More than just “tech”: A policy wonk’s guide to defining Canadian tech workers

More than just “tech”: A policy wonk’s guide to defining Canadian tech workers

A closer look at how our policy researchers crafted the methodology for our latest report on Tech Workers
More than just “tech”: A policy wonk’s guide to defining Canadian tech workers
Viet Vu
Economist
Asher Zafar
Project Lead, Data Science
January 24, 2019
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When was the last time you were told that in order to thrive in the new economy, you must learn how to code? TED talks, visionaries, and tech company recruiting ads paint tech work as something exciting, growing, innovative, and dynamic that offers unmatched promise and opportunity. Yet, getting everyone on the same page about the meaning of the terms “tech” or “tech workers” can be notoriously difficult. While some folks might throw the image of a software start-up in a garage into their definition of tech, others may add engineers working and managing robotic manufacturing into the mix.

Defining tech

In diving into this topic, we first challenged our own understanding of tech. To arrive at our definition, we started with surveying and learning from the best about how they defined a job in tech or a “tech occupation”. The Brookings Institution, the US Bureau of Labour Statistics and Economic Analysis, and academic researchers at Carnegie Mellon University have all met the task of doing exactly this with similar yet unique approaches. We scanned these definitions to inform and contextualize our approach, and reached out to leading researchers such as Mark Muro at the Brookings Institution, and Melissa Pogue at MaRS, to stress test our methodology. With the feedback that we gained we’ve aimed to develop a definition that is rigorous, carefully thought out, and replicable in many contexts.

Our approach

To define tech occupations, we looked at the skill content of each of the 500 occupations in the National Occupational Classifications (NOC) by linking them to the US O*NET database. Ranking occupations according to six tech skills drawn from O*NET, we didn’t choose these skills randomly, we made sure that the skills chosen related directly to technology use or production and  being adept at any one of them would qualify someone to be a tech worker. Next, we chose the 32 most tech intensive occupations. This is an expansion of the methodology used in State of Canada’s Tech Sector, 2016 report combined with ideas from recent Brookings Institution work, along with a few new wrinkles. We went a little further to validate our approach by using principal component and network analysis to see how skills and educational backgrounds, respectively, grouped together across occupations.

Through this process, we learned a couple of things about tech occupations in Canada. Firstly, we learned that one of the selected skills, “Telecommunications”, differed from the other five we identified. Generally, the other five skills tended to show up together across a range of occupations. Telecommunications, however, was unique in that it appeared in a more limited number of occupations, without any of the other skills we used to define tech occupations, suggesting that telecoms occupations are a somewhat distinct category.

Defining two kinds of tech occupations

Secondly, we realized that there were two kinds of tech occupations: those we considered to be “digital jobs” and those we considered to be “high-tech jobs”. Digital jobs are made up of jobs that typically contribute to the development of computer hardware or software solutions (i.e., software developers or technology architects), while high-tech jobs, require advanced technical skills in which computers are used as a means to other ends (i.e., engineers or scientists). As tech industries grow to encompass much of Canada’s economy, the significance of defining these two areas separately grows. New distinctions are needed to account for the new types of jobs and skills that these industries require.

This approach is dynamic — it can be updated over time as the tech intensity of different occupations changes or as new technology skills replace old ones. Further, it allows us to understand the tech sector from the ground up rather than imposing our own notions of what tech is. We encourage others to [build upon and adapt our code and data] for their own uses. Feel free to send us a pull request on GitHub and let us know what you think about our approach and methodology.

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Viet Vu
Economist
Asher Zafar
Project Lead, Data Science
January 24, 2019
Print Page

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