Blog, DH Fellowship

Summer Roundup: Making Arguments Using Digital History

With my summer as full-time Editor-in-Chief of Digital Humanities Now coming to an end, I thought it would be fitting and useful (at least for myself) to identify some kind of theme for the summer and write up a list of Editors’ Choice pieces that fall into that theme (sort of like I did here for the academic year). I didn’t have this theme already in mind when I was selecting posts for inclusion on DNNow; I set out to write this blog post, looked over the recent Editors’ Choice pieces, and found what stood out to me the most. As it turns out, a number of the Editors’ Choice pieces directly or indirectly address the topic of making arguments using digital history: how do we make those arguments, what are the problems we face in trying to make those arguments, how does argument relate to the form of digital projects, etc.

“Arguing with Digital History: A Workshop on Using Digital History to Make Arguments for Academic Audiences” is a workshop being held at RRCHNM in September. The aim of the workshop is “to encourage argument-driven digital history that contributes to disciplinary conversations,” and the result will be “a group-authored white paper on general principles for integrating digital tools and methods with the arguments and historical interpretations at the core of academic history.” It makes sense, then, that the question of how to make arguments using digital history would be on people’s minds. However, of the list below, only Ryan Cordell and Matthew Lincoln mention the workshop and will be workshop participants, so I think it’s fair to say that this conversation is not solely an effect of the approaching workshop.

 

Editors’ Choice: Computers & Writing Session F1 – Critical Making As Emergent Techne
by Daniel Frank – June 29, 2017

This post sums up a panel at the 2017 Computers & Writing conference. Using the examples of a class immersed in maker spaces and a bot that tries to subvert repressive Twitter dialogues, the panel sought to show how “critical making” and critical writing can “reinforce each other in the college writing classroom.” With the focus on writing and rhetoric, this post might seem disconnected from the topic of making arguments with digital history, but I think it does relate because it brings up an issue we encounter in digital history projects: trying to balance between “self-destructive… skepticism” of and “over-excited indulgence” in the digital. Using digital history to make academic arguments is important for the discipline, and for individual academics, but for all of the reasons below, we shouldn’t cease to be “critical makers.” After all, as the post points out, making and writing are not so dissimilar. From the post:

“Anthony Stagliano opened the session with a paper that situated ‘critical making’ as a position that works to avoid both the ‘Scylla’ of self-destructive or naval-gazing skepticism/criticality and the ‘Charybdis’ of an over-excited indulgence in technology in the classroom simply for the sake of technology. The critical maker, Stagliano said, looks at technology with a subversive but playful eye, looks to see how the technologies work, how they can be opened up and modified, how they may be used to challenge the status quo, and how they can lead to perceptual shifts in conversations, in what can be done, what can be seen. ‘Critical making at its best is affirmative rather than negative,’ Stagliano said; it’s about affirming possibilities, seizures, and perversions.”

 

Editors’ Choice: The Form of Digital Projects
by Nicole Coleman – July 13, 2017

In this brief but insightful post, Coleman claims that, “The form of digital projects has a direct bearing on the ideas they convey.” These decisions about form are therefore crucially important to the communication of scholarly ideas, but they are not yet part of disciplinary training and rhetoric. Although Coleman doesn’t give all the answers for dealing with this disjuncture, her post highlights why thinking about how to argue with digital history also means thinking critically about the form of digital projects. From the post:

“Though we may no longer think of ourselves as using word processors when we write with computers, we do pay attention to the format of the electronic documents we create and share. The format, whether .doc, .pdf, .rtf, .md, or one of many others, tells us something about the functionality and interoperability of the electronic file. With digital projects, the form changes everything. Print books published by the Press are usually born-digital—written with the help of a word processor. But, as Jasmine Mulliken explained in her post, ‘Beyond the ebook,’ what distinguishes digital projects is the way the argument is tied to the digital form. It is precisely that close link between the form and the argument that presents significant new challenges.”

 

Editors’ Choice: Argument Clinic
by Scott B. Weingart – August 1, 2017

The Twitter conversation linked below is the reason at least two of these posts were put up and the reason I was able to find and nominate them. This post is sort of a guide for beginning digital historians to go from data/statistics to argument. In that sense, it comes closest to answering the question of how to make an argument using digital history. From the post:

“Zoe LeBlanc asked how basic statistics lead to a meaningful historical argument. A good discussion followed, worth reading, but since I couldn’t fit my response into tweets, I hoped to add a bit to the thread here on the irregular. I’m addressing only one tiny corner of her question, in a way that is peculiar to my own still-forming approach to computational history; I hope it will be of some use to those starting out.

In brief, I argue that one good approach to computational history cycles between data summaries and focused hypothesis exploration, driven by historiographic knowledge, in service to finding and supporting historically interesting agendas. There’s a lot of good computational history that doesn’t do this, and a lot of bad computational history that does, but this may be a helpful rubric to follow.”

 

Editors’ Choice: What Makes Computational Evidence Significant for Literary-Historical Argument?
by Ryan Cordell – August 1, 2017

Ryan Cordell points out a specific problem with making digital (literary) history arguments: “we don’t yet as a field understand precisely how corpus-scale phenomena make their meaning, or how those meanings relate back to codex-scale artifacts.” Focusing on text reuse, he argues that no one in the nineteenth century had the “corpus-scale perspective” on a textual cluster that we are able to get today. That makes it hard to “extrapolate from the meanings we assign a cluster (among many other clusters) to the meanings of its constituent texts, much less the readers of those texts.” Cordell presents more problems than solutions, but they are important problems to discuss in order to understand how to argue with digital history. From the post:

“There has been much written (including by me!) about the need for zoomablescalable, or macroscopic reading that puts insights drawn from distinct scales in conversation. However, I would argue that thus far digital (literary) history has not adequately theorized the middle ground between corpus and codex, or developed methods that can meaningfully relate corpus-scale patterns to individual texts without pretending that patterns at each scale can be understood under the same interpretive paradigm. I would go so far as suggesting the macroscope is not the most useful metaphor for structuring digital historical arguments, as it implies a seamless movement between scales that the realities of analysis belie. Perhaps new metaphors are needed for expressing the continuities and disjunctures between analyses at distinct scales.”

 

Editors’ Choice: Predicting the Past – Digital Art History, Modeling, and Machine Learning
Matthew Lincoln – August 3, 2017

This post discusses the possibilities, as well as the limitations, of using explicit model building to build historical interpretations and arguments. When there is an abundance of evidence about a complicated process, it can be challenging for historians to evaluate the plausibility of a theory or to come up with a theory at all. In these circumstances, models can be used to “predict the past,” or to play out and evaluate theories. As Lincoln points out, “Computational simulations will never capture the full complexity of history—but then again, historians aren’t here to tell everything. We are here to distill evidence into a cogent argument.” Through the examples in the post, it is possible to see how explicit model building can help historians get from data to argument.

“Thus, Epstein argues, the choice for scholars isn’t whether or not to model, but whether or not to do so explicitly by specifying our starting premises along with the rules—whether defined mathematically, or in code—that lead from that starting evidence to our final conclusions. Among other benefits, Epstein shows that explicit model buildings help us form better explanations, discover new questions, and highlight uncertainties and unknowns.

While Epstein was talking about modeling in the context of the social sciences, many historians are beginning to think (once again) about the intersections between modeling and historical thinking and argumentation. Historians create theories to explain the processes that may have produced evidence—whether archeological remains, archival documents, or even works of art—that survives today.”

 

Editors’ Choice: What Do We Do About Archival Violence? (#DH2017 Talk)
by Anelise Hanson Shrout – August 15, 2017

This post specifically addresses problems with making digital history arguments about historically marginalized people. When you’re working with quantitative data that was used to dehumanize people, how do you work against that violence? How do you use it to make an argument that is humanizing and disrupts power structures? Shrout has three answers: look for discrepancies between what the data shows and what we know, use the data to understand invisible institutional forces, and use digital methods to locate moments of contingency and agency. From the post:

“Finally, and this is what I want to close with, we can use quantitative methods to identify particular moments of contingency. Put another way, we can identify variables (each of which signifies one stage in immigrants’ passage through the almshouse) which significantly predict or are correlated with some other stage or experience, and then drill down into those moments, and imagine the ways in which immigrants within this system might have exercised agency.”