This Research Brief discusses transformers—the core engine for most artificial intelligence applications. The brief situates transformer technology within the field of rhetoric and composition by surveying recent studies; highlights the innovative aspects of transformers; and, finally, thinks through (Majdik and Graham) the operations of transformers and generative AI through Miller’s theory of topoi, illustrating one way in which rhetoric and composition scholars and teachers can critically engage with generative AI in instruction and research.

OpenAI's ChatGPT is a large language model (LLM) that excels at generating text and public controversy. Upon its release, many marveled at its ability to author intelligible and generically responsible texts (Herman). Writing about his students' experiences using artificial intelligence (AI) writing assistants, S. Scott Graham remarks that the results were "consistently mediocre—and usually quite obvious in their fabrication." Why might this be true? How can an LLM succeed in some respects and fail in others? We argue that the discrepant reactions to human and AI rhetoric are a question of genre, specifically that AI rhetoric is only generic; AI rhetoric represents a new enactment of "writing degree zero" (Barthes) that is disengaged from immediate rhetorical situations and knowledge bases. AI text generators (currently) have a more difficult time simulating the positioned perspectives that human writers bring to situations and communicate to audiences through their genre usage. Drawing on the work of Bakhtin, we treat this problem as a question of generic form and audience addressivity. We describe the interplay of form and addressivity as genre signaling and offer it as a construct for the analysis of AI rhetoric and genre as a cultural form (Miller). Genre signaling (Hart-Davidson and Omizo) describes a feature of communicative behavior as it occurs over time that can help both humans and machines evaluate written discourse as it exhibits certain stabilized formal features. When texts contain specific genre signals at expected frequencies and intensities, it may be recognized as being generally accurate, reliable, trustworthy. Without these signals, a text with a similar topical focus might fail to be taken as credible or useful. In this essay we propose to quantify genre signaling based on three measures: (1) stability, (2) frequency, and (3) periodicity.

The Rhetoric of Participation: Interrogating Commonplaces In and Beyond the Classroom , memorializes and extends the research and legacy of Dr. Genevieve Critel. Critel’s research—and her legacy as a scholar, educator, and colleague—form the foundations for this collection. This collection presents the perspectives of twenty scholars and educators in the fields of rhetoric and composition, all of whom engage with the question, what does it mean to participate?

This article proposes novel methods for computational rhetorical analysis to analyze the use of citations in a corpus of academic texts. Guided by rhetorical genre theory, our analysis converts texts to graph-theoretic graphs in an attempt to isolate and amplify the predicted patterns of recurring moves that are associated with stable genres of academic writing. We find that our computational method shows promise for reliably detecting and classifying citation moves similar to the results achieved by qualitative researchers coding by hand as done by Karatsolis (this issue). Further, using pairwise comparisons between advisor and advisee texts, valuable applications emerge for automated computational analysis as formative feedback in a mentoring situation.

How do we as scholars of rhetoric, composition, and digital mediadodigital media theory? How do we develop these theories and put them into action in digital media?