Media researcher and publisher Jeff Pooley responds to the European open access initiative, Plan S, outlining the history of the current system of author-paid article processing charges (APCs) and the ways this system perpetuates inequality across the publishing landscape. He proposes an alternative system wherein university libraries shoulder the publishing costs, and describes an economic framework that could make such a solution sustainable for authors, libraries, publishers, and scholarly societies.
How does (and, ultimately, should) the production and distribution of knowledge change under digital conditions? Parameters is intended to showcase wide-ranging, even conflicting perspectives on this issue, amplifying voices of scholars and researchers, teachers and publishers, librarians and archivists, as they reflect on how their work changes—and doesn’t change—even as the modes through which knowledge is collected, shared, analyzed, and interpreted continue to be informed and influenced by computational methods, platforms, and tools.
While the impact of technology on social science research—from online archives to advanced tools for analysis—is undeniable, there remains an imperative for scholarship to, in turn, reflect on and influence the development of new tools, methods, and innovations. In an age of data collection and surveillance, increased inequality as well as racial and ethnic tension, such rapidly shifting social dynamics and their attendant ethical dilemmas require the keen insights from social science to better understand the impact of such challenges as one means of strengthening democratic agency.
Melissa Bica’s contribution to the “Chancing the Storm” series engages crisis informatics—research on “how people use personal information and communication technology, including social media, to respond to disaster…and cope with uncertainty.” Bica draws on her research on the use of Twitter during the 2017 hurricane season as a tool for experts to communicate and for people to evaluate the uncertainty of information about potential risks of major storms. Using a human-centered data science approach, she analyzes, in both quantitative and context-specific ways, conversations on Twitter as they took place in real time—using the example of how people interpret “spaghetti plots” used by meteorologists to represent the degree and location of risk.