's now my pleasure to welcome, as an individual, Dr. Malinda Smith, vice-provost and associate vice-president of research, equity, diversity and inclusion, at the University of Calgary, where the sky is big and blue today. We also have, from the Canadian National Institute for the Blind, Dr. Mahadeo Sukhai, vice-president, research and international affairs, and chief accessibility officer.

    They are here by video conference.

    Each of you will have five minutes for your opening statements.

    We'll start with Dr. Malinda Smith from the University of Calgary.

    Good afternoon. Thank you very much for the opportunity to discuss the impacts of pay gaps among faculty at Canadian universities.

    Before I begin, I would like to acknowledge that I'm speaking to you from the traditional territories of the people of the Treaty 7 region in southern Alberta. The city of Calgary is also home to the Métis Nation of Alberta, districts 5 and 6.

    Pay inequity is a significant obstacle to achieving an equitable, diverse, inclusive and accessible Canadian post-secondary sector. Its impacts are uneven. It differentially impacts members of federally designated groups, including women, indigenous people, racialized or visible minorities and persons with disabilities. While lesbian, gay, bisexual, transgender, queer and two-spirit people are not yet included among FDGs, this absence is recognized as an equity issue, as highlighted in the consultations by the Employment Equity Act review task force.

    In the post-secondary sector, we have significant data gaps on the representation, attainment, experiences and wage gaps for all FDGs, and this is the case for members of the LGBTQ2S+ community. I might point out that these gaps were identified in the Royal Commission on Equality in Employment in 1984—the Abella report. We are still dealing with these issues 40 years on.

    To understand pay gaps among faculty, we need to use an equity lens and an intersectional lens, because pay gaps disproportionately impact members of some groups of Canadian university professors more than others.

     I want to briefly answer four questions: What does an intersectional equity lens show? What are some common articulated reasons for the gaps? What are the impacts of the gaps? I'll focus on those. What needs to be done to ameliorate those pay gaps? I will emphasize those.

    First, with regard to what an intersectionality lens shows about the pay gaps of faculty, we can look at “Differences in Representation and Employment Income of Racialized University Professors” by Howard Ramos and Peter Li, in The Equity Myth. They highlight that incomes show that white male professors earn the most, followed by visible minority South Asian men and aboriginal men. Among those with the lowest mean incomes were visible minority Black women, Arab women, Asian women and South Asian women, all earning half of the average. While white female professors had the highest income, it is also notable that their income was clearly below the average of white males.

    They go on to argue that, for some, this might be the result of underperformance, hiring, publication records, success in funding or willingness to offer services, but that's not enough. The data shows.... For that argument to hold convincingly—that visible minority professors systematically underperform in productivity compared to white professors at all levels—we would need to see this in the data. However, representation and earning outcomes cannot be easily dismissed by productivity differences alone.

    Secondly, the Canadian Association of Universities Teachers' “Underrepresented & Underpaid” highlighted that full-time women university professors, on average, continue to earn significantly less compared to their white male counterparts. Racialized women professors experience a rate of unemployment that is almost twice as high as that of non-racialized women, and there's a persistent and indeed worsening gap between this group and both women who are not racialized and racialized men.

    I can highlight, as well, that in the policy brief for the Employment Equity Act review task force, it was shown that the wage gap was wider for indigenous women, women with disabilities, racialized women and newcomer women. In effect, intersectional analysis matters.

    What accounts for these gaps?

    It's educational attainment, job tenure, part-time versus full-time, unionized versus non-unionized, but also biases in discretionary university compensation, for example, merit determination, retention determination, salary adjustments and market supplements. Sociologists Ramos and Li also highlighted human capital factors, seniority, productivity and discrimination. Economists Blau and Khan also say that 62% of the wage gap can be explained by factors such as “occupational segregation”, full-time versus part-time, rank and experience.

    However, the full 38% cannot be explained by these quantitative factors alone. They suggest that discrimination is a factor.

    What are the implications? They're profound—

    I'm sorry, Dr. Smith. I'm going to have to call time on you, but maybe we can get to the implications through the questions and answers.

     Thank you very much for your testimony.

    We're going to go to Dr. Sukhai from the CNIB for five minutes, please.

     Good afternoon, honourable members of the House of Commons Standing Committee on Science and Research.

    I'm Dr. Mahadeo Sukhai, the vice-president of research and international affairs and the chief accessibility officer of the CNIB—

    Dr. Sukhai, I apologize. It was lagging a bit and there was some latency. We'll let you know if we run into any technical problems.

     You may resume.

    It looks like we're going. I've paused your time, but let's keep going.

    Thank you.

     Today I wish to discuss a critical issue—the enduring pay gaps experienced by different genders and equity-seeking groups among faculty at Canadian universities—and I want to specifically emphasize researchers with disabilities.

    The recent Statistics Canada report “Reports on Disability and Accessibility in Canada: Earnings pay gap among persons with and without disabilities, 2019” reveals that individuals with disabilities age 16 and older “earn 21.4% less than [those] without disabilities”. This gap widens for individuals with cognitive disabilities, who earn up to 46.6% less, and the gap also widens over time as persons with disabilities who are 40 years of age earn significantly less in comparison to their peers living without disabilities than those who are in their twenties. These gaps present significant obstacles to inclusion, diversity, equity and accessibility—IDEA—in the workplace.

    In the sciences, researchers with disabilities often bear the burden of advocating for their own workplace adjustments or accommodations while grappling with systemic biases. This cognitive load or access work can hinder their career progression and well-being. Furthermore, the health impacts of continual stress, often referred to as weathering; the additional living costs associated with living with a disability; the barriers to publishing; the lack of accessible spaces within research, such as meetings, conferences, classrooms, seminars and laboratories; and the prevalent biases in hiring and promotion processes—among others—present substantial barriers for researchers with disabilities. These barriers further exacerbate the experienced pay gap. Additionally, these affect not just the financial security but also the mental health of researchers with disabilities. The stress of navigating existing systemic barriers, advocating for accommodations and dealing with pay inequity can significantly impact mental health, affecting productivity and career progression.

    In research environments, one of the most significant challenges in addressing long-term pay gaps is the lack of comprehensive demographic data about researchers with disabilities in academia and outside of academia. Without this data, ethically sourced and carefully handled, we cannot fully grasp the breadth and depth of this issue. We must remember that disability is not a monolith. It is, in fact, a spectrum of unique experiences shaped by intersecting identities, including but not limited to gender, race and career trajectory, thereby creating unique experiences and challenges. Recognizing these nuances is critical for understanding the current existing barriers and pay gaps.

    One nuance in particular that must be very clearly acknowledged is that of a person's age when they first identify as living with disabilities. A faculty member who is a full professor when they first experience disability will have a very different career trajectory, career quality and, hence, resulting pay-equity gap than a person born with a disability who experiences ableism and many significant barriers, both personal and systemic, as they work to become and stay faculty.

    In addressing these issues, the role of policy cannot be understated. Policies that enforce pay equity, promote accessibility and ensure inclusive representation within academic spaces are vital. However, they are not enough on their own. We also need a cultural shift that values diversity, champions inclusivity and acknowledges the significant contributions of researchers with disabilities.

    Universities, research institutions and granting agencies play an imperative role in either perpetuating or mitigating these pay gaps. It is their responsibility to take proactive steps to understand and address existing pay gaps, promote pay equity and create supportive and inclusive environments for all researchers, regardless of their identities.

    That being stated, it is also imperative to acknowledge that there is a substantial lack of appropriate training and understanding of accessibility specific to research environments, and this knowledge gap perpetuates the barriers that are faced by researchers with disabilities. As such, there is an urgent need for systemic change in perception and attitudes towards disability in academia.

    Finally, it is important to highlight the benefits of IDEA in research. IDEA leads to better outcomes and innovation. By addressing pay gaps and promoting pay equity, we can create an environment where all researchers thrive, leading to a more robust, innovative and inclusive research community.

     Understanding and addressing pay equity is not just an issue of fairness, it is a issue of quality, innovation and excellence in research.

    We must act now to ensure that all researchers, including those with disabilities, have an equitable opportunity to contribute to the advancement of knowledge in Canada.

    Terrific. Thank you very much.

    Thank you both for your testimony.

    Now moving to our questions, we're starting a six-minute round with Ben Lobb, please.

    Mr. Chair—

    Just one second, we have a point of order.

    I simply want to say that the interpreters were having difficulty with the last witness. His microphone is not good enough.

    Thank you.

    I was watching the interpreters for a sign during the testimony. I didn't see one come.

    I can confirm that they told me that.

    To the presenters, if you could maybe speak up and speak slowly when you're answering the question, we'll see whether that can work.

    Thank you for pointing that out, Monsieur Blanchette-Joncas.

    Now for six minutes we go to Mr. Lobb, please.

    Thanks very much.

    Thank you to both our guests for coming today. My first question is for Dr. Smith.

    I'm just wondering. Dr. Smith, do you work with human resources on your mission in equity, diversity and inclusion? How does that relationship work with human resources at the university?

     The short answer is, yes, I do. The relationship is well. Equity, diversity, inclusion and accessibility at the University of Calgary, as at most universities, is a collaboration with human resources, offices of institutional analysis on data and the registrar's office, among others. The relationship, I think, is well, because it's vital to our standards in data collection.

    How do you track your compensation to know if it's fair across Canada or even within the university? How do you track that personally to know that you're getting fair compensation for the work that you do?

    There are a number of ways to do that. The UCASS system, of course, is probably the.... Statistics Canada is authoritative on publicly disclosed data. Also, I'm in Alberta, so we have public transparency data.

    There are a number of studies, some of which I highlighted, where people do comparative data analysis. What I also highlighted in my comments is that there are parts of the data that are discretionary and we might not be able to track. For example, anything that's, say, a market supplement might not be revealed publicly, or if there is something that might be a retention offer, which is made on a discretionary basis, those are generally made to men more than women, as an example, because men are more likely to seek jobs elsewhere and therefore need to be retained. That also changes the factor. Also, if you're a woman, things like maternity leave impact your income. Whether one's family-friendly or...child care also impacts one's income over time.

    The data on racialized women is so persistent across studies—Statistics Canada, sociologists, economists, the Conference Board of Canada, Catalyst Canada—that one has to take seriously the need for intersectional analysis.

    I'm making it clear that it's needed, but it's not sufficient.

    Universities have the most educated people, I suspect, in all the workforces across the country. There are many highly paid professionals there—the dean, all the people in HR, people like you. Let's drill into, let's say, the University of Calgary. You could go across all universities, but you work there so we'll talk about this one. Are there people at your university who are not receiving fair compensation based on all the classifications you provided?

    If there are people who aren't receiving fair compensation, why not? Everybody's there, so they should know who makes what. Why is this not happening?

    There are three responses to your question.

    First, the public disclosure is for a certain amount. That's for those who are higher up. I would say that's clear. That's less so for many staff members who work in universities. It's not clear for job offers. We don't see until much later on the pay gap that emerges—probably around the senior associate or full professor....

    At the University of Calgary, as probably at many U15 universities, there is a commitment to pay equity. The important thing about tracking the data is to ameliorate inequities, so there are mechanisms in place that are important to ensure those gaps are closed.

     Does HR see the offer letters that go out to prospective university employees?

     HR sees the letters because it has to implement these in its system.

    Then why wouldn't HR say to a professor, “Whoa, you're way low here. You can't offer that.” How come that doesn't take place?

    That's a very good question.

    Who should be accountable for pointing out discrepancies? I would say hiring is the prerogative of a provost or a vice-president academic, in relation to a dean or a chair. It's not necessarily HR, per se, although HR may implement practices to close those gaps.

    I like your question, because it highlights accountability. If you know there are gaps among assistant, associate and full professors across racial lines, whose responsibility is it to identify and ameliorate this proactively? I believe it's the chairs, deans and provosts who should do this.

    I think it's also HR or legal. It's also a dean at a university and the president of the university—

    We'll have to leave that as a comment, but that's a very good back-and-forth.

     Thank you.

    Now, we go to Mr. Turnbull for six minutes.

    Thanks, Mr. Chair.

    Thanks to both witnesses for being here today. Your opening testimony was great, although eye-opening, for sure.

    I want to get back to Dr. Smith.

    In your opening remarks, you talked about using an equity lens and then about the importance of an intersectional lens. I took your point very well when you described the statistics, research and information you were presenting. It seems there's consistency in the fact that racialized women, disabled women and other subgroups are experiencing a lack of pay equity—systematically so, by the sound of it in your testimony.

    What I want to ask you, though, is this: In your opening remarks, you were talking about this, and you were getting to the point of saying discrimination is a factor. Then you were cut off because of time. I want you to go back to that point and finish what you were saying.

    How do you know discrimination is a factor? I'm not disagreeing with you by asking that question at all. I think it is, and we need to acknowledge it. I want to give you the opportunity to finish what you were saying and make your points about why discrimination is a factor.

    Thank you very much for the opportunity.

    I highlighted two studies. One is by Howard Ramos and Peter Li. It's called “Differences in Representation and Employment Income of Racialized University Professors”. That appeared in The Equity Myth in 2017. The second study I highlighted comes from the Canadian Association of University Teachers, or CAUT. Again, it draws from Statistics Canada data. A third study, I think, is very important. It is highlighted in the Employment Equity Act review task force briefs. Consistently, the Catalyst Canada advisory board highlights the same kinds of discrepancies.

    These scholars did multiple regression analyses to try to rule out other possibilities. Is it age, seniority or, for example, human capital? Is it factors such as gender or race? How is it that racialized women, for example, or women with disabilities consistently have lower salaries?

    May I point out that, in a royal commission report in 1984, Justice Rosalie Silberman Abella alluded to the same fact 40 years ago? The question is, why has it not changed?

     Howard Ramos and Peter Li point out that we have to do other kinds of studies that are non-quantitative. Look at productivity. Are they more productive? Are they getting more research grants? Are they engaged in more prestigious services? Ramos did a study on that. Multiple studies show that racialized minorities outperform and out-innovate in many instances, but they are still underpaid. In fact, the 2021 census for Canada pointed out higher education and lower pay, or higher education and underemployment. This pattern has persisted.

    What are the factors that account for this? The Conference Board of Canada as well as Li and Ramos say we cannot rule out discrimination as a factor in these kinds of things, because nothing else seems to make sense when you do regression analysis on the role of education, seniority, etc.

     Essentially, Dr. Smith, based on all the research and studies you're pointing to, they've sort of ruled out all of the other possible explanations, which would then lead us to believe that discrimination has to be a factor. Is there additional research as to where that discrimination is specifically happening?

    One question that I want to pose to you and Dr. Sukhai is whether Stats Canada.... You both mentioned tracking data, and how important that is. I think Dr. Sukhai mentioned the lack of demographic data, and you both cited StatsCan as being one of the key sources for information. Do we need additional data, and what specifically would you require to inform better interventions to close that pay equity gap?

    This is for both of you. I'll start with Dr. Smith, and then go to Dr. Sukhai.

     We have good data, including administrative data, on gender—women, men and non-binary. We have inadequate data on racialized persons, persons with disabilities and indigenous peoples. These are not administrative data, these are based on self-identification.

    We need a national data collection standard to modernize UCASS, so that it includes all equity-deserving groups. We need a common methodology for collecting the data and analyzing it, so we have consistency and this, again, was called for in the 1984 Royal Commission on Equality in Employment.

     I'll leave it there, so that Professor Sukhai can answer.

    You can answer briefly as we only have a few seconds.

     I agree with what Dr. Smith said.

    I would actually add that part of the current challenge is that universities and granting agencies will ask the self-identification questionnaires, but not always in a standardized way, not always in the same way. The data then cannot necessarily be standardized and reviewed across the country.

    If, for example—

    Thank you. We're over time, but thank you for that.

    We'll now go to Mr. Blanchette-Joncas for six minutes.

    Thank you, Mr. Chair.

    Greetings to the witnesses who have joined us today.

    My first question is for Mr. Sukhai.

    Mr. Sukhai, at the committee's various meetings, numerous witnesses have talked about insufficient data on disabilities among university faculty members. Such data would help the committee better identify the pay equity issues among faculty members. I would like to hear your specific thoughts on that.

    What can the federal government do to effectively support pay equity among university faculty members, especially as regards disabilities?

    First of all, we need to come back to whether we are having a conversation about a faculty member who's an associate professor or a full professor who acquires the lived experience with a disability as they get older, or are we talking about somebody like me, for example, who was born with a congenital disability and who then goes through a research career and starts encountering barriers as an early-career researcher?

    If we talk about the second group, because that's actually where the greater emphasis does need to be placed, we can start talking about programs through the tri-council and in other ways to foster the participation of early-career researchers with disabilities. Those would have to be done in sensitive and respectful ways, so that we're not mandating or forcing a disclosure of a lived experience if that's not something that somebody wants to do.

    Certainly, through funding and through scholarships and fellowships, you can actually start to increase that level of representation. You can also develop policy and programs around the research environment and around accessibility within the research space. It's one thing to mandate a representation target, but it's another thing to make the environment fully accessible. Both actually need to be done in order to ensure that researchers with disabilities are retained.

    Thank you very much, Mr. Sukhai.

    What kind of data do you think should be gathered about persons with disabilities in order to promote pay equity? I understand of course that such data would always be confidential, out of respect for individuals.

     I think we would need to know the disability group. Again, as I said, is somebody congenital, or did they acquire a disability in childhood or later in life? I think we need to know that. Everything else is potentially inferable from those two pieces. You can infer multiple lived experiences at once.

    If you use the way that Statistics Canada asks the disability screening question, you're also able to understand a bit of the functional impacts. That combination of functional impacts, age of onset and number and types of disabilities will give us a lot to go along with everything else that gets captured in terms of pay, such as when somebody joins the professoriate, what their salary is and how that salary changes with time.

    I will say one other thing, if I have time.

    You have about two minutes in total with Monsieur Blanchette-Joncas.

    The interpreters are really struggling.

    Thank you, interpreters, for doing the job.

    There's a bit of a feedback on your microphone. Try speaking more slowly so we can catch it.

    Thank you.

    Of course.

    The one other thing I would say is that there are some really good economic analyses of earning potential over time. An example is post-doctoral scholars as they compare to other postgraduate career paths. Those kinds of economic analyses also end up applying to persons with disabilities, because many of the deeply held conventions around productivity and persons with disabilities go along with this notion of starting later or moving through our career paths more slowly. That also ends up leading to diverging earning potential over time.

    Thank you, Mr. Sukhai.

    We recognize what the three organizations receiving federal funding do as regards equity, diversity and inclusion for underrepresented groups, but what about the pay gap? What needs to be improved to reduce the pay gap, particularly for persons with disabilities?

    In less than one minute, the short answer is that there aren't any.

    If there is anything like a link or anything in writing that comes up later that you could submit to the clerk, it would be wonderful. I know timing is very tight in these sessions.

    We'll go to Mr. Cannings for six minutes, please.

    Thank you to both witnesses for being here today.

    I'm going to start with Dr. Smith.

    In your initial presentation, you mentioned several possibilities of differences that might explain different levels of pay gaps. You mentioned unionized versus non-unionized. When I worked at the University of British Columbia, there were three groups of workers. There was the faculty association with the tenured faculty, there were administrative and professional people, and then there were the unionized workers throughout the university.

    Could you comment on whether you have data that would separate out the pay gaps within those groups? Do you have that sort of data? Can you explain why there might be differences based on those different categories?

     Thank you very much for your question.

    I think, with the unionized workers, clearly they obviously negotiate and they have comparative data on which to negotiate, including for across the post-secondary sector, which they have obtained through their associations and, I would say, their national association, the Canadian Association of University Teachers. I would say that the pay for sessionals, who also are members of these sometimes unionized workers, would be impacted by the fact that they are maybe term to term or year to year. This is one reason I really appreciate UCASS's modernization initiative to try to track the experiences of sessional, part-time or contract workers who are now teaching a significant percentage of the courses in Canadian universities. However, I would say there is strength in the collective bargaining process for those who can negotiate for better pay, for pay increases over time and for benefits commensurate with their experience.

    I'm less familiar with the non-unionized workers, except for maybe support and management and professional staff. I would say they would be more vulnerable and more likely to be laid off more readily than would those with tenure-track positions, and that is no surprise to any of us on this matter. I say that as someone who has been privileged enough to be a tenured professor and who still is a tenured professor as the senior administrator. Undoubtedly, that's a privileged position in the university environment.

    We've been hearing testimony from various witnesses that would seem to indicate that, within the tenured professors, this pay gap tends to get worse, to increase, the higher you go in that tenure system and the longer you're in the system, especially between men and women. For male tenured professors who are full professors, that gap is bigger than it is at, say, associate or assistant professor levels.

    Is that something you see at the University of Calgary, and is there some way of trying to ameliorate that?

    I would focus less on a specific university, like the University of Calgary, and say that the UCASS data is very helpful for providing a snapshot of the post-secondary sector largely. I would say that you would find that the generational impact is important. Incoming new assistant professors, for example, who have better negotiated salaries could be making more than would some more senior associate professors, so you start to see a gap there that has implications over time. I would say that, because we moved the retirement age for full professors, for full professors their age might be more senior than it was historically, so the wage gap might also be higher than, say, it was historically when there was a cut-off at age 65.

    There are a number of overlapping factors that shape this, but I don't want to rule out the gender dynamics that impact our women. Those can include lower salary offers, the fact that women do different kinds of work that are less rewarded, such as serving as professional workers or mentoring students, or that they may get less prestigious offers to be research chairs. We know that historically—and we're trying to change this with the tri-council—women didn't get as many Canada research chairs.

    As you know from the research on full professors and senior leadership, women are significantly under-represented in these kinds of roles. As well, racialized people are severely under-represented in senior leadership roles, including at my own institution, which we acknowledge. These things all impact salary and they all impact the gap. To the extent that we don't close these other gaps—hiring, promotion, remuneration—we will continue to see them grow or remain the same, which is virtually what's happening right now.

    Okay. Thank you.

    Thank you.

    Now we're going to do five minutes, five minutes, two and a half minutes and two and a half minutes, starting with Mrs. Goodridge from the Conservatives for five minutes.

    Go ahead, please.

     Thank you so much, Chair.

    Thank you to our witnesses for participating as part of this study.

    Dr. Smith, I'd like to build on some of the questions that were asked by my colleague Mr. Lobb regarding the role of HR. Do you think universities have to play more of a role internally to address pay gaps?

     That is a beautiful question. The short answer is “yes”. You're highlighting a question of accountability and who's accountable.

    Obviously, those of us who are full-time continuing in administration are the ones who have the best data and knowledge and who are in a position of power and privilege to address it.

    Thank you. I appreciate that, because that was my follow-up question.

    I took a quick look while you were speaking—I remembered the Alberta sunshine list when it comes to public disclosure—at the University of Calgary. A lot of information is publicly available. It's not even a space where this is somehow hidden information.

    If we were to give you the power to make change at the University of Calgary, or at the the University of Alberta, let's say, so that you're not implicating your own university right now, what would be the first thing you'd do?

    That's a good question.

     Just so you know, I spent over 20 years at the University of Alberta. I'm a graduate, so I love them all.

    I'm also an alumnus of the U of A. You were actually teaching at the U of A when I was a student there.

     One thing I would do is require every chair or dean to have a consultation every two to three years to review all the salaries within a unit to make sure that, when assistant professors who are coming in are getting better salaries by virtue of the negotiated agreement, there isn't an inequity for the assistant and associate professors. Those associate professors, from what they call the “sandwich” generation, are primarily women, including women who, for example, took time off to have their children. Once you do that, you are almost always already behind—and not because of your knowledge or qualifications or experience—in terms of the salary gap.

    I would say that it would be a requirement to have regularized reviews of all salaries by chairs, deans and the provost, but the administrating body would be HR. I keep coming back to HR for this.

    That's wonderful. Thank you. I wish we could continue having this conversation, but I'm going to switch gears a little bit to Dr. Sukhai.

    A lot of your work has focused on social inclusion and accessibility in STEM, a field in which we know that women have been traditionally left out of or not represented at the same level. Can you tell me what efforts have been made by universities to address these barriers for both women and people with disabilities, and specifically women with disabilities?

     It's a great question.

    I think the barriers that women face in participating in STEM have been better recognized, better talked about and really better.... I'm not going to say “addressed”, but they've been better called attention to over the past thirty-odd years.

    Where I think we start to run into some significant absence of attention is on the experience of students with disabilities, of early-career researchers with disabilities and of women with disabilities doing STEM. I think part of the challenge ends up being this ableist perception of, “Well, you have a disability. You're not really supposed to be in science.” I've encountered it. It's real. It's there. I think there's this sense that you don't have “ability” X, so you can't really participate as a physicist. You can't really participate as a biochemist.

    Then you have this conception of what a scientist should be. You also have this conception of what a productive scientist should be. That definition of productivity doesn't include parental leave. It doesn't include medical leave. It doesn't include mental health leave. It doesn't include needing assistance within the labs. You have these rather structural systemic barriers that are there around disability and that resonate for everybody with disabilities—racialized persons with disabilities, women with disabilities, indigenous scholars with disabilities.

     Thank you.

     Thank you very much as well, Mrs. Goodridge, for your questions.

    Thank you so much.

    Thank you for being a sub. You're certainly welcome at this committee any time.

    We have Dr. Jaczek for five minutes, please.

    Thank you so much, Chair.

     Thank you to the witnesses.

    We've heard from both of you on the importance of data, particularly in looking at visible minorities and indigenous persons with disabilities. I think you've made those points very clear. Of course, we have StatsCan coming soon, later during this meeting, and no doubt we will get some recommendations from them, but it strikes me that we've been talking about this issue for about 40 years now.

    Dr. Smith, you made that point. I'm wondering if we're not at the point of some sort of analysis paralysis. In other words, where do we go from here? You talked a bit about accountability in terms of the universities themselves, but what can we—as the federal government in particular—do to advance the cause of these under-represented groups and essentially what pay inequity is. Could you give us some ideas on the role of the federal government?

     Thank you.

    I always go back to Justice Rosalie Silberman Abella's comment about voluntarism. Because these barriers are so self-perpetuating, to wait and hope is not going to have any impact.

     We need better data. I share with Stats Canada, but if the institutions aren't collecting it and collecting it in a systematic way, we're not going to get there. We need good administrative data for each of the equity-deserving groups.

    Second, we need transparency and accountability. MP Goodridge talked about transparency for data later on in the career trajectory, at the higher salary rates. Perhaps we need to see those opening salary rates. If they were transparent, maybe institutions would be less likely to have discrepancies, or we might see fewer biases emerge from the discretionary or the hidden. I think that's really important.

    I think that maybe we need to restrict the other kinds of hidden salaries, whether it's market supplements or these other kinds of factors, or make them public as part of accountability. Also, there need to be consequences for people who are in these roles like mine. If we are tasked or mandated to overlook equity, what are we doing to ensure it's actually happening? I believe that there isn't a lot of accountability despite the talk, and that is a factor for us.

    I personally would like to see a royal commission that looks at racialized minorities in particular—we've had gender, and we've had indigenous—because I think this is a lot of wasted talent, untapped talent, and it impacts our prosperity, it impacts productivity and it impacts our innovation. This is a huge problem for universities, but I think more broadly for our economy in Canada.

    There isn't an accountability that's mandatory, with impacts, so we keep talking about it but doing nothing, really.

    Dr. Sukhai, do you have any ideas for the federal government in terms of intervention? Also, since Dr. Smith has raised it, what do you think about the idea of a royal commission?

     I love the idea of a royal commission. I would broaden the mandate to not just around racialized persons. I would include persons with disabilities.

     I think you raise a very good point about analysis paralysis. I think the reason everyone harps on data is that somebody, somewhere, says that we don't have enough data, even though it's been 40 or 50 years. To some degree, do we need data? Yes, we do, but the lack of data shouldn't stop us from doing what needs to be done.

    I think the federal government has levers through the tri-council. I think the federal government has levers through ISED funding for Mitacs in order to drive accessibility and inclusion in the sciences and to drive accessible inclusion for early-career researchers, both from a representation perspective and from a change to the training environment perspective, because you can't be an assistant professor with a disability if you haven't been a post-doc with a disability, a graduate student with a disability, an undergrad with a disability or a high school student with a disability.

    There are many different points of failure along that career trajectory for, again, somebody like me, who was born with a disability. I think it's really important to say, “Okay, can we pull those levers?” Does it involve a royal commission? Does it involve funding? Does it involve a recognition of the training environment needing to be improved? Does it involve a recognition that representation is an issue? Does it involve a recognition that perhaps there are others elsewhere on the international stage?

    I would point to some of the work that is going on in the United States, which is doing work that I think we could really learn from in this space and that would be good best practice.

     That's terrific. Thank you very much.

    Mr. Blanchette-Joncas, you have the floor for two and a half minutes.

    Thank you, Mr. Chair.

    Ms. Smith, the federally funded agencies have various financial support programs for research and science in Canada. There are of course practices for equity, diversity and inclusion for underrepresented groups, but what do you suggest to reduce the wage gap?

     For early-career researchers, we have some efforts with the tri-agencies around USRAs, which are the undergraduate research stipend awards that they give for undergraduates. We also have some with post-docs. For example, I'm pleased to see that post-doctoral fellows can now at least get mat leave. They didn't in the past. More needs to be done to include racialized persons in the research programs. I know there's push-back against the Canada research chairs program and CFREF, both of which incorporate equity, diversity and inclusion.

    I've researched those for 20 years, and I will say to you, one of the things that impresses me most about Canada is that we have made an effort to ensure we have equitably distributed those research chairs across equity-deserving groups. Persons with disabilities remain chronically under-represented; I should say that.

    By having that diversity among research chairs, it highlights the intersection between diversity, excellence and quality that's a hallmark of the Canadian research ecosystem. I want to say that again. It's a hallmark of the Canadian research ecosystem. It's something we should be proud of—that we are trying to be as inclusive as possible compared with many other places in the world.

    That said, I think those we leave out highlight why we have a gap in productivity and innovation, because there are too many racialized people who are engineers driving cabs, who are doctors as lab technicians, and who are underemployed and underskilled. They could be contributing to our research ecosystem if their credentials were recognized, which is a big issue for us, and if they were properly paid commensurate with their education. I'm sure Stats Canada will tell you the 2021 census data shows that racialized minorities are over-educated compared with the average but are still underpaid and underemployed. The big thing is—

    Thank you.

    I'm trying to find which part of the thought we can end on. Your thoughts are all very good. I really appreciate them, but we are short on time now.

    We will go to Richard Cannings for two and a half minutes, please.

    Thank you.

    I'm going to turn to Dr. Sukhai with my question.

    Dr. Sukhai, you mentioned data being one problem, and the consistency of data across the country and across provincial boundaries. Universities are within the provincial mandate, as my friend from the Bloc likes to point out, and that causes problems. It doesn't just cause problems in university data. It causes problems in crosswalking data across provincial boundaries for all sorts of things, whether it's natural resources, health care or education.

    I'm just wondering what role the federal government could play in turning this around and in getting data that is useful across provincial boundaries. We have Statistics Canada coming up next, and maybe you could give me a good question to ask them.

     My sense is that if you folks could find a way to mandate data standardization.... StatsCan has repositories of great, and some not so great, questions that we have had conversations about. If everybody could ask questions the same way.... In my research, I've switched to asking demographic questions the way StatsCan asks demographic questions, because I need to be able to compare my data with StatsCan's data.

    If you have an engine to collect data and the tri-council is hewing to that engine, by and large, then if there was a way to enforce that level of data standardization across provinces and through the provinces down into the post-secondary system, that would be a really good thing. If you could identify a mechanism by which that was possible, and if StatsCan could identify a mechanism by which that was possible, I would be very friendly to that.

     We've had, in the last round of negotiations around health care funding, that demand, from what I understand, by the federal government on provinces, saying, “Here's some extra funding for health care if you want it, but we have to talk about data, getting data fixed across health care.” We don't have the same clout, I imagine, in university funding because of the way that is set up.

    On the record, I can see the nodding of heads. We'll try to trap that in the analysts' work.

    Thank you, everybody. We are at time.

    Thank you to Dr. Smith and Dr. Sukhai for the terrific discussion we've had with you. Your testimonies are really going to help us with our study on the pay gap experienced by different genders and equity-seeking groups. If there is more information that you can provide us from today's discussion or things that you think of later, please send those to the clerk.

     We are going to be suspending briefly now so we can get our next panel set up. For the members on Zoom, Mr. Lametti and Mrs. Goodridge, please stay in the session that you're in, and we will come back to you shortly.

    Welcome back.

    Pursuant to standing order 108(3)(i) and the motion adopted by the committee on Monday, December 5, 2022, the committee resumes its study on the long-term impacts of pay gaps experienced by different genders and equity-seeking groups among faculty at Canadian universities.

    Now it's my pleasure to welcome Statistics Canada. We have Vincent Dale, director general of the labour market, education and socio-economic well-being statistics. We also have Tracey Leesti, director of Canadian centre for education statistics. Both are on video conference.

    Welcome to you both.

     We do have some warnings about microphones, but I think that, when you have your headsets on, the microphone and the earpiece are far enough apart that the interpreters can safely do their work.

    We will start with five minutes for opening remarks for one of you. Whoever is going to be doing the presentation, you have five minutes.

    Go ahead, Mr. Dale or Ms. Leesti.

     Good afternoon.

    Thank you, Mr. Chair and committee members, for the invitation to today's meeting to discuss gender pay gaps for academic staff at Canadian universities.

    In 2021, among all full-time academic staff, the median salary for women was roughly $134,000, while it was $151,000 for men. That's a pay gap of 11.1%. This gap has decreased over time. In 1991, it was 20.6%.

    Rank is an important factor to consider when examining the pay gap among academics. Over time, the pay gap has decreased for full professors and associate professors, while it has increased slightly among assistant professors. In 2021, among full professors, men earned 3.3% more than women, compared to 5.9% in 1991. For associate professors, the difference between men and women was 2.3%, compared to 4.8% three decades earlier. The pay gap, although smaller for assistant professors, has increased slightly over the last 30 years, from 2.2% in 1991 to 2.4% in 2021.

    We also see differences in the pay gap across teaching disciplines. In 2021, for example, among full professors, women earned slightly more than men in fields such as humanities and health professions and related programs. In most other disciplines, men earned more than women. In business management and public administration, for example, the median salary of men was about $13,300, or 7% higher than that of women.

    We know that the age structure of academia has an impact on the gender pay gap. Fifty years ago, only 1% of full-time academic staff were aged 65 years and over. In 2021, this figure was roughly one in 10. This reflects in part the aging of the baby boom generation, as well as the end of mandatory retirement legislation in many provinces. Men are overrepresented in the older age groups, and they are overrepresented among full professors, whose wages are generally highest. This helps explain the overall gender pay gap.

    Let me turn now to some steps we're taking to understand the gender pay gap of academics more fully.

    Statistics Canada collects data on academic staff through a survey called the university and college academic staff system or UCASS. This survey involves receiving and compiling information from the administrative systems of educational institutions across the country. Currently, information is collected on gender, year of birth, principal subject taught, academic rank, years at rank and salary. UCASS does not include information on racialized groups, indigenous identity or disability status, and does it not collect information on part-time academic staff.

    We recognize the importance of gathering more detailed information on equity-seeking groups, as statistical findings for the total population can often hide differences in the experiences of diverse groups. To this end, Statistics Canada is currently assessing the feasibility of enhancing the information included in UCASS. This project has three components.

    First, we are evaluating whether information on equity-seeking groups is already held by institutions and the extent to which these data are standardized and comparable across institutions. Secondly, we are assessing whether it would be possible to fill information gaps through the integration of UCASS data with other data already held by Statistics Canada. Third, we are considering what would be involved in Statistics Canada acquiring information on equity-seeking groups from institutions, including important privacy and confidentiality considerations.

    This project will be completed in March 2024, and decisions on next steps will be taken at that point.

    Mr. Chair, this concludes my opening statement. We would now be happy to answer your questions.

    Terrific. Thank you very much.

    Now we will go to the first round of six minutes with Mr. Tochor, please.

    Thank you, Chair.

    Thank you to our witnesses today.

     Mr. Dale, previous witnesses noted that, although Statistics Canada tracks some information needed by researchers on the subject, it charges them for that. Are you aware of whether the amounts of monies collected from researchers, accessing these dollars, cover the cost of the actual research?

    Would you mind repeating the first part of your question?

    We charge researchers to access this information. I want to know whether it covers the cost of the collection of that data.

     No, it does not.

    We are collecting some of the monies to pay for this data collection. Is half of the cost being offset by researchers?

    I can help you to understanding how our costs work. Maybe I'll begin at the end.

    Once we have collected information and it's ready for analysis, tabulation or writing reports, for example, there are different options within Stats Canada to access that data. Typically, a large proportion of the data would be available free and easily through the StatsCan website. There are some more advanced uses of the data that involve additional costs to Stats Canada, and we do recover those costs.

    For example, we have what we call research data centres, where a researcher may spend weeks or months doing a more detailed examination of the data for a very in-depth research project. We do recover the cost associated with maintaining that infrastructure. That's quite separate from the cost of collecting the data in the first place.

    We don't charge to acquire data. To fully shed light on the situation, that's not to say those who share data with us may incur some cost in sharing that information with us.

    I hope that responds to your question, but it's certainly not the case that we charge to receive data.

    To receive data....

    Changing gears a little, in your presentation today you had the 30-year difference between those percentage gaps. Do you have what they were 20 years ago, or 10 years ago, versus today?

    We do. I don't have them at hand. I would be happy to supply that.

    Could you please supply that as well?

    There is data collection in the millions, if not hundreds of thousands, of individuals. When we look at post-secondary institutions and the actual pool of people you would be collecting statistics on, wouldn't it be more efficient for the actual facilities to be able to know what they're paying their individual people versus an outside source trying to collect that?

    That's the way that UCASS works. We're essentially acquiring information that's already in the administrative systems of the institutions.

    As you say, institutions are in the position to know exactly the situation, including the payouts of individual academics. They transfer that information to us. We compile that, and through that compilation of the data from each individual institution, we're able to build a national dataset that covers the entire country and allows comparisons across different groups.

    Would the universities be sharing personal information, such as names or characteristics of that individual with Stats Canada?

    They don't currently share name information. That's one of the things we are looking at as an efficient way of filling these information gaps that I referred to. If we were able to, for example, gather the name associated with each piece of information we already have, we would then be able to link that to existing data sources, such as the census of population. By doing that, it might be an efficient and expedient way of filling that information gap that we've heard about.

     On that alone, is there an ethical dilemma that you might be faced with in finding out some of that information?

    There are definitely privacy and confidentiality considerations that we have to think about during the process of acquiring the data from institutions. There's a series of internal policies that we have, as well as legislation under which we're authorized to work, that are very much focused on those privacy and confidentiality protections. It's in the process of acquiring the data but also, once it's in the door of Stats Canada, in the way we store and treat that data.

    Super. Thank you.

    The echo loop we had was actually in the room. When the members' mikes are left on, they pick up the sound we're hearing twice, so I think we have that problem licked now.

    Now we'll go over to Mr. Lametti for six minutes, please.

    Thanks, Mr. Chair.

    Thank you, Mr. Dale and Ms. Leesti.

    I guess this is for either one of you: How far away are we from being able to obtain the standardized data for equity-seeking groups that you mentioned in your remarks?

    As I said, we're conducting a feasibility study at the moment, working with seven institutions and working through that question of whether they already have the information and some of the privacy and confidentiality considerations. I'm not able to give you a direct answer to your question. That feasibility study will conclude early next year, and we'll evaluate which way forward we would like to go and what funding mechanisms might be in place to pursue the preferred option. At that point, we would begin to formulate some more precise timelines.

    Thank you.

    Certainly, you're getting data from universities, and you're collating it and coordinating it. I presume that you're also going back and forth with universities on trying to standardize the way in which that data is collected and organized even before it gets into your hands. We've heard from universities that they would like you to standardize even more. How can you pursue that goal as well?

    As I think you heard from previous witnesses, the question of data standardization is an important one. It's an area where we do have some expertise and where we would like to think we have some skill and expertise in working with individual institutions to encourage the adoption of common standards. That's one of the key questions that we're evaluating through this feasibility study: the extent to which additional standardization is required and how we might support institutions in doing that.

    My last question is a bit out of left field: Is there a way to get data from places like the United States? One of the things that I experienced as a tenured full professor in a law faculty that was trying to work hard at pay equity gaps of all kinds was that—and your statistics seem to demonstrate this—at the entry level it's closer. When you get to full professor.... The things that messed up in our faculty's case—a non-unionized law faculty—were offers from, in particular, the United States or other provinces. They generally went to high-ranking senior men. Sometimes they left, but sometimes they stayed. Then there would be a retention offer, which then completely messed up the pay scales.

    Is there any way to get that kind of data?

    It's an issue that we're very aware of. Those increases are reflected in the salaries that we see in our data, but unfortunately, we haven't yet arrived at a method to isolate the specific effects of those person-level negotiations that we know happen.

    Presumably, you would even be able to track the faculties, so law and business faculties and certain engineering faculties would probably be more prone to this.

    You know, the other thing I might say is that, when trying to understand an issue or a policy concern, I would encourage you to, maybe, think of multiple sources of data. The UCASS would give you good benchmark information and the ability to compare across jurisdictions and across time, but regardless of the issue, you would want to supplement that with additional information, additional research. In that case, it might be quite appropriate to refer to international sources or to various types of research to better understand the environment.

    Let me ask you a 30,000-foot question. For either one of you, based on the data you're getting, the kinds of inputs you're getting and the kinds of programs you know are out there that you are evaluating with the data, what is working? What kinds of measures are the kinds of measures that work?

    Would you mind elaborating? Could you just extend your last sentence? They are working in what sense...?

    They are successfully working at eliminating gender gaps, for example, or other kinds of pay equity gaps as opposed to what's not working, although you may want to go there.

    It's beyond my scope of expertise and authority to comment on policy questions. I can speak to what works in terms of data standardization, acquiring data and the development of data, but I'm not authorized to speak about what works in terms of policy interventions.

    Okay, that's fine.

    I'll just finish by asking if you feel that your resources are adequate to do the task that you have been tasked to do.

    As I said, we're in this feasibility stage. Early next year we'll make some decisions on which way we're going forward.

    Depending on which way we're going, the cost implications could be quite different. I mentioned the possibility of linking to existing census data. That might be a very different proposition from a full-scale data acquisition. To give you an example, it might be the case that, to supply some variables, a large number of institutions will have to make large, significant changes to their IT systems. That could be a significant cost, depending on the way we go.

    It is important that we finish our feasibility work and decide which way we are going. That will give us a sense of the cost.

    Thank you very much.

    Now, for six minutes, we have Mr. Blanchette-Joncas.

    Thank you, Mr. Chair.

    Greetings to the witnesses who are joining us.

    My first questions are for Ms. Leesti from Statistics Canada.

    Various witnesses have suggested expanding the survey for Statistics Canada's university and college academic staff system. For instance, they suggested including information about race, gender identify, disability and indigenous status for full-time and part-time staff.

    Can you tell us which reports and analyses conducted by Statistics Canada on the basis of the university and college academic staff system would be relevant for this study?

     I would first say that UCASS does provide a very rich data source on the analysis of gender pay gaps, but we do recognize that there are variables that we are missing from UCASS with respect to pay equity on racialized populations, indigenous identity and persons with disabilities, so I do believe collecting this information and having a centralized repository of this information across Canada would help in terms of furthering the analysis.

    Currently there are a number of areas across Canada, be they in institutions or with funding agencies, that collect this information, but there is not one centralized repository. I do feel that having that information centralized and available would be very beneficial in furthering the studies, particularly the intersectional studies with respect to pay gaps.

    Thank you, Ms. Leesti.

    Should the committee consider other measures as part of the survey for the university and college academic staff system, including potential changes to the survey itself, its frequency, data analysis or its management?

    In terms of the analysis of the data, there is quite an extensive amount that appears to be going on within other organizations.

    In terms of furthering the collection of the data with respect to UCASS, as you can imagine, it's quite an extensive process to collect this information, particularly across the multiple institutions—over 100 institutions—where the data is collected. Funding moving forward will be a question with respect to the collection of the data. It's a large-scale operation, so in terms of the future of UCASS, should the pilot prove to be successful, that is one thing in terms of moving the yardsticks forward on the collection of this type of information through UCASS.

    Thank you very much.

    Mr. Dale, do you have something to add on the last two points I raised?

     No. I think Ms. Leesti covered it very well.

    We have heard very loud and clear that this information on equity-seeking groups is a priority. That's why we are currently conducting this feasibility study. We believe there will be a very high value to enhancing the data with that additional information.

    Perhaps I'll leave it there.

    Thank you very much.

    As a number of my colleagues noted, various witnesses who have appeared before the committee as part of this study have indeed noted that Statistics Canada collects certain census data, but that there is a fee to access it.

    What measures could the federal government take overall to improve the collection and analysis of pay equity data for universities?

     I'll repeat some of what I said before.

    There are some more advanced uses of data, which require additional physical and IT infrastructure. For that type of work, we do recover our costs, so for advanced researchers, there can be some costs associated with that.

    I've forgotten—

    No problem, Mr. Dale, I have other questions. I have a lot of questions.

    In its 2021 budget, the federal government earmarked $172 million over five years for the implementation of the disaggregated data action plan, whose objective was to support the efforts of the government and society to limit inequalities and include considerations relating to equity and inclusion in decision-making processes.

    I would like you to explain how the disaggregated data action plan can help researchers and decision-makers reduce wage gaps in specific fields, including university faculty members.

    I'll introduce the idea that data is a team sport. There are certain activities that StatsCan can certainly take a leadership role in doing. As we tried to outline, and when we talked about a feasibility study, it's really about building co-operation around that common data strategy. What does that mean? It means agreeing on one common approach to filling these information gaps and then committing to a coordinated effort to collect, share, compile and analyze that information. If I were to make any suggestion or recommendation, it would be to mobilize around a coherent and coordinated strategy.

    Great. Thank you.

    Sometimes the recommendations are writing themselves, or you write them for us. I appreciate that.

    We'll go over to Mr. Cannings now.

    Thank you.

    I'll just continue on that line of coherent data and data that's the same across the country.

    Statistics Canada is a federal agency. We have institutions like universities and colleges that collect data, and they're being overseen by provinces that perhaps are collecting data.

    Can you give us an idea of the scope of that difference? Are we dealing with differences between different universities and colleges versus Statistics Canada, or do the provinces have different datasets that need to be standardized as well across provincial boundaries? How difficult is this?

    It would be hard to summarize the difficulties in a few words.

    One thing I can maybe help to clarify is that our interactions are with each individual educational institution. What is certainly part of the challenge or part of the context is provincial privacy legislation. For each institution and the applicable province, there are some challenges that should not be underestimated in terms of making sure that, depending on the way this EDI information was collected, the institution and the province have the appropriate legal authority to transfer that to Statistics Canada.

    Maybe that gives you a sense of the interaction between individual institutions and provinces and the acquisition process.

     You mentioned that it would be useful for you to have that name data associated with some of the statistics you have for each position at universities and colleges, and that the name data could then link to census data.

     Would it also link to CRA data? I'm just wondering about the extent of this privacy issue. Is it a social insurance number that would link all those? How would you do that?

    It may be the case that we come to the conclusion that acquiring name information is the best way forward. We're not at that point yet. When we do make those decisions, we are always evaluating the magnitude or the urgency of the information requirement, the data needs, versus the privacy intrusion that would go along with collecting that information. We call that necessity and proportionality.

    We strive for a balance so that the need to acquire the data is proportional to the privacy intrusion that's involved.

    As I say, it might be that we make that determination around linking to the census, but we are looking at other options. If we do decide to go down the road of acquiring first names and last names, we would certainly do that within the framework of our legislation and our privacy and confidentiality policies.

    Just to finish up on that thought, then, we've been struggling here with data on racialized people and people with disabilities. Would that name data be there in the census, or is it only there for certain people?

     It's there for a sample of the population—for about one-fifth of a sample of the population. It would be certainly there for indigenous identity and membership in a racialized group or an employment equity group. Disability status would be a further challenge, as it's not necessarily addressed in the census.

    Just to completely shift gears here and get back to your initial.... You gave some summaries of the situation from your data, and I had just a few questions there.

    You said that rank was important. Could you go over that again, because it was a bit confusing for me whether the pay gap was lesser in higher ranks or whether the change in the pay gap was lesser or coming down. I was left a bit confused.

    Sure. For both full professors and associate professors, the gender pay gap has decreased over the past 30 years. In 2021, for full professors, the gap was 3.3% and for associate professors it was 2.3%.

    The situation is slightly different for assistant professors. Over time the gap has increased slightly from 2.2% in 1991 to 2.4% in 2021.

    Okay, so the higher the rank, the higher the pay gap, but it's coming down, and for assistant professors it's lower but going up a little. Okay, I think I have that clear.

    That's correct, except for assistant professors the gap is small but increasing.

    Okay, I think I'd better leave it there. Thank you very much.

    Great. Thank you.

    We have Mr. Soroka for five minutes, please.

    Thank you, Mr. Chair.

    Thank you to the witnesses for coming today. I'm not certain who can answer this.

    Has your research found any correlation between the rising cost of living exacerbated by inflationary government spending and taxation, and the persistence of pay gaps among faculty at Canadian universities?

    That's not a question that we've looked at, no.

    Don't you have any information regarding regional differences in faculty pay gaps across Canada?

    We do have information on gaps across provinces.

    Maybe, to elaborate, we do have other sources of information such as for example, the labour force survey. One could look at the salaries or the wages by occupation and by industry. One could look, for example, at the rate of wage increase of professors over time in connection with the consumer price index. One would be able to do that using Statistics Canada data at a certain level of detail, but not using this dataset that we're talking about this afternoon.

     Do these regional disparities correspond with variations in the cost of living? Should the federal policies take this into account?

    That's a question that we have not looked at. One could construct a research project around that question, but to date we have not done that.

    Do you do a comparative analysis of cost of living data and the pay gap data?

    We could do that. I'm not aware that Statistics Canada has done exactly that analysis to this point.

    Do they collect cost of living data, though?

    Statistics Canada collects that information. For various levels of geography, we know the rate of increase of the consumer price index, yes. For example, we can look at that at the province level and ask ourselves how the increase in the cost of living across provinces compares to changes in the pay gap of academics across provinces. One could compare and contrast those two patterns.

    With this rising cost of living affecting Canadians, do faculty pay gaps exacerbate financial hardships within the academic community? Does the price of everything lead to the brain drain, where skilled faculty seek opportunities outside of Canada? Have you done any research on that?

    I'm not aware of any research that's been done on that question, but we can certainly follow up with the committee. We can review that question and give you a written response to that question if you would like.

    I was more concerned about.... You know how the cost of everything goes up. Do they leave simply because of that, or is there the brain drain for other reasons? Are there no statistics or information on that?

    There is no recent information that I'm aware of. As I say, I would like to verify that before telling you that it has not been done. I would like to verify that and get back to you in writing, if that's okay.

    Yes, that would be great.

    Do you know if there's a role for the federal government in helping to close these pay gaps among faculty in Canadian universities? Is there any information or data that you have on this?

    I can't speak to the actions the government might take in terms of policy interventions, but I can speak to data development or the enhancement of data. Yes, as we've tried to convey, there is certainly a role for Statistics Canada to play in terms of leading or coalescing around a coordinated data strategy on these questions. We think there's an appetite for that. When our feasibility study is finished early next year, we'll certainly be following up with interested stakeholders to see if we can forge a common strategy around this question.

    Yes, that would be very nice to have, because that's the whole purpose of statistics, to get that information and to make it better for Canadians.

    How much time do I have?

    That's just about it. You have about seven seconds.

    On that line of questioning, when we have inflation rates in different countries, that might be another way of comparing the pay gap in Canada to pay gaps in other counties to see whether there's a correlation. However, I'm the chair. I'm not on the side of the table asking questions. It's just a comment from my side.

    Ms. Bradford, you have five minutes, please.

    Thank you, Mr. Chair.

    Thank you to our panel. We've had some very interesting testimony today. I thank you for that.

    It's clear that not only do we have a wage gap but we have a data gap. It's been indicated that you currently don't collect information specifically on equity-seeking groups or on part-time academic staff. You do recognize the importance of gathering more detailed information on these groups, as big-picture statistics often hide key differences in the experiences of diverse groups.

    Can you talk to us a bit more about how the key differences experienced by these diverse groups are often hidden?

    When I say “hidden”, I mean that in the statistical sense. For example, I spoke about the difference in pay among full professors between men and women being 3.3%, but, for example, that 3.3% might be very different for racialized men versus racialized women or for persons with disabilities. In a statistical sense, it's the idea that what's true at the total level might disguise relevant, important, insightful differences for smaller populations.

     Are there other methods of getting a better understanding of the pay gaps for these diverse groups, such as through the census or other information conducted by Stats Canada, until the time you implement additional information collected through UCASS?

    There is a certain potential to analyze these questions through the census. As you know, the census is done every five years. The benefit of the census is that it can support very detailed research, but you're getting a signal every five years so it's difficult to assess changes over time or changes in response to specific policy interventions.

    There are some limitations involved in that. We think that modernizing UCASS or enhancing UCASS, so that we can get a flow of these data every year for all institutions across the country, is likely to be the preferred option.

    How does the data you collect on the general population compare with the pay gap among academic staff?

    Are you referring to the gender wage gap for the labour force as a whole?

    Yes.

    We do have a series of research articles on that question. It changes over time, obviously. The best thing for us to do might be to answer that question in writing to make sure we give you an accurate answer.

    That would be good.

    How is the data that you collect used? Is there any way you could use it to help support reaching pay equity among academic staff?

    I would be speculating, but I'm sure it's used by administrators. I'm sure it's used by unions and professional associations. It's used, certainly, by equity-seeking groups, and federal and provincial policy-makers. I'm sure it's used in various specific ways. In a general sense, it's used by a very wide range of stakeholders.

    As we've heard through our consultations and engagements with stakeholders, there's a particular interest in understanding the gender wage gap at a more granular or more disaggregated level for equity-seeking groups.

    From a Stats Canada perspective, what can the Government of Canada do to advance data collection analysis related to pay equity within universities?

    As I've said before, we think of data as being a team sport. We are the national statistical agency. We have expertise in a great number of areas. Ultimately, our data collection efforts tend to involve co-operation with partner organizations and strong partnerships.

    The role of Statistics Canada is to consult, engage and build partnerships, so that, as I've said before, we're coalescing around a coordinated data strategy to get this information that we need.

    That's the end of your time, unfortunately.

    Mr. Blanchette-Joncas has his finger up. He's also the next speaker, but I think he has something else.

    Yes, Mr. Chair.

    There seem to be some technical difficulties on the screen, and the people who are following us online see a blue screen.

    They're working on it. We have a problem for those who are on the screen. We have a blue screen for the floor. The floor camera isn't picking us up. I think you can still hear us. We won't watch ourselves, but as long as our witnesses can hear our questions, let's go with two and a half minutes with Mr. Blanchette-Joncas.

    Mr. Chair, I just wanted to point out that people who are following us online, because this is a public meeting, are unable to see the video on the screen. That is the problem we are having.

    So I would request that we suspend temporarily because people cannot see what is happening.

    Let me consult. Give me two seconds.

    It isn't a televised meeting, per se, and we do have audio so people can see and hear what we're talking about. We have five minutes left in the meeting, so by the time we solve this.... I think it's more important for us to get our questions to the witnesses and their answers to us. The public will be able to pick that up in the meeting as well as in the report as we go forward.

    If it's okay for you to enter into your two and a half minutes of questions, that would be great.

    Okay, Mr. Chair, we will continue for the sake of the process.

    Ms. Leesti, I would like to go back to the disaggregated data accomplishments report 2021‑22, which was tabled in April 2023.

    In order to obtain detailed data and eliminate the systemic barriers faced by certain groups in the population, $172 million in funding was allocated over five years, and $36 million annually thereafter. That is a significant amount.

    Despite this funding, various witnesses have mentioned insufficient access to data to conduct analyses, help improve pay equity and reduce the wage gap, especially among genders.

    So I would like you to tell us what exactly is happening with that federal investment because right now, in 2023, it seems that we are still missing a piece of the puzzle.

     Thank you for the question.

    The disaggregated data action plan has been used—and is still being used—to fund multiple initiatives across Statistics Canada, including, for example, the labour force survey and the Canadian community health survey. It is an envelope of funding that is being used to cover a wide portfolio of projects. It has been used to fund the feasibility study I've been talking about, which is, in part, funded through the disaggregated data action plan.

    There is a process within Statistics Canada to allocate that funding. Some of it is being used to assist jurisdictions in sharing administrative data. Some of that activity is leading to lessons learned and best practices, which would certainly be applicable in this case.

    Mr. Dale, has the action plan been analyzed to assess its performance and to determine whether the objectives you set have been met?

    Yes.

    For this particular topic, the data does not yet exist. We are using the funding through the disaggregated data action plan to enhance the way we collect the data and work with jurisdictions and institutions to collect the data. We're not yet in a position to analyze or write a report, per se.

    Thank you very much.

    We go now to Mr. Cannings for the final two and a half minutes.

    Thank you.

    I'd like to stick with Mr. Dale.

    You mentioned that men are overrepresented in the full professor category. Since this is a study about pay gaps, being a full prof versus an associate or assistant prof would have implications. I want to drill down and see whether you have data, perhaps, on why that overrepresentation has occurred.

    Is this just a function of time? These full professors have been in positions in universities for longer. What might have caused that?

    We haven't necessarily looked in detail at your question specifically, but the data certainly supports an analysis of, for example, tenure—how long people have been in their position. We have information on age, for example. That's what allows us to know a larger number of professors aged 65 and older—a larger proportion by far—are men.

    We're able to look at patterns and trends. I can't necessarily speculate as to what's.... For example, I can't speculate as to why it was that, 20 years ago, more men were becoming full professors than women. That's reflected in the data today, but I can't speak to the causes of those hiring decisions.

    Does this imply there isn't that overrepresentation in assistant and associate professors?

    For younger groups and for assistant professors, in terms of the composition of faculty, it's true that we don't see as large a gender imbalance in terms of the proportion of academics by gender, ignoring for the moment the levels of pay.

    Yes, we do see for younger generations and lower “ranks” more gender balance than for full professors.

    I was just trying to get at whether this difference in full professors was as a result of earlier differences in assistant and associate professors, or whether it's something about who is chosen to become a full professor. I was trying to get at that.

    Be very brief.

    I think you would want to look at what we call cohort effects. When we look at those who are 65 and older now, they were probably hired 25 or more years ago. You'd probably want to look at the cohort effects. How did those people come to be in those positions?

    That's great. Thank you very much.

    To both witnesses, Vincent Dale and Tracey Leesti, thank you for your testimony and your answers. Sometimes there is a line between policy and the work you're doing, so thank you for keeping on the right side of all of that as well. It will really help our study that we're doing on pay gaps experienced by different genders and equity-seeking groups. If there is more information, you can always submit that to the clerk. That can be included in the analysts' work.

    We'll be meeting again on Wednesday, November 1. We'll be considering draft reports for version two of support for the commercialization of IP. We're going to have version two of the Government of Canada's graduate scholarship and post-doctoral fellowship programs. We will also provide drafting instructions for the study on the long-term impacts of pay gaps experienced by different genders and equity-seeking groups among the faculty at Canadian universities.

    Is it the will of the committee to adjourn? I see no one objecting.

     Thank you very much for your participation. We are adjourned.