Das Komitee der AG Digitale Geschichtswissenschaft im Verband der Historiker und Historikerinnen Deutschlands freut sich, Ihnen das offizielle Programm des diesjährigen Praxislabors vorzustellen! Auf dem Historikertag in Bonn warten von Dienstag, den 16.9., bis Donnerstag, den 18.9, vielfältige praxisorientierte Workshops auf Sie.

In bewährter Tradition werden damit digitale Ansätze und Methoden in ihrer Breite erfahr- und erlernbar. Angesprochen sind mit dem Programm sowohl interessierte Einsteiger:innen als auch Spezialist:innen. Das Praxislabor schafft auf diese Weise eine Plattform, um digitale Methoden und Tools für die Geschichtswissenschaft praktisch zu erkunden, Projekte hinsichtlich ihrer digitalen Methoden und Ergebnisse kennenzulernen, Fragen zu stellen und pointiert Themen zu diskutieren. Dabei handelt es sich um ein communitygestütztes Angebot – denn aus den vielfältigen und durchweg spannenden Einreichungen, die das AG-Komitee im Rahmen eines Call for Workshops erreicht haben, haben wir diese Auswahl treffen können.

Die Anmeldemodalitäten und alles weitere Wissenswerte erfahren Sie auf den Informationsseiten, die wir für jeden Workshop auf unserem AG-Blog bereitgestellt haben. Bitte beachten Sie, dass die Anmeldung zwar auf diese Weise erfolgt, das Praxislabor 2025 aber Teil des Historikertags ist, für den alle Teilnehmer:innen ebenfalls angemeldet sein müssen. Hier finden Sie sämtliche Informationen: https://digigw.hypotheses.org/6170

Mit herzlichen Grüßen, im Namen des AG-Komitees,
   Christian Wachter

What follows is material drawn from a larger book project I’m working on about an approach to digital humanities pedagogy that intersects with administrative policy to work towards a more equitable landscape for higher education. I’ll be blogging pieces of it as I go, so stay tuned for more related work in the future. Keep in mind, though, that I will likely be blogging about other topics intermittently as well. You can find book-related posts here. Happy to hear feedback, either on social media or by email at bmw9t@virginia.edu.

This is a book about teachers, the labor they take on, and the structures that prevent them doing that work well. Our institutions often define teaching as something that happens in specific spaces, at specific times, and by specific people. In higher education, positions are often described with a common shorthand: “I teach a 2-2” or “I carry a 4-4.” The formulation describes both a calendar distribution as well as the supposed burden of teaching. Once your courses are done—your course load carried—you can get back to work. And the implicit encouragement is to spend less time on teaching and more time on your tenure file. The classroom is a space to be escaped. And when we describe some positions and institutions as teaching-intensive, however true the designation might be, we create boundaries. We suggest that some spaces are for teaching and some not.

Staff positions often distribute identification with the craft of teaching in a similar way. A Teaching and Learning Librarian might explicitly focus on classroom instruction. An Undergraduate Success Librarian might specialize in undergraduate outreach. Some roles might work with patrons directly to answer questions and roles, while others might think of themselves more as back of house and removed from the community. As with faculty positions and their associated teaching responsibilities, the ways we distribute staff labor can suggest separation between those who teach and those who do not. Some are in the classroom, while others might never set foot in it.

But we all teach.

It is understandable that someone without explicit classroom responsibilities might see themselves as disconnected from the act of teaching. But we do ourselves and our students a disservice when we fail to recognize the teaching that takes place across the institution by instructors in a range of different job titles. This book specifically speaks from the point of view of the teaching librarian, in part, because library positions entail a range of types of interaction. In some cases, librarians might design for-credit courses as part of the curriculum. But so much of the work of librarianship takes place in other spaces: reference consultations, collaborations with faculty members, one-on-one mentoring, workshops, one-off instructional sessions, and more. To be a librarian is to dance along the cracks of the institution, engaged in a thousand small teaching acts. Because of this, library perspectives are helpful for illuminating the cross-cutting impact of pedagogical decisions.

In the same way that teaching occurs throughout the university, staff positions like those in the library are useful case studies for discussing the pedagogies of institutions because they are regularly called upon to engage in the infrastructure of the university. Even if their job titles do not contain the word “administrator,” staff positions often make policy decisions that affect others. Digital humanities library positions, in particular, expose the ways in which teaching is an intersection of pedagogy and policy. Throughout this book I use the term teaching administrator to refer to individuals inhabiting such complicated roles in places of higher education. The term refers to those faculty and staff who inhabit administrative roles within their respective institution but also provide instruction in some capacity. I use the term administrator quite liberally here: it refers not only to directors or managers but more broadly to anyone engaged in the inner workings of university infrastructure and making policy decisions for it. Teaching, too, is construed broadly. Teaching takes place throughout the university, in its cracks and its hallways, in all manner of forms. The teaching administrator might direct a center but teach a course periodically. They might be a GIS Specialist who also runs regular workshops. Or they might be a developer engaged in paired programming with a student as part of a project development. Teaching administrators, no matter their specific job title, regularly find themselves implicated in and exerting force upon the various policies and norms that work on the institution and, in so doing, upon their embedded pedagogies.

More specifically, this is a book about all those principles, practices, and structures that intersect in a kind of pedagogy in the institution around them. When a local government reduces its budget, forcing secondary educators to dip into the own bank accounts to pay for classroom supplies—that is an observable act that impacts pedagogy. The material conditions of the classroom are changed based on administrative choices that are removed from the classroom. When the chairs in a public classroom are welded to the floor so as to prevent them from being moved from neatly arranged rows—that is a kind of pedagogy. The decision to bolt chairs to the ground may never have been made with actual instruction in mind, but it nonetheless affects the possibilities for learning in that space. The university encourages the idea that teaching takes place in the classroom, and this mode of thinking is a function of policy, power, and politics. When conversations are not explicitly about teachers and students—a kind of pedagogy is still being enacted. After all, an absence can still be noted and remarked upon. Why aren’t we talking about teaching? What does it say about what we value instead? A pedagogy.

This is a book about administrative choices like these, about the ways in which they help or harm the teachers in their midst. About all the myriad ways in which the work of education is routinely damaged by forces outside the classroom. This book argues that these institutional norms, policies, and structures act as embedded pedagogies that are operationalized for or against teachers and learners. Most often, as in the case of budgets cuts or prescriptive classroom spaces, these institutional pedagogies put teachers on the back foot, forced to teach in ways they might not otherwise do so in part out of a survival instinct. The first step to finding our way to the teaching we want to see in our work is to recognize the obstacles facing that labor, the pedagogies running counter to our own. And it can be especially difficult to notice the things affecting our teaching when they happen far outside the classroom, carried out by those who don’t consider themselves educators. By recasting institutional activities and actors in pedagogical terms, I hope to empower teachers to find their own path to enduring administrative difficulties even as they work to change them. These embedded pedagogies can be especially challenging to work against because the pressures they exert are often invisible to the teachers and learners in their midst. The first tactical decision we can make to counter them is to render them known.

Universities invest vast resources in making themselves known to their students, their communities, and their publics, from marketing to branding, communications to legislative testimony. In the process, though, this knowability is limited by design, as elite universities necessarily want themselves to be only so known, in specific ways, and by particular people. Institutions frequently obscure their actual administration in ways that distance teachers from their core functions. This web of policies, practices, and pressures shape our ability to teach and learn in seen and unseen ways, forming the network of embedded institutional pedagogies. By rendering these opaque practices transparent, we can empower educators to intervene in the forces affecting their ability to do the work of teaching.

In a certain way this book was also my own attempt to chart a pathway to survival in the face of the embedded pedagogies of my own institution. During a period of administrative upheaval at my place of work, blogging became a way for me to vent and reflect about the challenges I found for supporting student work. The audience I found for this writing seemed to be largely people in positions like mine: mid-career digital humanities administrators who had a hand in research, teaching, and administration. Positions like these are sometimes called “alt-ac” for the ways in which they offer a landing for graduate students outside of the traditional faculty path. Alt-ac staff often refer to themselves as scholar practitioners, a phrase that further serves to illuminate the fact that we often see administrative praxis itself as a subject for research and critique in its own right. The term “teaching administrator” is a similar riff, both a description of a hybridized identity and an attempt to instrumentalize it.

In moments of despair I sometimes referred to this manuscript as “the book I’m writing about bullshit and how to deal with it.” Invariably, others would respond with their own, similar frustrations at their own institutions. Embedded pedagogies carry power, in part, because they refuse to be seen for what they are. Writing this text is a first attempt at making legible the relationship between administrative policy and teaching in a way that makes them visible. To describe what I see so others can notice as well. To know and be known. To use the unique position of the teaching administrator to push back on the limited knowability of the institution and render legible its embedded pedagogies.

A version of this piece will be an open-access chapter in a volume by invited speakers at the 10/23/2024 “Reimagining AI for Environmental Justice and Creativity” conference, co-organized by Jess Reia, MC Forelle, and Yingchong Wang and co-sponsored by UVA’s Digital Technology for Democracy Lab, Environmental Institute, and School of Data Science. I had more to say, but this was what I managed inside the word limit!

I direct the Scholars’ Lab, a digital humanities (DH) center that’s led and collaborated on University of Virginia ethical, creative experimentation at the intersections of humanities, culture, and tech since 2006. A common definition of DH encompasses both using digital methods (such as coding and mapping) to explore humanities research questions (such as concerns of history, culture, and art); and asking humanities-fueled questions about technology (such as ethical design review of tools like specific instances of AI). I always add a third core feature of DH: a set of socially just values and community practices around labor, credit, design, collaboration, inclusion, and scholarly communication, inseparable from best-practice DH.

I write this piece as someone with expertise in applicable DH subareas—research programming, digital scholarly design, and the ethical review of digital tools and interfaces—but not as someone with particular experience related to ML, LLMs, or other “AI” knowledges (at the levels that matter, e.g. code-review level, CS-journal-reading). A field of new and rapidly evolving tools means true expertise in the capabilities and design of AI is rare; often we are either talking about secondhand experiences of these tools (e.g. “Microsoft Co-Pilot let me xyz”) or about AI as a shorthand for desired computing capabilities, unfounded on familiarity with current research papers or understanding of codebases. (A values-neutral claim: science fiction authors without technical skillsets have helped us imagine, and later create.)

Convergence on the term “data science” has both inspired new kinds of work, and elided contributions of the significantly overlapping field of library and information studies. Similarly, “AI” as the shorthand for the last few years’ significant steps forward in ML (and LLMs in particular) obscures the work of the digital humanities and related critical digital research and design fields such as Science and Technology Studies (STS). When we use the term “AI”, it’s tempting to frame our conversations as around a Wholly New Thing, focusing on longer-term technical aspirations uninhibited by practical considerations of direct audience needs, community impacts, resources. While that’s not necessarily a bad way to fuel technological creativity, it’s too often the only way popular conversations around AI proceed. In one research blog post exploring the moral and emotional dimensions of technological design, L.M. Sacasas lists 41 questions we can ask when designing technologies, from “What sort of person will the use of this technology make of me?” to “Can I be held responsible for the actions which this technology empowers? Would I feel better if I couldn’t?” We don’t need to reinvent digital design ethics for AI—we’ve already got the approaches we need (though those can always be improved).

When we frame “AI” as code, as a set of work discrete but continuous with a long history of programming and its packagings (codebase, repo, library, plugin…), it’s easier to remember we have years of experience designing and analyzing the ethics and societal impacts of code—so much so that I’ve started assuming people who say “LLM” or “ML” rather than “AI” when starting conversations are more likely to be conversant with the specifics of current AI tech at the code level and CS-journal-reading level, as well as its ethical implications. The terms we use for our work and scholarly conversations are strategic: matching the language of current funding opportunities, job ads. We’ve seen similar technologically-vague popularizing on terms with past convergences of tech interest too, including MOOCs, “big data”, and the move from “humanities computing” to the more mainstreamed “digital humanities”.

Digital humanities centers like our Scholars’ Lab offer decades of careful, critical work evaluating existing tools, contributing to open-source libraries, and coding and designing technology in-house—all founded on humanities skills related to history, ethics, narrative, and more strengths necessary to generative critique and design of beneficial tech. Some of the more interesting LLM-fueled DH work I’ve seen in the past couple years has involved an AI first- or second-pass at a task, followed by verification by humans—for situations where the verification step is neither more onerous nor more error-prone than a human-only workflow. For example:

• the Marshall Project had humans pull out interesting text from policies banning books in state prisons, used AI to generate useful summaries of these, then had humans check those summaries for accuracy
• Scholars Ryan Cordell and Sarah Bull tested Chat GPT’s utility in classifying genres of historical newspaper and literary text from dirty OCR and without training data, and in OCR cleanup, with promising results
• My Scholars’ Lab colleague Shane Lin has been exploring AI applications for OCRing text not well-supported by current tools, such as writing in right-to-left scripts
• Archaeologists restoring the HMS Victory applied an AI-based algorithm to match very high-resolution, high-detailed images stored in different locations to areas of a 3D model of the ship Alongside any exploration of potential good outcomes, we need to also attend to whether potential gains in our understanding of the cultural record, or how we communicate injustice and build juster futures, are worth the intertwined human and climate costs of this or other tech.

One of DH’s strengths has been its focus on shared methods and tools across disciplines, regardless of differences in content and disciplinary priorities, with practitioners regularly attending interdisciplinary conferences (especially unusual within the humanities) and discussing overlapping applications of tools across research fields. DH experts also prioritize non-content-agnostic conversations, prompted by the frequency with which we borrow and build on tools created for non-academic uses. For example, past Scholars’ Lab DH Fellow Ethan Reed found utility in adapting a sentiment analysis tool from outside his field to exploring the emotions in Black Arts Poetry works, but also spent a significant portion of his research writing critiquing the biased results based on the different language of sentiment in the tool’s Rotten Tomatoes training dataset. (ML training sets are an easy locus for black boxing biases, context, and creator and laborer credit—similar to known issues with text digitization work, as explored by Aliza Elkin’s troublingly gorgeous, free Hand Job zine series capturing Google Books scans that accidentally caught the often non-white, female or non-gender-conforming hands of the hidden people doing the digitizing.)

We already know where to focus to produce more beneficial, less harmful, creative digital tools: social justice. At the Reimagining AI roundtable, my table’s consensus was that issues of power and bias are key not just to reducing ML harms, but to imagining and harnessing positive potential. Key areas of concern included climate terrorism (e.g. reducing the energy costs of data centers), racism (e.g. disproportionate negative impacts on BIPoC compounding existing economic, labor, and police violence threats), human rights (e.g. provision of a universal basic income easing concerns about areas ML may beneficially offset human labor), and intertwined ableist and computing access issues (e.g. AI search-result “slop” is terrible for screen readers, low-bandwidth internet browsing). In our existing scholarly fields and advocacy goals, where are current gaps in terms of abilities, resources, scale, efficiencies, audiences, ethics, and impacts? After identifying those major needs, we’re better positioned to explore how LLMs might do good or ill.

(Part 3 of a 3-part series: see also the 1st post on email practices and some caveats about my particular academic job context, and the 2nd post on Slack, task management, meeting notes.)

My previous two blog posts shared some of the ways I approach “work chores” (email, Slack, tasks) to keep them more sustainable. In this third post, I wanted to share a bit about how I try to do things as a manager/director re:similar expectations-impacted work-chore practices, so that my colleagues in the lab can also try or use the approaches to work that work best for them.

Not just asking about work sustainability; offering to act

As a manager, I try to regularly check in: Do you have time blocked out for focus, work-chores, time off? But I try to not only ask “are you doing these theoretically useful approaches”; I also want to discuss if the person needs those or wants something different; what is making it difficult to use these or other work-management approaches; what can we do to make this all more sustainable. Do you need actions from me/other colleagues to support that, e.g. changing deadlines, moving or cancelling meetings, changing communication formats (emails, Slack, meetings), notes from a meeting you can’t make? If you’re going to ask if people have time blocked out for needed things like focus and time off, being prepared with possible ways to help if they don’t makes sense.

Where expectations are needed, make them as loose as possible

As a manager, I try to make space for others to figure out the what, when, how of the practices that work best for them. To do this, I try to communally discuss and set agreements on what outcomes are critical (e.g. impact colleagues and people we support) and which are nice to have; and to let folks know they can question and advocate for something different these expectations, which are often ultimately somewhat arbitrary (e.g. why answer most emails within 2 workdays rather than 3 or 4?). I try to keep expectations as high-level and brief as possible—setting these as what’s fine for us to generally at least meet, rather than what’s ideal (but not required to happen all the time—or at all, if doing so impedes other work/focus/non-work time). And I try to talk about my reasoning for expectations, since that can often be useful context (e.g. something that isn’t a big issue if 1 person does it, but I ask for because I have not 1 but 10 full-time staff reporting through me, so effect of approach x multiple people may be a big issue) or allow my colleague to suggest alternatives that still meet my goals while also meeting theirs.

For example, when responding to our lab’s consult listserv, we want people to feel welcomed and know they’ve contacted folks who will get them to the right place, even if that isn’t ultimately the lab. We do also balance a lot of consultations against longer projects, teaching, fieldwork, events, etc., and try to set public expectations of our availability for consultations as usually 2-3 weeks out from original email date (though we can meet faster when there’s an urgent need). So our expectation is that we try to have someone on staff reply to any initial message requesting a consultation with us, to us within two workdays if possible; but that reply can simply be “thanks for your message; we’re discussing internally, and will get back you with more by [DATE]” if needed. This is useful when an ask requires us to talk to colleagues in different units about a project’s history, ID whether anyone has some specific software experience, and/or when multiple relevant staff across units might all be available to attend a consultation together.

This meets our goals of making sure the person contacting us feels welcomed and knows we’ll be helping them, but also does not require staff to constantly check or reply to email. As with my post on personal email/etc. approaches, we often reply to folks within the same day! But setting the minimum bar higher is good for making sure folks can set boundaries on email management, and also get non-email work done.

I try to emphasize communication over conformance: it’s okay if you need more time, need to change plans, etc. But the way you make this not adversely impact colleagues is by communicating as early as possible when you need a change and why. (E.g. if you’re repeatedly asking for extensions after deadlines pass instead of well before, it could be a sign that deadlines are being set too soon, you have too much work, or something else we should work on making more sustainable.)

Look for ways to support others’ needs

We know other Library colleagues sometimes have in-person, or urgent questions from visitors for us. While protecting time to do the kinds of focused work we’re tasked with (and acknowledging we’re not staffed to have someone guaranteed available and able to drop their work at any time for unscheduled non-emergency drop-ins), we’ve got several approaches to staying available to other Library staff, including:

• Our consult listserv goes to our whole team of 12 people, so even if each person is only checking email once a day (not the norm), when that happens would vary enough we’re getting someone seeing incoming emails who can usually note if something’s urgent.
• We use Slack a bunch, and its notification settings make it easy for us to find each other and ask for a quicker reply, when one’s actually needed.
• We’ve set “core staff hours” when it’s most likely you can find a free staffer somewhere in the lab, and shared these with library circulation desks; as well as non-public, broader core times when at least several of us are physically in the lab and findable if needed.

Ultimately, we are privileged to encounter few work-related emergencies (e.g. site is down before a conference talk about it; water is leaking into the makerspace; short-notice funding possibility). We try to make our availability and response practices clear, so folks know how and when they can find us.

Part 2 of a 3-part series: notes on what works for me, when managing alt-academic job work-chores. This one covers Slack, tasks, and meeting notes. The 1st post covers my email practices, as well as some caveats about my particular context relevant to why I can and do things this way. The 3rd post on supporting work practices like these as a manager will be linked here, once it’s published (assuming I remember…).

Slack

I have a daily “Slack catchup” time, like I do for email. This works best when I do it at a time there aren’t many folks actively chatting, so that I do eventually get to all waiting messages; on the downside.

• As with email, I do in practice check Slack elsewhen, but having the daily catchup time lets me close Slack (and Outlook) when I’ve scheduled myself to focus on getting a specific thing done. I could easily spend all day answering email and Slack if I just kept them open and checked them throughout the day.

Slack has a couple helpers I like, both superior to “mark unread” (as it’s easy to accidentally open a channel, and have it auto-mark something as read when you didn’t actually look at it):

• Bookmark icon/”save for later” holds messages in a “later area => stuff I want to remember or look at again during my weekly Brain Day time or after, but zero urgency
• Message menu > remind me about this => for messages I want to be reminded of at a specific time (e.g. something I skimmed but need to respond to by the end of the day, but not now because I’m leaving for a meeting; something I want to remember at the end of term).

Task management app

I use a task management app that allows setting recurring reminders:

• There are many good, free options; it’s worth playing with a couple to see which is comfortable and matches your particular way of handling tasks (also look for: syncing to phone/between computers; ability to export/backup in readable format). I use Things3 for Mac.
• I keep a “Brain Day” area on my task app that fills with recurring tasks on my Friday “Brain Day”s, in the order I want to do them in (stuff I can’t miss doing weekly or it’s a problem, e.g. email catchup, first).
  • I add a weekly reminder to check Slack’s “later” area for messages I should respond to, that I do once I’m on top of email.
  • This approach also helps with non-weekly reminders, like “add your consult stats to LibInsight bimonthly” and “bimonthly block out any leave days on my calendar for the next two months” (so I remember to mark stuff so people know when they can’t schedule me).
• I have task app areas for various categories of things, including
  • “flagged” (do this first when you start work on x day)
  • sets of tasks I only want to look at/work through in priority order at specific times (e.g. my ACH volunteer work, during the ACH meeting’s work time)
  • tasks I can’t/shouldn’t do until a specific date (so I don’t need to see them until then)
  • things I asked of others (as a manager; reminder of when to check in, if don’t hear back)
  • “errands” (zero-urgency things I get to in priority order, just as time allows)

Meeting notes

I use a Remarkable 2 tablet (e-ink tablet) to take notes during meetings:

• I use a different notebook for each meeting kind: 1 notebook per
  • recurring 1:1,
  • recurring groups like our all-staff meeting,
  • related aggregators of ad hoc meetings, such as external consultations, SLab website sprint discussions
• Each new meeting date starts on a new page of the notebook, with the date and meeting title at the top.
• I keep a small lined paper pad and pen next to the Remarkable. If a task for me comes up during the meeting (something I need to do or say), I write it on the paper tablet:
  • Things that must be done before my next “Brain Day” get a star, and I try to remember to do them or add them to my task app that day. I used to use symbols in my meeting notes to mark things that were tasks, but that means I need to look back through my meeting notes to find tasks from the past week, and I repeatedly did not and let those build up.
  • Keeping tasks on their own paper list means I can just see all incoming tasks there; paper vs. directly into task app means that the “wouldn’t it be cool if…” and “I can do this in 30 seconds after meeting ends” don’t clog the task app (I used to struggle with putting way too many “wouldn’t it be cool if” ideas into my task app, making it hard to see what’s actually urgent and look like I’m behind on working though tasks).

The following is a short, internal lightning talk I gave to UVA Library staff as a part of the Library’s Open Access Week in fall 2024.

Hello! My name is Brandon Walsh, and I’m Head of Student Programs in the Scholars’ Lab, one of the twin branches of the UVA Library’s Digital Humanities Center. I was asked to talk a bit about my work in open pedagogy as it intersects with digital humanities, a big baggy field in which we’re constantly confronting what we don’t know and helping others to do the same. From my earliest days working in DH, way back when I was a student myself in the Lab and in the Library, I was drawn to this pedagogical through line. The sheer importance of learning to it all. And this, in turn, has deeply informed how I approach Open with my students.

Always learning. Always teaching.

Together.

My practice of open digital pedagogy is informed by three intertwining principles:

1. Humanities students see themselves as imposters more often than not, particularly when it comes to technical concepts and methods.
2. Students are experts in teaching and learning. There is no one better equipped to explain something complicated than a person who has just learned it.
3. The labor of teaching and learning is often invisible.

My whole career has been about the commingling of these three concepts when it comes to pedagogy—self-confidence, expertise, and visibility.

Open has been the space in which they meet.

Often, this takes the shape of co-authored OER materials with my students. I co-wrote A Humanist’s Cookbook for Natural Language Processing in Python with Rebecca Bultman, then a UVA religious studies PhD. When I was a postdoc at Washington and Lee University, I co-wrote a course book on text analysis with Sarah Horowitz, a faculty collaborator who I was co-teaching with at the time. In each case, the process of co-writing, I hoped, would offer my partners a space to teach themselves something about the topic as well as the technical stack that it took to make it. They learned the terminal, Python, text analysis, markdown, version control, and more. I, in turn, learned to be a better teacher: the materials were much improved by having them involved as partners. The outcomes also presented this labor—the work of teaching and learning—in a space that was available to other learners and also CV-friendly. By positioning these student collaborators as co-writers, co-experts, I hoped to gently affirm that they were more than capable of doing this work. And the work aimed to present this new material in a space that would be more comfortable for humanists, grounding the learning process in public writing and conversation as opposed to pounding away at a programming script.

The production of open materials, by, for, and with students like these has always been a core part of my DH practice. Sometimes, as with these examples, the result explicitly looks like OER, but it’s often just about asking students to write in public about the process of teaching and learning. They teach themselves new techniques, develop workshops for each other, and document the teaching materials for others. My students use open writing as a means of imagining into existence the kind of scholars they want to be on their own terms—they don’t wait for academic publishers to credential them accordingly. The examples I used here were specific to me, but virtually every member of the Scholars’ Lab staff is engaged in this work in some capacity. We want our students to see the Lab and the Library as spaces that see them for who they are—worthy and capable even as they are learning.

All of this is to say that open pedagogy for me means treating students as true partners in the production of scholarly knowledge. They teach me as much as I them, and it happens in public. I’ll close with a quotation by Nicholas Payton, a jazz hero of mine. It’s one I sit with every day.

“There are no great teachers, only great students who give tools to other students.”

I’m sharing some approaches to work chores (email, Slack, etc.) that are currently working for me. This is another “my SLab colleague told me I should write a post about this” post—thanks to Brandon Walsh for suggesting I make some of my more personally-successful work-chore practices (which I periodically have shared with various staff, when asked) into a public post. I’ve found it most useful to try out small changes at a time, not huge swerves among different systems of task management.

Short version, pls

tl;dr of the hacks detailed below and on subsequent posts in this series:

1. Have a daily email/message triage time, putting those messages that can wait for reading/reply until a weekly email catchup time, into a folder to attend to then.
2. Block that weekly catchup time on your calendar, preferably the same time each week, at a time you won’t struggle to put aside other work to finish going through those emails (e.g. I do it first thing Friday mornings).
3. Use: Outlook rules to divert low-priority emails and highlight high-priority emails; Slack “save for later” and “remind me about this” (not “mark unread”); a task manager that supports recurring tasks.

Some caveats

This is a very “your mileage might vary” post; this doctor is not saying whether these approaches are right for you. Directing a library-based DH research center means my workday involves a variety of communications (e.g. Workday notifications, budget reports, sending many recurring meeting invites to various groups) that make it more useful to have a more formal system for balancing them against focused work time, as do my own particular work habits and neurodivergence. (FWIW, I am very much an Always Inbox Zero, Task App: Too-Many person.)

I also recognize my privilege in having the job type, security, supervision level, accessibility accommodations, and more that mean I get to make these choices. Some workplaces have invasive policies about when, how, how often; some jobs actually need you to be checking or replying to communications as they come in; some teams would be negatively impacted by someone not checking messages as often as the group truly needs. Different jobs have different needs and/or culture regarding what goes into email, Slack, recurring meetings, or ad hoc conversations.

In particular, the part about how often I check my email felt a bit fraught to share, especially without sharing more context about accessibility. But it’s made a significant improvement in how well I can focus, make progress, maintain work boundaries and sustainability, as well as do well by my colleagues—so I wanted to share it, even if it isn’t necessarily something everyone else can implement as described. (Part two of this blog post will discuss how I try to accommodate similar practices for my colleagues, as a manager/director).

Ultimately, I try to balance two things:

• being able to get to the kinds of focused work that are part of my job, without interruption (unless something is truly an emergency)
• responding to messages within a reasonable timeframe, and having a triage system keeping my inbox manageable so I can more easily see if a colleague sends an urgent-response-needed message

Some approaches that work for me, right now

Email management

I use a daily triage practice, plus a weekly block for catching up on reading/replying to things that can wait until then:

• I have a daily time when I’m always free (5-30min?), that I block for managing email (Outlook is what UVA uses for staff). I put this daily email time as a recurring hold on my calendar until it became habit, and now I just do it first thing, before any meetings.
• I have a “process today” email folder; when this daily email time happens, I dump everything currently in my inbox into “process today”. I don’t require myself to look at my inbox again until the following day, unless* I’m done with all my other work and feel like it.
  • This helps me not get caught up answering constantly incoming stuff, which can usually wait a bit, and get to older reading/replies first.
  • * In practice, I do actually check my work email several times per workday. I try not to do so until I’ve both done that initial transfer to the “process today” folder, and until I’ve processed that “process today” folder (as described below). This means that any other emails I get to are a bonus, so they don’t carry the same feeling of “I’m behind until I clear this from my inbox”.
• Emails that can wait until my weekly “catch up on work chores” block (Friday mornings) get moved to a “Brain Day” folder.
  • This keeps my inbox more manageable, so I can more easily visually skim it between meetings to notice if someone does have an urgent and/or easy-to-answer question
• I try to reply to everything else in the “process today” folder during that daily time, even if it’s just to say “I received this, but it’ll be [a couple days] before I will have a more substantive response”. I send that kind of message if I’m not sure I’ll get to something (better to followup up sooner than promised, than to forget to respond).

“Brain Day” for weekly work chores

I use a weekly, scheduled catchup block (“Brain Day”):

• During “Brain Day”, I catch up on all emails I moved to the “Brain Day” folder during the week—the ones that could wait to be read (including non-urgent FYI things, newsletters), and emails I told people I’d need more time to reply to.
• If I can’t finish working through all my email then, I block time to do so the following week (rare/ugh).

After completing email catchup, I also use that “Brain Day” block to do other weekly or monthly recurring work chores, like updating our budget, planning what tasks I’m doing the following week, and prepping for the next week’s meetings.

Other email hacks

I use Outlook rules to:

• route stuff that I mostly only need to skim or can wait to read until my weekly “Brain Day” (e.g. from our “general announcements to all Library staff” listserv, which tends to more “here’s an interesting webinar” and less “urgent info to read today”) into the “Brain Day” folder, so I don’t have to look at it nor manually sort it until Fridays
• route stuff I need to get to sooner (e.g. emails to the SLab consult listserv; emails from SLab staff, supervisors) into a place I’ll see them easily
• Move some sent emails to a “Waiting to hear” folder, if I need to make sure I do hear back a response (vs. assuming someone will definitely write back); I check this during weekly “Brain Day” to see if I need to ping anyone about a non-response (when enough time has gone by)

I don’t currently need this, but if staying out of your inbox is hard because you need to notice specific things: I used to use USB LEDs called Blink(1)s to alert me to things I wanted to notice. For me, that was during my dissertation’s Infinite Ulysses open beta, when I wanted to know when someone created a new account on my digital edition, or posted an annotation. But you could hook these up to IFTTT or Zapier and have specific combinations of person and text on Slack or Outlook trigger the light turning on, or blinking in a pattern. (I can’t use sound notifications—if you can, you can of course set up Slack/Outlook to make a noise for certain things, though I think this isn’t granular down to e.g. “make this sound if x person pings me”?)

The next two posts will deal with Slack, task management, and meeting notes; and handling expectations vs. healthy work practices, as a manager.