Overview
The world of work has been reshaped by digital technologies, and more change is visible on the horizon. The technologies that have fostered increased connectivity among workers have also resulted in technological speedups, as platform-based companies work to minimize labor costs and attain a monopoly in their sector. New types of work have been created while other professions confront the possibility of their jobs being automated. As researchers, how can we study the scale and scope of these and other technologically mediated challenges facing workers in the twenty-first century? How can our work help to foster means of resisting them?
As part of the Data Fluencies Project, the Social Science Research Council is organizing a research development workshop (RDW) on the theme of “Labor and Technology” on July 24–25, 2023, at Simon Fraser University in Vancouver, Canada.
Applications
We particularly encourage applications from early-career (final year of the PhD, visiting or untenured faculty) scholars. We welcome applications from all relevant social science and humanities fields, as well as law and legal studies, computer science, data science, and related fields. The workshop is open to projects with a wide range of intended outputs (journal articles, book chapters, book proposals, long-form reportage, and reports and case studies). The papers proposed by applicants should not yet have been accepted for publication.
Proposals will be evaluated based on (1) relevance to the workshop’s substantive theme, (2) whether they are at a stage of development where feedback from peers will make the most impact, and (3) complementarity with other research topics selected for the workshop.
Methodology
Our RDWs are designed to catalyze and strengthen early-to-mid-stage research. Three weeks before the workshop, participants share in-development work with all participants plus our chair, who is responsible for guiding the discussion. Because participants are expected to read each other’s work in advance of the RDW, authors spend minimal time presenting their work.