DH Scholarship from the Viewpoint of Women and Gender Minorities

 ·   4 min read

If you identify as a woman and gender minority working in DH anywhere in the world, you are invited to contribute to a new annotated bibliography of DH scholarship, to be published as part of the proceedings of the “Women and Gender Minorities in DH” conference held at Stanford University, May 29-31, 2019.

Elaine Treharne and Quinn Dombrowski will be co-editing the proceedings of the workshop, which will feature less-formal and more interpersonal writings drawing from the speakers’ presentations: closer in spirit to an essay, blog post, or oral history transcript than a formal research paper.

For the second part of the proceedings, we welcome submissions of 300-600 word annotated bibliography entries for to a piece of scholarship in DH, broadly defined, that you love. We’ve included an example below. All women and gender minorities working in DH worldwide are welcome to contribute, regardless of their position (from undergraduate to emerita), speciality, or employment status. Together, these pieces can provide one perspective of the world of DH scholarship as experienced by women and gender minorities – of the things that matter to us, and why.

Submission deadline is January 31, 2020. Please direct submissions and questions to Quinn Dombrowski (qad@stanford.edu).

Example: Miriam Posner’s “Data Troubles” talk, by Quinn Dombrowski

Miriam Posner is one of my favorite people in virtual and physical spaces alike. Whenever I see her asking questions or talking about data on Twitter, I start saving tweet URLs to ravenously follow the threads until they run out, and reference in future presentations. Miriam’s insight into what “data” means for humanists, and how that differs from fields that – at a glance – would seem to be doing similar work with similar materials, hasn’t yet received the widespread recognition it deserves, by being conveyed only through talks rather than written publications. I couldn’t be more delighted that it’s now taking a printed form, both in this volume and in more formal articles, so that I can include it in all future syllabi and reference it anytime I’m called upon to “say a few things” about the intersection of digital humanities and data science or AI. This piece is a tribute to Miriam’s notes for one of her data talks, which she generously shared with me when I was at a loss for what to say to my students about the core question about what “data” means in DH. When I opened that Word file, I was expecting a few high-level bullet points about challenges that humanities research materials pose for the concept of “data”, as it’s used in data science. Instead, I found a beautiful articulation both of how many humanists engage with their research materials, and how humanists’ perspective on what matters is in some ways fundamentally at odds with the assumptions, conventions, and even the infrastructure underpinning both technical systems and the “data science” worldview. As someone with a disciplinary background in a humanities sub-sub-sub field (medieval Slavic linguistics) that didn’t do close reading, I felt like I gained a better understanding and appreciation for that methodology that I’d previously been somewhat dismissive of.

Before reading this lecture, I might have been able to gesture vaguely towards some of the particular challenges for the concept of “data” posed by humanities materials, but Miriam lays out seven issues – demarcation, parameterization, ontological stability, replicability, boundedness, deracination, and categorization – crisply explaining each one, with examples. And yet, this isn’t even the most striking part of the talk. In the final few pages, Miriam demonstrates the generous citation practices that also formed a common thread throughout the “Women and Gender Minorities in DH” workshop. She names and describes the Maori Subject Headings as an alternative structure for organizing knowledge, before turning to Black Code Studies as a provocative and inspiring model. In addition to giving a few examples of work done in this space, she gives a longer list of people working in the field, putting up a slide with their names (Shaka McGlotten, Tressie McMillan Cottom, Jessica M. Johnson, Simone Browne, Gabrielle Foreman, Safiya Noble, Mark Anthony Neal, and Mimi Onuoha) and explicitly suggests that the audience take note and “Google them later”.

Miriam Posner’s DH is one that reflects thoughtfully on the methodologies – technical and non-technical – of the humanities, and uses that worldview to interrogate the assumptions of data science, computer science, and related fields with which digital humanities finds itself in conversation. Miriam’s DH is one that uses speaking engagements as a platform for amplifying the voices of POC and queer scholars: not as a passing name-check, but as fundamental to a more nuanced wya of thinking about data, and in a way that prompts the audience to read that work for themselves. This is a DH that I want to help to build.