Average wage of tech workers by racial identity and sex, 2016
What is this metric and why is it important?
The technology sector plays an important role in Canada’s innovation economy, and provides interesting innovation opportunities and the potential for good incomes for those it employs. We present here the wages of those working in technology-intensive occupations, dissaggrated by racial identity and sex.
How is Canada doing?
- Women experience a significant wage gap in tech occupations, making $7,300 less a year on average than men. This difference is especially large for Inuit and Japanese women.
- Those in visible minority groups make on average $3,100 less than those not in visible minorities.
- Those with Indigenous identity make on average $6,300 less than those with no Indigenous identity.
- However it is when we start to look closer that we find the real disparity, with Inuit, First Nations, and Black people making by far the least, with a salary gap of $11,000 or more.
In previous work, the Brookfield Institute defined tech occupations as those that involve a high degree of technology development or use. This has the benefit of including occupations in non-tech sectors that are focused on tech development, implementation, and use, but excludes less technology-intensive jobs in technology companies, such as finance and marketing. Nevertheless, to the extent that tech occupations are those at the frontier of technological innovation and implementation, understanding who holds those occupations is essential to understanding inclusive innovation.
For Statistics Canada, racial identity is composed of two distinct dimensions: visible minority and Indigenous identity. Those counted as visible minorities are “persons, other than Aboriginal peoples, who are non-Caucasian in race or non-white in colour." Those considered visible minorities are then broken into further categories. It should be noted that by "sex", Statistics Canada refers to biological sex and not gender.
The aggregation of different groups into the category of “not a visible minority” makes certain comparisons difficult. Additionally, the lack of a distinct category for those who identify as “White” or “Caucasian” impairs analysis.