The Globe and Mail newspaper is currently running a series of articles titled Power Gap: a data-based investigation into gender inequality in Canadian workplaces. I’m really pleased to see attention and resources being directed towards understanding this issue. To date, the articles are doing a very good job of unpicking why there are more men than women in positions of power in Canadian workplaces, and why men are generally better-paid. But the series also shows how difficult it is to address these imbalances in a substantive way, because of data limitations. It’s hard to solve a problem without fully understanding what’s causing the problem.
The complete explanation of the Power Gap project methodology is paywalled, but to summarize it, the analysis relies on data from “sunshine lists” – lists of public sector employees with an annual salary above a certain level, which most Canadian provincial governments release every year. Because these lists are not consistently formatted across provinces – for example, not all provinces release employees’ full names – the data on the lists had to be combined and then adjusted so the data were comparable.
Also, since the purpose of the Power Gap project was to investigate gender inequality, the employees’ gender had to be added to the data set. Gender data were collected through several different methods, including verifying gender through information from other online sources, and commissioning Statistics Canada to review names and estimate the probability that a specific name was associated with a specific gender. These additional steps identified the gender of the “vast majority” of employees in the data set. The Globe and Mail researchers were also interested in investigating gender differences within specific workplaces, not just general trends or patterns, so data were also added to identify the employer of each employee in the data set.
In any research project, researchers can take different paths to investigate the same research question. And because no research project has unlimited time or money, researchers almost always have to make choices about what they can do with what they have to get the best results. The Globe and Mail’s research team acknowledges, quite rightly, that “sunshine lists” aren’t a full representation of what’s going on in Canadian workplaces. The lists only include public sector employers, and only include employees in specific, higher pay grades. But combining and refining “sunshine list” data so that the data can be compared and analyzed is a reasonable approach for this particular issue, and it’s always important to acknowledge the limitations of any data set.
It also needs to be acknowledged that pay differences between men and women are caused by many different factors, including individual workers’ qualifications, job performance, and experience. Gender-based pay differences have been the subject of a lot of previous research, and there are no definitive findings other than that many variables affect these differences. The challenge lies in identifying which variables are relevant in specific situations, and identifying exactly how each of those variables affects the differences.
Hopefully Canadian society is past the time when employers would explicitly pay women less just because women’s work was considered less valuable than men’s. But many factors affecting pay rates are indirectly attributable to gender – for example, women being primarily responsible for household duties and child care, which can limit their access to educational opportunities and affect their employment patterns across time. So while it’s not accurate to blame every pay difference between men and women solely on sexism, it’s also not accurate to say that gender has nothing to do with those differences.
The Globe and Mail has also divided its data into four categories of public sector employers – provincial governments, municipalities, universities, and publicly owned corporations – and has an interactive tool on its website where you can look at comparative data within each category. Another innovative feature of this series is that each organization included in the data set was contacted for a statement about the gender balance, or lack thereof, in its workplace. As you might imagine, a lot of the responses are buzzword bingo about not tolerating discrimination and respecting equality, or performativity along the lines of “look at all our high-ranking women!” – even when the data for the organization show significant differences between male and female workers’ status and pay. Nevertheless I appreciate that the Globe and Mail gave these organizations the opportunity to respond.
So if this were an ideal world, and if I had unlimited research funding and time to follow up on “Power Gap”, what would I do?
- Compare gender representations and salaries in positions that aren’t included in “sunshine lists”. This could be done for some occupations or workplaces by using data from other data sets, such as the Canadian Union of Public Employees’ data set on contract (non-permanent) faculty at Canadian universities. This dataset don’t include salaries, but they could be cross-referenced with information on university websites to identify gender and ethnic representation within institutions and within academic disciplines or departments.
- Look more closely at gender representation within specific jobs or positions, rather than within categories such as “vice-president” or “dean”. It’s no secret that in many large organizations, female executives are more likely to be found in areas such as human resource management; in universities, there are more male deans than female deans in many programs where there is little or no difference in the numbers of female and male graduates. Looking at, for example, how many men and women in the C-suite hold specific positions like VP of Human Resources or VP Finance could be very enlightening.
- Track gender representation across time. This might sound like a daunting task, but if an organization’s website is regularly archived in the Wayback Machine, it would be relatively straightforward to look at employee or executive directories and see if gender representation changes across years or decades. This type of investigation could help determine if it’s true that women hire more women, or whether women in top positions are regarded as tokens and don’t inspire more diverse hiring.
There’s a bigger issue at play in all of this too, and it’s one that would be hugely difficult to investigate without extensive and expensive long-term research. But it’s an important question: namely, does more equitable gender representation result in a more equitable and inclusive workplace? Or do women (or members of any other underrepresented demographic group) “get along by going along” and continue the norm of discriminatory behaviour and attitudes? It’s sexist to say that women should be paid less than men, but it’s also sexist to assume that putting women into high-paying positions or executive positions is automatically going to make the workplace better.
These are complicated and wide-ranging problems, none of which are going to be solved by a single set of newspaper articles. Nevertheless, I’m glad that the Globe and Mail is addressing these problems in a serious and thoughtful way, and I hope that Power Gap inspires support and interest for more of these types of investigations.