This report looks at the social and emotional skills that construction tradespeople will need to participate in an industry that is becoming increasingly multi-generational and diverse.

This report is based on an analysis of online job postings in the pre-pandemic and pandemic periods. We discuss both changes in total job postings and changes in job postings across geography, occupations, skills, and sectors.

This Issue briefing discusses the impact of current programs for Indigenous learners in science, technology, engineering, and mathematics in post-secondary education. They are one approach to increase Indigenous inclusion in these fields.

This paper contributes to the development of a post-pandemic skills agenda by clarifying broad changes and continuities in the economy and society that could have implications for skills and identifying a set of key themes on which further research is needed to better understand the challenges and opportunities which we face

This document reflects results on a prospective future before a seismic shift occurred. The research we present here is no longer a good indication of what is to come, but a good indication of how things were.

In Learning Together: STEM Outreach Programs for Indigenous Students, we were interested in free STEM programs, not run by the formal education system, that target Indigenous children in Kindergarten to Grade 12. We surveyed these programs across Canada to learn more about how they reach Indigenous youth.

Indigenous Institutes play an essential role in helping Indigenous peoples—Canada’s fastest-growing population—prepare for the labour market. And they bring a distinctly Indigenous lens to higher education.

This paper offers a conceptual framework and preliminary typology of gig work and workers, based on a thorough review and synthesis of the existing research, designed to be tested “in the field” with real gig workers themselves.

This Commentary assesses the likely impact of technological automation on Canada’s labour market and compares these results to past predictions. In fact, they show a lower proportion of employment at high risk of automation (about 22 percent) than most previous estimates.