The most recent paper based on research with Tara Mahoney of Gen Why Media (and currently a research fellow at the David Suzuki Foundation) has just come out.
The paper, Expectation and anticipation: research assemblages for elections, was published in Continuum: Journal of Media & Cultural Studies as part of a special issue on emotions, political work, and participatory media and edited by Sudha Rajagopalan and Krisztina Lajosi at the University of Amsterdam. The material for the paper was based on research for Publics: Art-Making Inspired by the Federal Election by Tara, Frederik Lesage and Peter Zuurbier during the 2015 Canadian Federal election. The specific goal of this paper is to show how alternative research assemblages can channel the anticipation generated by participatory politics to yield more diverse and critical forms of participation in the lead up to elections.
An earlier paper, Investigating politics through artistic practices: Affect resonance of creative publics, was published in 2019 in the European Journal of Cultural Studies. Both papers draw in part on theoretical and methodological experiments developed in a 2016 book written by Peter Zuurbier and Frederik Lesage titled Masamune’s Blade: A Proposition for Dialectic Affect Research in which the authors explored how to study affect using a combination of critical theory and cultural probes methodologies adapted from design research.
Skills and skills training remain, without a doubt, some of the big key words for any policy discussion concerning the future of work.
While compiling some literature for our Mitacs-funded investigation into digital skills I started to come across a lot of interesting pieces on how digital platforms are developing their own taxonomies for modeling skills.
In response to the economic crisis of 2008 and the Obama administration’s response to the crisis, LinkedIn CEO Jeff Weiner laid out a vision of an “economic graph”:
“Most of us are by now familiar with the value generated by the social graph concept popularized by Facebook, the professional graph developed by LinkedIn (LNKD), and the interest graph implicitly manifested by Twitter. What if we were able to extend that thinking to the economy itself and developed an economic graph?
Imagine a world in which every job opportunity, full-time and temporary, was digitally searchable and linked to the appropriate company and skills required to obtain the position. Now imagine if the 153 million people in the U.S. workforce -- or 3.3 billion people in the global workforce -- had a digital profile, highlighting their experiences, skills and, most importantly, their ambitions.” (Weiner, 2011)
This vision has arguably guided much of the platform’s evolution since including the billion-dollar acquisition of Lynda.com (now LinkedIn Learning) in 2016. More recently, researchers affiliated with LinkedIn have started to refer to the “skills genome”:
“LinkedIn’s skills genome analysis can track the skills composition of clusters of roles, industries, cities and regions for the purposes of comparing historical trends and contrasting skills profiles. Such measures can therefore provide the tools to identify reskilling and upskilling priorities across industries. The metric can be expanded to match emerging jobs to populations with the right skillsets to fill those new roles such as migrant populations or women. It can also be expanded to understand entry into the labour market for new entrants to professions and industries today and in the recent past.” (p.17) [Data Science in the New Economy: A new race for talent in the Fourth Industrial Revolution]
Lu, Jian. (2019, July 10). Skills, not job titles, are the new metric for the labour market. Economic Graph.
In parallel to LinkedIn, the online education platform Coursera has called its Skills Graph. In a Medium article from 2018 Emily Glassberg Sands, Coursera’s head of data science, described it as:
“a series of algorithms connecting learners, content, and careers through a common skills currency. At its essence, the graph maps a robust library of skills to each other, to the content that teaches them, to the careers that require them, and to the learners who have or want them. It’s built on data from across the site and powers a range of applications in content discovery and beyond.” [Sands, 2018]
Adams, S. (2013). Everything You Need To Know About LinkedIn Endorsements. Forbes. Retrieved May 25, 2020, from https://www.forbes.com/sites/susanadams/2013/12/24/everything-you-need-to-know-about-linkedin-endorsements-2/
LinkedIn Economic Graph: https://www.linkedin.com/showcase/linkedin-economic-graph/
LinkedIn Buys Careerify To Build Out Its Big Data Recruitment Business | TechCrunch. (n.d.). Retrieved May 25, 2020, from https://techcrunch.com/2015/03/16/linkedin-buys-carreerify-to-build-out-its-recruitment-business/
LinkedIn Economic Graph Research: Helping New Yorkers Connect With The Jobs Of Tomorrow [INFOGRAPHIC]. (n.d.). Retrieved May 25, 2020, from http://blog.linkedin.com/2015/02/12/linkedin-economic-graph-research-helping-new-yorkers-connect-with-the-jobs-of-tomorrow-infographic/
LinkedIn to Acquire lynda.com. (n.d.). LinkedIn Newsroom. Retrieved December 5, 2016, from https://press.linkedin.com/site-resources/news-releases/2015/linkedin-to-acquire-lyndacom
LinkedIn. (07:40:54 UTC). LinkedIn Economic Graph Research: New York City [Data & Analytics]. https://www.slideshare.net/linkedin/economic-graph-research-new-york-city?
Thoppil, D. A. (2014, June 25). Where Is the Top City to Spot Tech Talent? WSJ. https://blogs.wsj.com/digits/2014/06/24/where-is-the-top-city-to-spot-tech-talent/
Weber, L. (2014, December 8). Oh, the Places You’ll Go! (Or Not.). WSJ. https://blogs.wsj.com/atwork/2014/12/08/how-to-predict-your-next-job/
Weinberger, M. (n.d.). LinkedIn is making its endorsements feature a lot smarter to help people find jobs. Business Insider. Retrieved May 25, 2020, from https://www.businessinsider.com/linkedin-upgrades-skill-endorsements-2016-10
Alex (2020, May 30). Skill Development Dashboards Product Guide. Coursera for Business. Retrieved June 8, 2020, from http://business.coursera.help/hc/en-us/articles/360037329514
Coursera. (2018, August 7). Coursera for Business Launches AI-powered Skills Benchmarking Tool. Coursera Blog. https://blog.coursera.org/coursera-for-business-launches-ai-powered-skills-benchmarking-tool/
Coursera. (2019). Global Skills Index (GSI) (v1.1; p. 48). Coursera. https://www.coursera.org/gsi
Thanks to a Teaching and Learning Development Grant (TLDG) awarded in the Spring term of 2018 (click here for project summary), our team set out to improve a third-year undergraduate course titled CMNS 354 Social and Communication Issues in Design that was regularly taught by Dr. Frederik Lesage in the School of Communication.
Our initial objective was to redesign the course to provide students with custom learning support for software skills to help them complete their assignments. We started with a working hypothesis that ‘just-in-time’ models might improve the scaffolding that enabled students to choose how to learn software relevant to their needs by giving them access to custom resources when needed. We collaborated with Riipen.com and LinkedIn Learning to develop an innovative course design based on a “learning-by-doing” approach. (Click here to view slides from a presentation at BCNET 2019 about the collaboration.) Over the course of the six research activities spanning 5 months however, the team realised that we were in fact trying to understand an emerging digital ‘hidden curriculum’ in university student life. This research report is an account of our investigation, completed on July 5th 2019, in which we highlight some of our findings and point to future research.