This article examines how students use and perceive digital writing tools, including chat platforms and generative AI, within academic writing environments. It describes a qualitative study of 15 undergraduate students in guided focus group discussions. In a grounded theory analysis of focus group transcripts, the researchers explored undergraduates’ sense of copresence—their perception of support through both human interaction with both peers and instructors and AI technologies during their writing processes. Findings reveal that students’ trust in both peer feedback and AI assistance plays a crucial role in their writing, shaping their decisions about which tools to use and how they integrate human and AI feedback in the development and revisions of their writing. The study sheds light on students’ nuanced understanding of the affordances and limitations of multimodal chat platforms and generative AI technologies. We conclude by highlighting the need for pedagogical practices that support students’ choice of tools when collaborating in digital spaces. We suggest future research directions that will enable us to better understand how copresence and trust influence students’ writing in these contexts.

This article uses the example of nootropics—a flexible term that capitalizes on the flexibility of the brain—as a category to describe how seemingly oppositional tropes, or turns, can occupy the same rhetorical topos, or space, and produce distinct ethos, political identity, and commitment within that space. It considers two dialectical, gendered tropes in nootropic discourse. The tropes are a falsely binary and highly problematic set of subjectivities, a Gothic masculine and an ostensible Gothic feminine. These two tropes exemplify how rhetorics of wellness produce identities whose turnings towards a politics does not map cleanly onto electoral politics or even identity politics in the US and Canada.

Protein folding is an important area of research in bioinformatics and molecular biology. The process and product of protein folding concerns how proteins achieve their functional state. A particularly difficult area of protein folding is protein structure prediction. There are many possible ways a protein can fold, and this makes prediction difficult, even with the aid of computational approaches. Protein folding prediction requires significant human attention. Foldit, an online science game, provides an innovative approach to the problem by enlisting human beings to solve puzzles that correlate with protein folding possibilities. Such work aligns broadly with emerging trends in citizen science, where non-experts are enlisted for productive alliances. We examine Foldit, commonly looked at as a dynamic community, and suggest such communities actually have potential to be relatively static and to reproduce and maintain a set of power relations. We make this argument by combining perspectives from Rhetorical Genre Studies and Actor-Network Theory.