We begin by comparing male and female employment across three classifications of information and communication technology occupations (Figure 1): a 15-category list of the core ICT occupations defined by Information and Communications Technology Council (ICTC) in 2016, a 25-category measure of ICT occupations updated by the ICTC in 2017, and a broader group of 67 ICT occupations outlined in Mueller, Truong, and Smoke (2018)2. The results of our analyses indicate that even when women have similar ICT skills, they are under-represented in ICT occupations across all three types of classification. As shown in Figure 1, no matter what definition of ICT is used, women are less likely to hold employment in these occupations.3
Figure 1 Representation of women across different definition of ICT occupations
How much of the occupational effect is due to gender differences in full- and part-time employment? We explore the impact of these differences by running models that restrict the sample to individuals who are working full time. We also include models that consider differences in full- and part-time employment in the full sample regression analysis.
The results are very similar: women remain significantly less likely to hold occupations in the ICT sector. We repeat this exercise to look at the chances of being employed across the occupational definitions of ICT. Again, women are less likely to be in the ICT occupations.
How much of an effect does the employment sector have on gender representation? We examine the proportion of men and women in ICT occupations within the wider labour force, controlling for employment in the public or private sector. Figure 2 shows us that in the workforce overall, a greater proportion of women in ICT jobs work in the private sector than in the public sector, though this is also true of men and is likely to be driven by the increased availability of ICT-related jobs in this sector of the labour market.
2 This list is created by combining data from the Occupational Information Network (O*NET), the Standard Occupational Classification (SOC), and the 2011 National Occupational Classification. The O*NET-SOC database is available at www.onetonline.org.
3 In subsequent analyses, we will discuss the gender inequality in ICT occupations using the ICTC’s 25 core digital economy occupations.
Figure 2 Public and private sector men and women working in ICT occupations as a proportion of the labour market as a whole
We therefore need to investigate this trend further by observing the proportions of men and women employed in the public and private sector while limiting our focus to those in ICT occupations. In Figure 3, we see that the proportion of women to men with ICT careers is higher in the public sector than in the private sector. It is likely that a greater emphasis on diversity hiring within the provincial and federal governments is encouraging female involvement.
Figure 3 Female and male representation in ICT occupations by public and private sector
Does the quality of workers’ basic ICT skills influence their likelihood of holding employment in ICT occupations?
As one would expect, in the general population, the chances of being employed in ICT occupations increases with respondents’ skills in ICT. On the other hand, we do not find support for the myth that women’s lack of skills renders them unfit for occupations in the ICT sector. see Kindsiko and Türk, 2016 Summary tables of these regressions are available in Appendix C.
Figure 4 shows differences between men and women in general-purpose technology and problem-solving skills, as measured by problem solving in technology-rich environments (PS-TRE) scores. Our findings do not indicate that women and men do not score significantly differently in basic ICT skills.4 It is therefore surprising that women are less likely to be represented in ICT occupations even when their skills are roughly equal to their male counterparts. These results suggest the existence of a pipeline issue; that is, fewer women may be enrolling in the fields of study that are necessary for ICT careers.
Figure 4 Comparison of PS-TRE scores by gender
Indeed, educational pathways do seem to have some effect on occupational decisions. For example, in the general population, receiving training in the science, technology, engineering, or mathematics (STEM) disciplines increases the propensity to acquire employment in an ICT occupation by as much as 15 percent (see Appendix C). At the same time, women and men who hold degrees in STEM disciplines have similar probabilities of being employed in ICT occupations . Therefore, part of the issue appears to be that women are less likely to pursue these more technical fields of study.
Perhaps systemic factors affect women’s choice to participate in ICT-related fields of study and subsequently to work in ICT occupations. The wider discussion often describes a labour market in which women’s skills are “gendered,”
referring to how tasks are distributed between women and men. This separation of tasks can lead women to receive less specialized or less meaningful work assignments than men.
We explore several different measures of self-reported ICT applications used daily at work. Figure 5 shows the use of these applications in ICT occupations. Our findings indicate that the daily tasks of women in ICT do not differ significantly from those of their male counterparts with respect to either their use of processing software such as Word and Excel or their advanced programming and other computer-related responsibilities. This is surprising, given that we find evidence to suggest divisions of tasks based on sex within the wider population, where women are more likely than men to take on less rigorous assignments. It is therefore even more remarkable that women have lower levels of participation in ICT careers, considering that this sector practises more equitable divisions of labour.
4 Even though the test scores used in the analysis capture only ICT generic and compleimentary skills, these skill sets are foundational skills to for building advanced ICT skills. Thus, it is hard to imagine that persons people with specialist ICT skills would not perform equally well on these “general-purpose” technology and problem-solving skills tests.
Figure 5 Applications used daily at work by women and men working in 25 ICT occupations
The results presented above suggest that as the ICT sector continues to grow, employers may struggle to fulfil labour demands unless a greater proportion of women pursue careers in the field. Female involvement may be affected by two related issues. First, there appears to be a pipeline problem, whereby female participation in the field seems stunted.
Second, continued employment-side barriers may hinder women’s access to and navigation through the field.