Standardized academic English is now understood to be rooted in histories and practices that are colonial, classist, nationalist, heteronormative, ableist, and sexist. Current teaching of academic English carries an ethos of making practices of research writing accessible to students from marginalized backgrounds through explicit attention to language patterns and genre structures. In the context of both ideological critique and explicit pedagogy, I discuss three pragmatic elements of research writing—positionality, citation, and evaluation—with examples from one of my courses. I present these (...) elements and my approach to teaching them as a practice that is attentive to both details of published scholarship and students’ agency and intentionality in shaping their own writing projects, claims, and arguments. My work is framed by a functional approach to grammar where grammar is not interesting as a standardized apparatus but as a code that provides a range of options for producing performative effects. I call this spacious grammar. (shrink)

We advocate for the inclusion of Indigenous studies within first-year writing and academic English courses, particularly those taught to multilingual, international students. We argue that asking international students to learn about local and international Indigenous issues productively intersects with coursework in academic English. Our pedagogical approach emphasizes metalanguage and allows Indigenous studies and explicit language instruction to work in tandem, thereby recognizing the agency of Indigenous scholars and guiding non-Indigenous students in relation to it.

We assess the state of thinking about gender identities in computer vision through an analysis of how research papers in gender and facial recognition are designed, what claims they make about trans and non-binary people, what values they espouse, and what they describe as ongoing challenges for the field. In our corpus of 50 research papers, the seven papers that consider trans and non-binary identities use questionable assumptions about medicalization as a measure of transness, about gender transition as a linear (...) and bounded process, and about the concept of gender deception. Otherwise, non-normative gender identities are absent and their consideration is in fact hindered by prevailing research values, particularly deeply embedded ones such as performance and accuracy. We point out how the use of shared datasets calcifies binary conceptions of gender. In the way that the field of computer vision conceives of ongoing challenges for its research, it does not yet face questions that trans and non-binary user experiences pose and often falls back on biologically essentialist notions of sex classification. We make two recommendations: that computer vision researchers undertake interdisciplinary work with researchers who study gender as a socio-cultural phenomenon, and that journal editors and conference organizers do the same in peer review and conference acceptance processes. (shrink)