The posts rarely strayed far from manuscripts, yet it seems like some most important challenges facing medievalists in the 21st century have little to do with the manuscripts themselves. We need to think much more broadly about the future of medieval studies, its data, the community practice of producing and interacting with that data, and how training in medieval studies can become much more relevant both to students who go to careers in a related field and to students who end up working in a totally different one.

Medieval Medicine

Session 48: Medicine in Medieval Iberia
Public Health Initiatives of a Town in the Late Medieval Crown of Aragon: Castello de la Plana | Douglas Kierdorf, Bentley Univ.

Medicine in Late Medieval Portugal: A Distinctive Spectrum of Healthcare? | Iona McCleery, Univ. of Leeds

Medical Cosmetics? An Ekphrastic Approach | Cristina Guardiola

Session 72: Wounds, Torture and the Grotesque
Holy Blood, Holey Body | Rachel Levinson-Emley, Univ. of California–Santa Barbara

The Vision of Thurkill and the Performance of Purgatory | Michelle Kustarz, Wayne State Univ.

“Food for the Beasts”: Broken Human Bodies in Medieval Bestiary Illuminations | Susan Anderson, Arizona State Univ.

Session 121: Old English Literature
Locating the Alien Spirit: Poisonous Blood and Medieval Medicine in Beowulf | Barrett Beck, Florida State Univ.

Old English Remedies for Poison: Materials and Metaphor | Claire Whitenack, Cornell Univ.

Body Break-Ups and Make-Ups: Medicine as Metaphor in Soul and Body II and the Metrical Charms | Jenny Boyar, Univ. of Rochester

Session 122: Theory and Practice of Medieval Medicine
Political Profs.: The Medical Faculty of Late Medieval Bologna | Kira Robinson, Univ. of Alabama–Huntsville

The Evolution of Medicine in the Medieval University Curriculum | Michelle Fitzsimmons, Univ. of Missouri–Kansas City

Prophylactic and Therapeutic Plague Recipes in the Household Book of an Early Tudor Noble Family | Linda Ehrsam Voigts, Univ. of Missouri–Kansas City

Session 142: Reading Body Language: Digestion, Boundaries, and Community in the Middle Ages
Waste Management: Communal (In)Digestion in the Old French Fabliau Les trois dames de Paris | Stefanie Goyette, Harvard Univ.

Canterbury Bodies | Merrall Llewelyn Price, Western Kentucky Univ.

Constructing and Consuming Communities: An Examination of Medieval Bodily Consumption between Mothers and Children | Mary Zaborskis, Univ. of Pennsylvania

Menstruation and Purgation: Salvation of the Communal Self in Anglo-Saxon Female Religious Communities | Marybeth Matlack, Cornell Univ.

Session 144: Food and Violence in the Middle Ages II: Diets That Make (a) Difference: Food, Violence and the Religious “Other”

Not Fighting Fare: Debating Taste in Inquisitorial La Mancha | Madera Allan, Lawrence Univ.

“What, is Sarezyns flesch thus good?”: Cannibalism and the Humors in Richard Coer de Lyon | Sonja Mayrhofer, Univ. of Iowa

Violence and the Soul: The Penitential Diet in the Spanish Middle Ages | Martha M. Daas, Old Dominion Univ.

Session 147: Mental Health in Non-medical Terms
Mental Disability and Intellectual Impairment in the Middle Ages: Some Preliminary Research Findings | Irina Metzler, Swansea Univ.

Man Bites Dog: Alarming Effects of Medieval Animal Venom | Kathleen Walker-Meikle, Univ. of York

Going Mad in French: Royal Notaries and Charles V’s Translation Project | Aleksandra Pfau, Hendrix College

Civic and Religious Understanding of the Mentally Ill, Incompetent, and Disabled of Medieval England | Wendy J. Turner, Augusta State Univ.

Session 171: Technical Communication in the Middle Ages
Cookeries as Technical Literature in Late Medieval England and France | Sarah Peters Kernan, Ohio State Univ.

“A Comyn Rule in Cure”: Medieval Cookbooks as Technical Writing | Mary Frances Zambreno, Elmhurst College

Repurposing the (E)MEMT Corpus and Presenter Tool: Identifying Trends and Transitions in Page Design and Genre in Late Medieval through Early Modern Medical Texts | Susan Rauch, Texas Tech Univ.

Session 272: Fourteenth-Century Health Care
Pharmaceutical Traces: Textual Traditions of Drugs in the Late Middle Ages | Fred Gibbs, George Mason Univ.

Critiques of Medicine and Critiques of Astrology in the Fourteenth Century | James Byrne

Health Crises in the Mediterranean: State Prevention and Responses | Alexander F. More, Harvard Univ.

Session 340: Monsters II: Down to the skin: Images of Flaying in the Middle Ages
A Window for the Pain: Surface, Interiority, and Christ’s Flagellated Skin in Late Medieval Sculpture | Peter Dent, Univ. of Bristol

Getting under Your Skin: The Monstrous Subdermal | Derek Newman-Stille, Trent Univ.

The Flaying of Saint Bartholomew and the Rhetoric of the Flesh in the Belles Heures of the Duke of Berry | Sherry C. M. Lindquist, Western Illinois Univ.

“Lo, his flessh al be beflapped that fat is”: From Flagellation to Flaying in the English Cycle Passion Plays | Valerie Gramling, Univ. of Massachusetts–Amherst

Session 348: Multilingualism in the Middle Ages III
Code Switching in Medical Recipies | Susanna Niiranen, Jyväskylän Yliopisto

Session 475: Plants in the Middle Ages: Between Philosophy and Medicine
Roger Bacon and the Vegetative State | Jeremiah Hackett, Univ. of South Carolina–Columbia

The Old English Herbals and Faith-Based Healing Practice | Warren Tormey, Middle Tennessee State Univ.

Albert the Great’s On Plants and Late Medieval Natural Science | Iolanda Ventura, IRHT–Orléans

Session 509: Violence and Warfare in Late Medieval England
The Politics of Battlefield Medicine | Ilana Krug, York College of Pennsylvania

Session 510: When Women Fight: The Ideal, Reality, and Idealization of Female Aggression in the Middle Ages
Consorting with the Devil: Interpreting Aggressive Female Actors in Old English Medical Texts | Erin E. Sweany, Indiana Univ.–Bloomington

Session 514: New Voices in Anglo-Saxon Studies II
Lay Access to Medical Resources in Anglo-Saxon England | Julia Bolotian, Univ. of Cambridge

Session 579: Low German Medieval Literature II: Medicine, Weltchronik, History, Osterspiel
The Manuscript Version of Hans von Gersdorff’s Feldbuch der Wundarzney in Copenhagen GKS 1663 Quart and Its Relation to the Printed Tradition | Chiara Benati, Univ. degli Studi di Genova

Digital History

Session 16: Taking It Public: Programming, Pedagogy, and Outreach (A Roundtable)

Session 32: Interdisciplinarity Now
Interdisciplinary Reading: Negotiating Sir Orfeo in a Digital Age

Session 50: Publish, Don’t Perish
Monographs in a Digital Age | Hans Christoffersen, Liturgical Press/St. John’s Univ.

Session 80: Emblem Studies
Emblems and the Digital Humanities | Sabine Moedersheim

Emblems and the Web 3.0 | Wim van Dongen, Vrije Univ. Amsterdam

Session 204: Collaborations: The Multi-lingual Classroom, Text Editing, and New Media (A Poster Session)
The Virtual Palimpsest: Teaching Students to Read Middle English | Andrea R. Harbin, SUNY–Cortland, and Tamara F. O’Callaghan, Northern Kentucky Univ.

How to Edit a Text in Collaboration with Everyone | Peter Robinson, Univ. of Saskatchewan

Session 238: E-publishing and Medieval Studies (A Roundtable Discussion)

Session 271: The Sciences and Medieval Studies: New Approaches, New Questions
Hypothesis Testing in the Humanities? A Digital Contribution to the Debate on Early “Germanic” Identity | Christopher M. Roberts, Arizona State Univ., and Sean M. Bergin, Arizona State Univ.

Session 272: Fourteenth-Century Health Care
Pharmaceutical Traces: Textual Traditions of Drugs in the Late Middle Ages | Fred Gibbs, George Mason Univ

Session 283: Critical Remediation: Intersections of Medieval Studies and Media Theory
The Digital Scribe: A Riddle | Yin Liu, Univ. of Saskatchewan

Mapping Social Networks: An Ordinary Habit: Remediation of Dutch “Alba Amicorum” in Today’s Social Network Mapping Services | Sophie Reinders, Radboud Univ. Nijmegen

Rethinking Anglo-Saxon Epistolarity | Jordan Zweck, Univ. of Wisconsin–Madison

Session 382: Blogging the Medieval(ist) World (A Roundtable)

Session 500: New Developments in Digital Resources on Medieval Austria, Germany, and Switzerland
Digital Resources on Things in a Domesticated Space | Ingrid Matschinegg, Institut für Realienkunde des Mittelalters und der frühen Neuzeit, Österreichische Akademie der Wissenschaften

The vHMML Project: At the Crossroads of Digital Humanities and Manuscript Studies | Matthew Z. Heintzelman

Session 547: Digitizing Saintly Space: Barking Abbey
Barking Abbey: A GIS Map of a Medieval Nunnery | Donna Alfano Bussell

Tracing Sacred Pathways: Processions at Barking Abbey | Kay Slocum, Capital Univ.

Session 549: Doing Things with Manuscripts
Emerging Technologies and Medieval Literary Networks: Finding Machaut’s Readers | Deborah McGrady, Univ. of Virginia, and Rachel Geer, Univ. of Virginia

Session 578: The Scribes of Medieval English Manuscripts: New Knowledge, New Technologies
Textual Problems and Progress: Some Incidental Findings of the Dictionary of Old English, Digital Mappaemundi, and the Parker on the Web Project | Alex Fleck, Centre for Medieval Studies, Univ. of Toronto/Dictionary of Old English, Univ. of Toronto

“When you don’t have a second pair of eyes nearby that can give you a sense of what you’ve done, sometimes it helps to trick yourself into seeing your work in a new light, by printing it out, changing your font, reading your work out loud.”

This quote from Aaron obviously addresses the trouble we have getting out of our own heads, even when we’re reading words on a page. The technique of reverse outlining provides a new perspective, in which you might end up “doing a little math” to recognize that you’ve written too much or too little about something—even when you thought (=assumed) you had done otherwise.

At least at first glance, a technique like reverse outlining applies more to revision than to research itself. After all, historians have become very comfortable at making sense of their sources when that means deciphering words in sentences: we like to think about who wrote them, their motivations, and the extent to which we can take that person and those words at face value. We think we’re good at it, and we have a certain cluster of letters after our name to prove it.

But the process of reading is hardly less biased when we’re reading historical sources than when we’re reading our own work. This is true because we are, in no small way, making those historical sources into our own work. It’s also true because just as reading something we’ve written inadvertently triggers neurons to make us read or think something that isn’t evident in the text itself, reading historical sources makes invokes the same kind of ancillary conceptual framing that lends an inherent bias to our reading, no matter how strong our drive toward objectivity.

It’s hardly necessary at this point to dredge up the debate about historical objectivity. But if we’re serious about reading as objectively as possible, then why not embrace multiple ways of reading? To embrace digital history is to expand what it means to read a text.

Just to be clear, I do not mean that we should necessarily embrace a kind of distant reading that assumes one has lots of historical data/texts that must be analyzed. Despite all the rhetoric about distant reading and big data, they are often totally irrelevant to what most historians do. But other ways of reading sources are useful regardless of how many sources there are. Allow me to provide a trivial but informative example.

How many times a word appears in each of 5 documents

As part of my “programming for historians” course last semester (#clio3), we had more than one occasion to think about the representation of texts. We drafted a rough but instructive tutorial on representing documents with R. When I first contemplated the goal of creating document matrix (and how it could be considered a corpus) my reaction registered somewhere marginally above abject disdain. This matrix is not a corpus; it is a grid of numbers. Obviously, this was just another example of some computer scientists over-simplifying complex humanistic data to numbers again. Everyone obviously knows that a matrix and a set of texts are different things! Why pretend otherwise?!

Another view, with the axes reversed

Of course this knee-jerk response is exactly why so many historians remain skeptical of embracing new methodologies, even as they would whole-heartedly agree that a reverse outline—just another representation of a text—is a good way of forcing a new and productive reading of an old (or too familiar) text.

It was only in creating a document matrix myself when I started to understand more of the steps behind it and to see the numbers as a perfectly nice representation of the text itself. To be clear, I did not have a Matrix-like Neo moment when I could move seamlessly between columns of green characters scrolling up my terminal console and the words in the individual documents themselves. That would actually defeat the point, anyway. (I can, however, stop bullets in mid air.)

Frequency of words appearing across all documents

I began to see the document matrix as a perfectly valid representation of the text itself—a version that could be read in a different way from the other representation I had (the documents themselves). This wasn’t really distant reading; I was only using, like, 4 texts of a few sentences each for the purposes of completing the tutorial.

I could compare texts in new ways; I could see them in different ways, especially in terms of what was connected to or related to what. I realized that I could read them in different ways.

I imagine that a typical historian’s response to the idea of reading a document matrix or other visualization is to reject the presumption that a grid of numbers should be considered a text or a set of texts at all. We tend to assume we know a text when we see it (even considering its many possible forms), and a document matrix simply isn’t one. But it’s the interpretation that matters and there is plenty of room to interpret a matrix or any other representation—just as much as reading words in sentences.

I suspect one reason that such a numerical approach to texts incites fear and loathing in most humanists is because of a totally erroneous assumption of reliability, a fallacy predicated on the notion that calculations or statistics are inherently less ambiguous than the hermeneutics of language. Such a position also usually assumes that something like a document matrix should be considered as a de facto “analysis” of the texts—yet one that we can’t really trust because computers are notoriously bad with extracting meaning from human language.

Just because we can’t extract the same meaning(s) from a representation in the way we might from a traditional text does not mean that representations can’t be read.

We must distinguish between representing texts and extracting meaning. Although it can be said that a scatterplot of word frequencies offers a numerical analysis of sorts, it does not pretend to offer a humanistic one. Rather, it less ambitiously provides another representation of the text itself. A chart of word frequencies or a list of topic models is no more or less authoritative a reading than using the words themselves. Of course what’s interesting about the words is the ideas they represent. But the same goes for any representation, including how one can get new ideas about what a text “means” by inspecting the statistical relationships between words and documents. Obviously it’s no substitute for “real” reading, but that’s precisely my point, and the whole motivation for something like reverse outlining.

One could argue that any such transformation has corrupted the original text so much that the original and essential meaning has been irretrievably lost. But haven’t we yet unyoked ourselves from the imperative to discover the essential meaning in any text? Do we not all read things differently anyway? Don’t multiple readings aid in analysis?

As everyone should know by now, looking at visualizations of texts is a form of exploring and should be taken not as analysis, but exploration. One might respond, then, by saying that a document matrix on dendrogram that shows word relationships cannot be read, although perhaps it can be explored. The traditional historian might then reply that exploring is fine, but eventually one has to read, because that is how we make true sense of things. Also fine.

But this view is okay only as long as we recognize that there are lots of ways of reading that don’t involve looking at words in some predetermined order. We must train historians not only to embrace exploration, but also to embrace multi-modal ways of reading—ones that are not necessarily exploratory, or at least no more so than the traditional act of reading itself. Art historians, for example, often read images, not just explore them. Those images don’t tell the whole story, nor do a set of topic models, nor does a text.

It may be tempting to call such a digital reading a distant or perhaps abstracted reading—one that isn’t connected to the text and therefore less useful. However, something like a document matrix is arguably more connected to the original text because its bias and presumptions stem directly the algorithms and whatever dials and knobs the reader has fiddled with during the course of “reading” with a tool like R—if only our own biases in reading could be known or changed so easily! Of course these biases lead to misreadings, but only in the same way that our regular ways of reading do. Let’s just be honest: all ways of reading are flawed. It’s silly to discard a technique because it doesn’t automatically reveal the same relationships that we expect when reading traditionally.

Most of the debates of the merits of distant reading have focused on the distance rather than the reading. The common language used to describe the step of understanding statistical representations like a document matrix is to “interpret the results.” There may be unfortunate consequences to approaching the problem in this way, namely in how it foregrounds a “result” of an analysis rather than creating a representation of a text that needs to be interpreted like the version of texts with words in it. There are no results to interpret any more than a paragraph of text is some kind of result. It is merely one possible expression of an idea.

How words are related to each other.

And more ways of reading increase our interpretive powers. To claim that mathematical expressions of texts have nothing to offer in the way of interpretation is to say that abstract and unexpected representations cannot provide useful readings—which is also to deny the fundamental premise of visualization and to embrace the fallacy of infallible readings. Please don’t.

Of course the elephant in the room wears a giant neon sign that reads: “So what?!” If these techniques are so great, why hasn’t anyone rewritten historical interpretations based on such techniques?

Revolution is unfortunately the litmus test for short-sighted skeptics.

But we’re still learning to read in this way. And my point is that new ways of reading are a good thing, even if such “text mining” techniques don’t immediately reveal the gold nuggets that everyone’s missed up until now. Multiple readings help us be better historians, regardless of whether one way of reading can be seen as (or actually is) “better” than another.

Looking at texts through tools like R is indeed a kind of reading in itself. Far from the presumption of objectivity, they embrace the hermeneutical fuzziness inherent even in a statistically-derived document matrix. As with traditional reading, there is considerable reading and interpreting to do be done even on numerical representations of texts. Perhaps thinking of it this way—as reading—can make it seem not like digital work, but simply historical work.

We can (and must) learn new ways of reading texts, and to embrace mathematical abstraction and visualization as interpretative allies rather than block-box enemies. The typical humanist creation of meaning from text is no less black-boxy that reading the text through mathematical lenses. These new ways of reading are not the savior of the humanities, and they do not guarantee new insights into anything. They may be utterly useless for your purposes, in the same way that trying to analyze sources through a Marxist or a Feminist lens may be totally unhelpful. But we expect good historians to carry a large bag full of lenses, and tools like R are just another one to bring various textual features into focus.

Early Lessons

A good first few weeks of any course are usually crucial for its success, but the stakes are even higher for this kind of course that builds on itself so extensively from one week to the next. Some of the most important things that the students taught me had to do with adjusting the focus of the first few lessons.

• Strong early focus on data manipulation/scrubbing techniques with standard command-line tools like vim, sed, grep and regular expressions. As a class we had the right idea (the topic was scheduled for the second week), but it should have been at least two if not three weeks, to build core skills and get data ready for the analysis or visualization lessons that come later on. I envisioned that we’d do a lot of data scrubbing with PHP and python scripts eventually, but in practice it simply took too long to learn how to do it effectively because many basic programming concepts hadn’t been covered yet. Besides, using regular expressions via one mechanism or another for cleaning up text files is often the best tool for the job, and can always be later integrated into scripts for reuse. Another reason I didn’t include these kinds of lessons is because I thought that they would be too specific to particular datasets and boring to everyone else. Even if that were true, it would have been valuable to spend more time early on general strategies and a few techniques for fixing systemic errors so it would be easier for students to learn what they needed throughout the semester (and hopefully blog about it).
• Incorporate a code repository like GitHub into the course workflow right away. Since the course was already over-ambitious, code repositories seemed like something that could wait. But actually using GitHub really emphasizes the practice of collaboration and encourages thinking about working on larger projects even if the course is mostly about individual or small group projects. In our case, using gists proved invaluable for sharing code between everyone and staying organized, which can be deceptively difficult. In retrospect, it would have been better to formalize and standardize this process early on. Doing so would have made our communal efforts at debugging easier as well.
• Spend more time with jQuery and Javascript upfront. There was not necessarily a lot of interest in them when we first (but too briefly) discussed them (fairly early in the course). But once we played with the D3 visualization library for a bit and began to better appreciate what Javascript and its code libraries can do for manipulating data and visualization, students became much more interested. But by this time, end of the semester deadlines loomed large, and we weren’t on solid enough footing to take full advantage of them. With more attention on the Javascript basics, visualization lessons can focus on cooler problems than the language mechanics.

Systemic Improvements

• We needed more short assignments/challenges each week that clearly focused on developing certain skills or addressing clearly-defined problems. I figured that such assignments would be too frustrating even for highly capable students with a wide range of experience and interests and ongoing digital projects. In a future version, it may be worth trying larger group programming assignments that would effectively require students to be constantly sharing and updating code.
• I should have given a specific deadlines and concrete examples for students who needed to create their own datasets. Even before the course started, I encouraged students to accumulate data that would be useful to them, but I didn’t give them or have for myself a clear idea of what formats would be useful for later lessons/assignments on data mining or visualization. I should have emphasized more that the course was never about big data but rather extensible data—about learning and reusing techniques for adding and managing data rather than analyzing gigabytes of it—with the hope of not making it seem like anyone had to put together a lot of data to use for the course. It also would have been helpful to provide sample historical data for students whose own projects did have any readily available so that they can jump into assignments without feeling confused as to how they can use a specific technique.
• It might be better to forgo a “final project,” which I assigned with hopes that it would serve as a rallying point for students’ work and would be an extension of their dissertations. But it became something to worry about in its own regard, and somewhat discouraged playful exploration of technologies or techniques that obviously wouldn’t have been a part of it. This limitation imposes itself less at the beginning of the course when everyone is optimistic about everything, but it becomes a much larger burden as the semester begins to wind down.
• Instead, the class sentiment was that students should divide into groups according to their digital needs and interests. As a whole, students would systematically build up one or maybe a few larger projects over the course of the semester; small groups could be formed to tackle certain aspects of it. I contemplated doing this even this past semester, but thought it would be too frustrating for students to work on projects that were not their own. The students made the very important point that not being able to work on something immediately (many lessons were not immediately applicable to their own projects) requires time later to review and maybe relearn course material. This kind of approach would also make it imperative to introduce source code version control and best practices of social coding.

Lastly

To end on a positive note, I’ll close with one thing that worked well and will continue next time: Having students create tutorials and present introductions to various topics. This proved valuable and useful not only as learning experiences for the presenter/blogger, but also in creating course resources that people were able to refer to and use throughout the semester. No one was expected to become an instant expert, but rather act as a guide for getting started with a new technique. Tackling unknown technologies was encouraged; I tried to make it very clear that part of the expected course work is to fail, and that when students got stuck they should stop and blog about it. Many of them eventually solved their own problem, but even if not, that’s fine. Explaining the problem helps other people in their own work and the act of writing it out helps the author as well. I hope the students are as proud of their work on the course blog as I am.

This post was originally published as “Riding the Bicycle of Kuhn’s Structure” in Historical Studies in the Natural Sciences 42.5 (2012): 510-513.

To say something is “like riding a bike” suggests intuitive learning and the acquisition of lasting, tacit knowledge. Any task that may be thus described remains difficult to teach explicitly, though some instruction may dampen the learning curve. There is a definitive moment of realization: no training wheels, no hand on your seat; you are on your own! Yet, after experiencing some success, you might struggle to explain exactly what you’ve learned. It’s not just about steering, pedaling, or balancing, but some fuzzy and virtually inexpressible connection between a few crucial forces. Both the process and product of such learning can be remarkably transformative and empowering. The same should be said for learning about Thomas Kuhn’s The Structure of Scientific Revolutions.

The students in my graduate seminar on early modern science and the so-called Scientific Revolution are most likely to study American history. For most of them, my course will likely be their first and only exposure to the history of science. To make the course useful to these students, most of whom have widely varying backgrounds and generally no intention of pursuing academic careers, broad and accessible themes must take priority over the most recent specialized scholarship. When I first describe such priorities and the contours of the course, virtually every colleague makes some comment or query about SSR. I hear over and over again: “Oh, Thomas Kuhn!” Some simply assume that no course on the topic could be complete without Kuhn’s text—perhaps a tight-fisted clutching of an outdated prelim reading list. Others inquire with a morbid curiosity about whether it would appear on the syllabus—as if I were indoctrinating a coven of necromancers with an injunction to brew toad stew on the Sabbath.

Although historians of science rarely engage in such infamous (if unfounded) Paracelsian bombasts as burning the historiographical canon to make a point, both the premise of Structure and its role in history (of science) education continues to encourage a plurality of polarized opinions. Considering that SSR has already been the subject of countless refutations and revisions, one might be forgiven for believing there is nothing else to say about SSR’s fundamental premise other than it’s wrong and we should simply move on. What use could there possibly be in teaching outdated and outmoded scholarship?

Even fifty years later, SSR is hardly academic pedantry. The basic premise of the book is something novice history graduate students already know about, many of whom assume the veracity of scientific “paradigm shifts” whether they’ve heard of Kuhn or not. Like the many fictitious scientific “revolutions” that have been convincingly but unevenly dispelled (though still occasionally held up as straw men), Kuhn’s ideas, if not the text itself, remain entrenched in popular, if not in specialist, discourse. Such persistence demands, at least for now, a pedagogical responsibility to engage with SSR and its legacy.

Historical selectivity and superficiality aside, Kuhn effectively and convincingly outlines the (a)historical appeal of puzzle-solving normal science and, at least when we’ve adopted an incorrect or inappropriate paradigm, the inevitable outliers that drive paradigm revision and eventual abandonment. One can hardly fault Kuhn for his effort: even the most cynical historians take some delight in explaining complex processes with straightforward models, even when accompanied by reductionist unease. For better or worse, I try in my course to explore both the historical and historiographical constructions of the Scientific Revolution by starting with traditional assumptions and thematically deconstructing them. SSR and the discussion (and research) it provoked have proved most effective partners in this regard. As historians and sociologists of science have teased apart the subtleties of Kuhn’s thesis, the ensuing debates over the nature of scientific revolutions have themselves become unusually interesting and educational.

I am occasionally panicked by grave doubts about assigning what is arguably a defunct text, especially when most of the course is, at least indirectly, devoted to complicating and/or invalidating it. Am I trying to teach my students to ride an antiquated, iron-tired Boneshaker? Ultimately (and thankfully) the students have reassured me that they appreciate and in fact need its organizing function. One could say that SSR occupies the heart of the course. But, with a course more proximately concerned with early modern science in general, perhaps it is more accurate to say that it functions—and performs admirably well—as a base of operations. It provides easily accessible points of departure for various underlying themes that repeatedly surface across many topical discussions about early modern science, such as assumptions and perceptions of theory choice, disciplinary differences across various scientific fields, and the (in)utility of generalizing about motive forces of scientific “progress.” Needless to say, these are lessons that could be learned from a variety of sources. But for a more or less introductory course on the history of science, it remains inordinately effective and efficient. And this is perhaps the principal reason why SSR itself (paired with a supporting cast of dissenters)—as opposed to more recent books on the scientific revolution or scientific change that aren’t nearly as ambitious—remains an indispensable tool in the classroom.

Of course, even once the basic premise of riding a bicycle is internalized, cycling experiences vary wildly. The briefest experience jetting around on a 2012 titanium racing kit could hardly be more dissimilar from cruising along on a 1974 steel Schwinn Collegiate. It is almost unfair to conflate them as the same activity. SSR, too, offers a rare variety of experiences for diverse student interests. For example, Kuhn deliberately challenges the boundaries of history, philosophy, and sociology—with each camp seemingly crying foul in response— an important case study for those who intend to cultivate a cross-disciplinary identity in their careers. Yet Kuhn also turns repeatedly to science education to explain the persistence of scientific models, an oft-neglected component of the scientific enterprise that has appealed to my students who intend to pursue careers in education. For an entirely different audience, Kuhn’s big-picture view of scientific change provides an indispensible historical perspective for analysis of any particular episode (like the Scientific Revolution), as well as the broader terms and categories that can fruitfully (or not) frame such analysis. What students take away from SSR thus varies, but the text functions as a remarkably versatile platform and organizing principle, much like a first bicycle ride.

Larger lessons from SSR extend far beyond scientific revolutions; they also reflect profitably on the processes of historical change. As Kuhn’s respondents have demonstrated, the notion of a paradigm shift—which could be applied to a variety of vocational or intellectual phenomena—is historically visible at only certain scales and under unfairly controlled conditions. Even if ephemeral, it remains heuristically useful. Not long ago I participated in a Library of Congress workshop on archiving online science content where one participant wondered whether archivists now faced a “paradigm shift” to cope with new kinds of materials and collecting processes. Everyone in the vocationally varied audience understood the question and its implications to be a essentially a question of “out with the old, in with the new.” But of course it’s not that simple. Examining SSR and the responses to it cultivates a finer eye for continuity and discontinuity in times of ostensibly revolutionary change, as well as a more sensitive awareness of the implications of speaking in terms of paradigms and intellectual adaptation.

In the broadest possible sense, assigning SSR facilitates exemplary engagement with a “classic” and influential text—including its reception and criticism—that ought to remain a crucial aspect of higher education. If there is one thing that Structure did, it was to generate conversations that remain salient. My students have savored engagement with a culturally relevant text, even if it is no longer academically en vogue. More specific to my own use of it, SSR provides a case study in how historical studies of science are produced under certain intellectual, social, and ideological conditions that reflect instructively on the history of science itself. Of course all texts are produced under various conditions that inform them, but SSR’s preface and postscript (in the third edition) reveal an unusually clear meta-level of historiographical context. These considerations, coupled with the way Kuhn makes an explicit argument for the importance of understanding the history of science and knowledge production, can then be easily applied to contemporary reflections on scientific practice—an indispensable goal for my history of science courses.

By the end of the course, the process of analyzing SSR—including the text, its relationship to the history of science, and its legacy—indeed compares favorably to learning to ride a bike. Students struggle to articulate exactly what they have learned; I can count on wide disagreement as to the definition of a scientific revolution, the extent to which it’s a useful construct, and whether such a thing is even possible. Yet, the students insist that they’ve learned something empowering if not transformative. Most importantly, they are able to peddle out on their own, each on their preferred kind of bike. They perhaps ride away from SSR itself, but (as they usually indicate) they happily steer toward further reflection on the nature of knowledge production. They acquire an intuition about how different communities—whether scientific or historical—identify and solve problems in their field, as well as gain new perspectives about their own role in that process. Sure, they’ll crash from time to time. But I have a feeling they’ll keep riding.

I wish to thank Erika Milam and Michael Gordin for the invitation to indulge my bicycle fantasies; their perceptive feedback produced a much clearer essay. I must also thank Shannon Withycombe for serving as an indefatigable soundboard and for encouraging me to keep my hands dirty.

Need a portable version? Download the PDF.

There remains a strong tendency to save only what is deemed as “good” science, which seriously reduces future historians’ ability to understand the character and boundaries of science.

A few months ago, a short workshop convened by the Library of Congress addressed the problem of preserving “science at risk.” It focused not on scientific data or official publications, but rather on what’s called gray literature—writing (in this case about science) that falls between the archival cracks—including sources like science blog aggregators, citizen science projects, open notebook scientists, reader comments on newspaper articles about science, and even individual blogs. Obviously, all of these will prove to be fundamental resources for future historians of science who will then have a much greater record of what people thought and wrote about science.

Or will they?

Only if we are casting as wide a collection net as possible. This is not a challenge related only to location (where to look), or of quantity (how much to save), although of course those are relevant concerns. One of the greatest challenges hinges on overcoming our traditional criteria employed when making difficult value judgments of quality. Needless to say, curators and archivists, are unable to save everything and must make difficult decisions. But, as the workshop clearly demonstrated, there remains a strong tendency to save only what is deemed as “good” science, which seriously reduces future historians’ ability to understand the character and boundaries of science.

Selecting science

One of the supposed achievements of the so-called Scientific Revolution is the move toward openness and transparency. Experiments had to be demonstrable and repeatable; the cryptic esotericism of alchemical mysticism had been replaced with the matter-of-factness of the publications of scientific societies. The task of understanding nature had been wrestled from the stodgy and traditional university natural philosophers and put into the hands of the people. In reality, though, science was a gentlemanly sport, and without the proper social connections, your fabulous eyewitness observation was unlikely to find a sympathetic ear, and would certainly not find its way into the pages of the Transactions. Those at the highest ranks decided, through entirely understandable and defensible means, what was science and what wasn’t. This selection of good or bad science makes sense in this context, even if we might quibble with some of their criteria.

Needless to say, selection processes are still important. Even if one believes that storage space is cheap, and simple file formats are likely to be available many decades from now (as many already have been), such content needs to be not only collected and stored, but also made useful and visible, a process that takes substantial human work, even if the process can be heavily automated. Of course, the work of collecting, organizing, making visible, and making available is simply impossible given the magnitude of digital material and increasingly limited resources to conduct these complex processes.

I argue here, from the point of view of a historian of science (and to some extent of a digital historian), that librarians, curators, and archivists must address the difficult question of what content to save with three important but often neglected considerations in mind: the varied audience for science content (e.g. scientists versus historians), the importance of collecting science content that departs form what might be considered good or mainstream science, and the changing nature of archival use. Throughout, I emphasize the role that historians of science have to play in making archivists aware of their questions and sources.

Varied audiences

Science at Risk workshop participants agreed that it is helpful to think of three stages of archival life: creation, near-term, and long-term. This tripartite scheme nicely encompasses the varied challenges of 1) collecting from diverse sources that employ diverse technologies; 2) making such content immediately available for immediate research needs, and 3) preserving it for posterity and future reference.

In the long term, historians—especially historians of science—will benefit most if collection development is made with both scientists and historians in mind.

In addition to this scheme, we also must consider the different audiences that will benefit at those various stages. In the near term, other scientists and perhaps policy makers will likely be the primary audience—and thus dictate near-term strategies both in terms of what to collect and how it should be made visible and available. In the long term, however, historians—especially historians of science—will benefit most if collection development is made with both audiences in mind. While there is substantial overlap in the kinds of materials that each group will be interested in, there are significant differences that must factor into collection strategies.

The disciplinarily diverse audience and presenters at the Science at Risk workshop showed they are actively creating and curating online science content according to their varied needs and interests. Workshop presenters associated with science blogging or citizen science projects, for example, demonstrated their distinct interest in preserving discussions about current science issues, whether from professional scientists or science enthusiasts; their content ranged widely across natural philosophical discussions, methodological questions, historical essays, or arguments about what species of bird appears in a particular photo. Open notebook enthusiasts demonstrated their interest in preserving a narrow but deep view of science in action. There is no doubt that all of these constitute sources worth saving. Such sources will be of use to scientists (or civic scientists) struggling with similar problems; parts will be useful for historians who want deeper insight into the messy processes of science that do not emerge from official and polished publications.

Yet for these generators of online science content—as seemed true for many participants at the workshop—the emphasis of what was at risk leaned heavily toward what the creators and managers of these resources, as well as those tasked with archiving such sources considered to be “good” science. There is no question that, when considering the near term use of scientists or future historical uses to learn about mainstream science, archives of content from publications like science blogs and open notebooks will prove to be fantastic and largely unprecedented resources.

It would be deeply problematic for future history of science research if content selectors focused on preserving a narrow—and to some extent arbitrary—selection of content that a particular set of insiders thought was “good.”

Longer-term archival materials, however, are useful to a rather different audience that does not share the same agenda as many creators of online science content. From a historian’s perspective, it would be deeply problematic for future research if content selectors focused on preserving a narrow—and to some extent arbitrary—selection of content that a particular set of insiders thought was “good.” Of course it is true that historians’ ability to understand and interpret the past will continue to be mediated by the stewards of our cultural artifacts: librarians, curators and archivists who, laboring under various practical constraints, must often save what is or will be of obvious value. This value is often determined by the context in which it is collected. Science content, then, is likely to be collected because it reflects upon the activities of a recognized scientific community and is said to constitute “good” science.

Yet some of the most fascinating work from historians, philosophers, and sociologists of science examines how societies (at various levels) demarcate science from non-science or how various communities embrace (or not) various explanations or theories. Such research often attempts to establish the ways in which historical actors determine the boundaries of science, or to examine how historians have chosen to portray them. Being able to determine the boundaries of science, regardless of their epistemological origin, are entirely crucial to the success of these historical efforts. As a result, thinking about such future historical use should encourage different kinds of selection processes from those that have been previously employed. Archivists and curators must select the broadest possible spectrum of science content that represents a wide range of attitudes and understandings about science, even when they contradict what would be generally considered good science. In other words, we must prioritize breadth over depth even when limitations on the content collection process do not allow a more cohesive or thorough cataloging effort. It will be helpful to broaden the filters, even if the catch from a wider net cannot be fully processed or cataloged per the usual rigor. Historians are gaining greater facility with processing such mountains of data and in fact need less parsing done for them.

Archivists and curators must select the broadest possible spectrum of science content that represents a wide range of attitudes and understandings about science, even when they contradict what would be generally considered good science.

For example, we must actively preserve materials that can easily be labeled as pseudo-science, including creationist blogs, anti-climate change blogs, and generally science-skeptic blogs, regardless of their religious or political motivation. For the historian of science, the historical record that outlines ideas and attitudes about creationism, phrenology, and alchemy have been just as important as those that outline evolution, psychology, and chemistry. Similarly, science bloggers (and sites that aggregate such content) often publish invectives against what they consider pseudo-science or bad science. If collected together, they provide an unusually complete discourse around science in the popular realm. To attempt to separate “real” science and knowledge claims from the complex interactions of politics and science is to ignore or deny the vast historical analyses that reveal the social and cultural constructions of science and judgments about it.

One facet of the historical record that historians of science never seem get enough of is the “popular” attitudes, views, and understandings about science. In terms of targeting specific content, these might include blog posts and user comments about—and especially in response to—scientific or science policy articles that run in online newspapers, or other web periodicals with web forums of some sort. For example, the line of violent storms that swept through much of the eastern half of the country in the summer of 2012 were the subject of numerous newspaper articles that prompted user comments that mentioned climate change as a possible explanation for the rare storm system. Many comments (perhaps in a coordinated effort) explicitly challenged any connection between global warming and severe weather or the scientific status of man-made climate change. This is a wonderful and new (historically speaking) venue for getting at a variety of attitudes about science, including the kinds of arguments people do or do not not make in the course of such debates about the viability or applicability of certain scientific theories. And it perfectly exemplifies the so-called gray literature—writing that does not fall into traditional archival categories—than can be easily neglected, especially by scientists and others interested in promoting “real” science, which can unfairly minimize the voices of those who do not agree with it.

Especially if the mainstream science blogging sites or other official publications turn their back on what they deem as “bad” science, both historians of science and the cultural heritage community must redouble their efforts to capture this rhetoric.

Especially if the mainstream science blogging sites or other official publications turn their back on what they deem as “bad” science, both historians of science and the cultural heritage community must redouble their efforts to capture this rhetoric. This would, for example, allow future historians to see how effective such rhetoric was at important political moments, how it has changed, or how it correlates with other data, like demographic or election data. It can provide a fascinating window onto a much broader scientific discourse that lies outside the typical venues of official science publications. But of course the broadens the collection net even further, which is where historians of science must be more vocal about not only what kinds of sources they use, but also what kinds they want.

Apart from the discourse itself, one of the potential values of science content captured from online sources is to help historians to understand the wide diffusion, perhaps even the popularization, of scientific knowledge. To study (at least effectively) larger social phenomena such as diffusion, though, requires careful and relatively precise metadata about the content, such as when and where a particular post or comment came from—information that is sometimes not visible on the webpage where the content resides. Historians will hope for as much metadata as possible, and their analysis will be as rich as the metadata is complete. As websites may balk at collecting and/or sharing data about posts, archivists are seriously limited when working only in content-ingestion mode. Rather, librarians, archivists, and curators must work with content providers to capture as much metadata about the posts as possible (even if not publicly visible, such as IP addresses that reveal geographic data) in a way that is sympathetic to privacy concerns without being a slave to them.

When trying to understand the diffusion of scientific knowledge, not only is content essential, but also important is some sense of its influence. One obvious example would be to capture the viewing or download statistics for various publications, or perhaps how often (and when) it was posted to Facebook or retweeted. But the many kinds of statistics that one might find associated with a particular online publication (and thus might want to preserve) do not necessarily overly complicate the archival process. It is important to remember collecting can be done in ways that preserve metrics without thinking too much about exactly what needs to be preserved. Websites, services, and publishers often display this kind of information on webpages that contain the original content.

Future researchers might use various text mining methods to understand influence of a particular blog or article and correlate it to other historical events—but this depends on having as much data and metadata as possible, not only what is prejudged to be of sufficient scientific quality

At the same time, it is also important to think about the ways in which diffusion might be measured in ways that are not already explicitly quantified and displayed on pages. Participants at the workshop repeatedly lauded the value of “alt-metrics” in measuring the value of scientific work or its uptake in the community. But once publishers start to foreground alt-metrics for whatever purpose—as they already have begun to do—then they are not really “alt” anymore, and thus they lose some of their value that they had when they were truly outside mainstream measures. Truly “alt” metrics are not, by definition, clearly visible. The implications for archiving–as with content–is to save as much metadata as possible, not just what is obvious value now. Of course it is difficult if not impossible to anticipate what future alt-metrics might be, and truly alt-metrics will comes from discovering new relationships between whatever combinations of data are available. And this is yet another argument for casting as wide an archival net as possible for not only content but metadata as well. Future researchers might, for example, use various text mining methods to understand influence of a particular blog or article and correlate it to other historical events—but this depends on having as much data and metadata as possible, not only what is prejudged to be of sufficient scientific quality or to have an established value for measuring diffusion. Certainly, such determinations will yield different kinds of historical analyses in the future.

Relationships between historians and cultural stewards

Lastly, I want to emphasize how we must facilitate new kinds of relationships that can help make preserving web science content a manageable enterprise. These grow out of the workshop conversations, but they maintain my bias as a historian of science.

The scholarly community must transcend the typical disciplinary divides between historians and archivists. In particular, historians of science are well positioned to make insightful recommendations about the kinds of science content that will be useful for future historical research. We can hardly rely on a few Subject Matters Experts (officially known as SMEs) to know of all possibilities across such a broad range of science disciplines and sub fields. There is simply too much to know. Even with the most vigilant efforts toward objectivity, the gravitational pull of mainstream science and higher-profile spaces of discussion remains strong.

Historians of science are uniquely positioned to know about useful alternative venues for science content that will be useful for historical purposes. Those engaged in science content preservation might reach out to a wide audience of historians and sociologists of science and technology to discover what kinds of sources they now use and what they hope their students will use in the future. They will be especially helpful for understanding how current historical research questions and answers would be different if certain kinds of materials would have been saved. Those who consider themselves digital historians are worth consulting as well, to understand growing importance of data, new techniques for exploring it, and future expectations of access.

Diligent archivists are now creating a historical record that has never been so rich. But there is no inevitability to its utility. Historians of science, especially those who are as much interested in the fringe materials around the mainstream notions of “scientific” literature, must take an active role in foregrounding the importance of the kinds of materials that they have almost always wanted, but almost never had.

Many thanks to Trevor Owens for suffering through and improving some earlier drafts of this. The full version of this report is here.

I fully agree with the idea that learning to program—especially for humanists—is more about shifting one’s mindset about interacting with code than acquiring any particular skills (ie attitude over aptitude). I fully agree with the sentiment that more people should know how make computers into their personal lackeys (yes, why don’t you parse and transform this 500,000 line text file and map all the place names while I get some coffee…). Yet as I read the post and thought about a course that I’m teaching for the first time this fall, which I’ve often described as “programming for historians,” something didn’t sit right.

Ramsay raised an interesting and difficult question for me: what do I want my students at the end of the course to think they know how to do? How should they describe their abilities? Should they say that they learned to program? To do some programming? To think like programmers? That they learned to hack?! (clearly NO on this last point, as I remain eager for DHers to drop the hacking trope.) In broader terms, I think Ramsay has raised important questions about pedagogical framing and disciplinary identity that anyone teaching technical skills to humanists should consider for themselves.

I wrote some time ago (less eloquently than Ramsay, of course) about the value of learning programming and the potential dangers of the term ‘programming’ for historians. The danger is that it implies an expected eventual level of competency that most historians will never have and don’t want anyway. On one hand, Ramsay’s post is a good argument for why I may be totally wrong about that: it’s not that historians can’t be or don’t want to be good programmers, but that they can be considered perfectly competent programmers without being highly skilled. On the other hand, perhaps Ramsay has only implicitly but essentially argued to expand the notion of a programmer to include anyone who applies procedural and step-wise thinking—or even harbors such desires—to computer code.

It’s true that good courses are more about expanding ways of understanding than imparting particular knowledge or skills. But is there real value in broadening the term programmer to include anyone who has monkeyed with a line of code? Or in encouraging budding humanists to think of themselves in terms of another field? I’m not sure that the students will be best served by thinking of themselves as programmers. And I’m not sure that they want to be thought of that way, either.

It’s helpful here to consider two separate components or stages of auto-didacticism: 1) barriers to the learning process; 2) self-evaluation during the learning process as to what you know and what you don’t. Ramsay wrote mostly and convincingly about the first. At the same time, he largely conflated the two. I think these should be more carefully teased apart. Ramsay rightly argues that the programmer label is irrelevant in the first case: you don’t need to consider yourself a programmer to start learning programming or to be doing programming-like work. Absolutely. Yet it becomes relevant, appropriate, and perhaps necessary in the second case. Students who think like programmers effectively have learned to be programmers (even if not by the typical definition), and therefore shouldn’t feel awkward about doing things with code. They are in the club.

I couldn’t agree more with the first part. The worry that one is not a programmer, or cannot become one, should not dissuade anyone from learning how to customize a WordPress theme or write command line scripts to parse a text file. But my unease with the label is less about skills and more about identity and the way students need to be able to describe what they do. What is at stake to identify (either internally or externally) as a programmer? It means something to say “I know programming” or “I’m a programmer.” I think it’s useful to reserve such labels to imply a minimum level of competency.

If someone tells me “I’m a historian,” I take that to mean that they know how to frame original research questions, find sources to answer them, and analyze them in methodologically sound ways. I understand this is no claim to competence, but I do not expect that it means simply that they read history books from time to time. When someone tells me they are a programmer or that they program, I take that to mean that they write code in the process of designing and/or troubleshooting relatively complex software. Even if they embrace their own insecurities and say that they program computers (like someone who plays the piano versus is a pianist), I still expect that they are doing more than applying some technical skills to literary or historical research.

Perhaps I have attached undue significance to trivial and possibly antiquated labels. But if everyone who could write a line of PHP code claimed programming skills, what would “real” programmers call themselves? I am willing to be accused of nitpicky semantic overkill or even programming snobbism (though anyone who has seen my code will readily attest that I am no programmer, nor do I claim to be), but it would be nice if these labels actually meant something and implied technical proficiency as well as state of mind. In other words, there is a threshold at which one can claim to be a programmer. But a willingness to manipulate code or change the width of your sidebar widget is far from that threshold. To say otherwise is to delude yourself and deceive others who probably embrace a more restrictive, traditional, and meaningful definition of the term.

But my point is not that labeling yourself as a programmer even when you’re starting out is bad or will be hopelessly confusing to everyone else. I mean to emphasize that it’s simply unnecessary—even if you keep that thought to yourself—and possibly detrimental in that it portrays programming as something outside humanistic vocations. Part of the problem is that it is and worlds are colliding (until 1:20). We don’t really have an adequate way to describe humanists who are able to manipulate code with some efficacy. It’s not part of established professional expectations, there is no niche society, and traditional vocational structures generally discourage it. Perhaps “programming historian” could work. But that, too, as a vocational description, sounds like you’re not a real historian, but a programming one.

But maybe we don’t need a new label. It might be better to think of writing perl scripts not as programming, but in fact on par with any required skill of a historian (or substitue other humanities discipline here). I can imagine that even the most digitally inclined historians can be put off by courses and assignments that seem too distant from their own field, even if they know they don’t need to become fully fledged computer scientists. Ramsay’s post helped me clarify my course goals in unexpected ways: I want my programming assignments to look like history assignments. I want to make programming—and in fact “the digital” in general—to be mundanely invisible. I need to consider my programming for historians course as an optional part 2 of the required methodology course.

Towards that end, I’m not sure I want my students to think of themselves as programmers no matter how much they learn or what their attitude towards manipulating code might be. I want them to think of themselves as historians who have an unusually high technical proficiency. And not because they won’t have learned enough or won’t be good enough to be considered programmers—Ramsay has nicely articulated why they might well be—but because it emphasizes a technical skill (or mindset) that can too easily be construed as sufficiently outside their own vocational identity, an outside skill brought to bear on an inside problem. I don’t want that dichotomy. They don’t need to consider themselves as programmers or coders to be at ease with their ignorance or abilities with code. After all, they will not be there to learn programming, but how to be pioneering historians in the 21st century.

In case you didn’t know, the previous title of my blog, historyproef, blatantly bastardized the Dutch word letterproef (sounds like letter proof), a sheet of type specimens once produced by printers. Type sheets were standard fare, but some Dutch examples I found in a catalog of stylistic exemplars immediately resonated with me because of their refined and elegant aesthetic and practical function. The form mattered as much as the content.

The name reflected my interest, especially as a historian, in combining creative design and expert production. Just as the specimen sheets served not only as a proof-of-concept for type faces and printing devices, they also served as proof of superior craftsmanship and originality in design. It’s unfortunate that historians too often feel that design must take a back seat to content, when the aesthetics of our work can be as intellectually engaging and as useful as the prose itself—and in fact can take advantage of representational freedom beyond words on a page can do.

So that was the hope. Here is why that hope evaporated, and why it proved an interesting experiment in online identity.

But why expose my warped logic and machinations about a trivial domain name that is often referenced and obscured by a shorted URL anyway? Some friends recently asked me about how they should choose a domain name for themselves, and I was forced to rationalize my embrace of an abstraction instead of something like the more obvious and now current domain name. I confessed—which they found helpful for their own thinking—that the safety net of abstraction had become annoying, if not a hindrance.

Some drawbacks I considered early on but dismissed. For example, it is not obvious that the historyproef URL that shows up on search results pages refers to me, if that’s what people are looking for. Yes, people found their way. But it’s unclear from abbreviated search result listings what exactly what the site is, anyway. Why add the extra step of cognition?

Other conflicts, which were more in my mind than online, were not as easily anticipated. But these, too, became evident over time. For reasons that I could never get entirely clear about, I wanted abstraction from my website. After all, it was a professional website (whatever that is), and I didn’t want it to be mistaken for the much more wholesome me, who wants you to think I do lots of interesting things that are not related to my job. (Do I really? Well, that’s not the point right now.) Even in professional terms, I wanted to uphold the illusion that my website is only a selection of what I’m working on. In other words, the website was not me.

I decided against the eponymous URL also because of how it emphasized that the grubby, practical realities of academics involve quite enough shameless self-promotion, thank you. I hardly needed to fan the flames with my own domain name. Maybe having arbitrary letters in the URL was a sneaky way of trumpeting my own achievements with looking like a braggadocio. Besides, wouldn’t it obligate me to post more? And not just professional work, but perhaps <shudder> personal tidbits as well? But I don’t want an incomplete online me!

I realize that the above two points are largely contradictory, which I can now use to help justify my previous confusion about what to do. I should emphasize, though, that I do not equate having an eponymous domain name with being an indulgent narcissist, and it does not seem the least bit weird to me when other people do it. But it seemed weird for me to do it.

Yet at the same time that I wanted to undercut a personal connection to myself, I wanted to aggrandize the site and its content. I wanted it to be something larger than myself (and not just by characterizing my online presence as an organization). I really can’t say why. Was it an unconscious way of artificially inflating my shriveled and immature ideas? Was it to foster an illusion of objectivity? I had a new job and was trying work my way into a new field. Maybe I was scared. Maybe the head fake of an obscure domain name perfectly exemplified my academic insecurity. (Even if you think so, don’t think that my move away from it signals a triumph over such anxiety.)

If you think that I was overthinking this whole thing, you’re right. I knew it didn’t matter. At the very minimum, I figured that any domain name would become what I made of it. Corporate brands like Starbucks and Intel are not successful simply because of a catchy name (through diligent research with focus groups, of course). At the same time, my domain name couldn’t have been more important. It would be the new me! For those that I have interacted with only in a professional capacity, is there any real difference between the real me and what you see on this website? If there is, does it matter? You could say that I had an existential virtual crisis. If you are confused by what that means, then you know how I felt.

The topic of online versus real identity has grown old quickly. Readings about it have proliferated like flies on a perpetual dung heap, but there’s no need for a literature review here. What stands out to me, though, is how I became fascinated if not obsessed by my own delusion that, at least in everyone else’s mind, I was whatever was online. Except that I began to think that I in fact wasn’t online; historyproef was. And everyone was pronouncing it wrong (no, it’s not history prof). It was obvious that whatever abstraction goals I had for the website–however it was meant to convey some kind of meaning or identity by its own carefully chosen name and agenda, or better yet, make an argument–largely failed. Perhaps this was a marketing failure on my part, but I think I grew dissatisfied with it for more substantial reasons.

As an advocate for the importance of design in communication, regardless of media, I’m convinced that all aspects and details of a website reflect some underlying reality, whether through intention or neglect, including any abstraction from the author. In a way, it mimics the way our relationships are increasingly mediated by various technologies. Perhaps one posts content less for friends as much as for how one’s friends will expect via their content delivery mechanism. Perhaps my posts became more of an expression of a generic digital humanities blog than of myself. Obviously, this would defeat the point of the blog. Even a professional one.

So perhaps less abstraction is a good thing after all. Even digital humanists, a label that I suspect describes most of my readers, probably identify more with authors of texts than with websites that host their ideas. Don’t correct me if I’m wrong. Perhaps I drank too much of the DH Kool-Aid, and all my subsequent evangelism for openness created sufficient internal dissonance to make an impersonal virtual place less compelling and ultimately less effective than something more semantically connected to my real self.

There was no final straw, but the camel eventually just wandered off after reflecting on these concerns and tiring of having to repeat or spell out some obscure domain name too often. When people ask to learn more about something I’ve worked on, I often refer them to my website. It’s where everything is and will be, so they should know about it, right? But despite the careful deliberating over its incarnation, I never got comfortable with its foreignness. People don’t want to write down a URL; they want to write down a name. Spelling out some obscure .org domain name doesn’t facilitate the personal exchange that really is one of the most gratifying aspects of scholarly exchange. And of course neither does hiding behind obscure domain name, even if readily pronounceable. And ultimately, the website is (the professional) me in many crucial and functional respects. Pretending otherwise simply obscures a fact of modern day life.

Even if the legitimate reasons for the abstraction of historyproef proved less useful than I anticipated, the larger goals that motivated its creation live on. When I finally get around to combining historical research and innovative graphic design (I just need to finish writing a book on medieval poison real quick first), it will be here. And it will be me.

anecdotal prelude

Improper use of technology—or perhaps misplaced technological priorities—is a danger that we might already be falling prey to. We might be able to better frame the digital challenges facing early modern texts and modern organizational technologies with an analogy to the world of printing in the later 19th century. It was then that letterpress printers found themselves competing with newer and sexier printing techniques, like chromolithography and engraving. Those products were hand-drawn and therefore allowed much greater freedom in design. Soon after, technical advances in letterpress print technology itself (brighter and faster drying inks, new typesetting techniques) allowed letterpress printers to flex their own design chops, and to develop what came to be known as “artistic printing.”

Despite the name, it wasn’t really artistic at all—at least not in the sense that it could be characterized by superior aesthetics per fine art standards. The predominant feature was ornamentation—excessive ornamentation: grandiose borders, highly stylized typefaces, bizarre color schemes, and non-linear design elements—employed to rival materials printed with newer printing technologies, even when those weren’t characterized by such ornamentation. Printers’ content was thus dictated by technology; the medium had overtaken the message.

Critics reacted strongly against printers making their content subservient to “barbaric” excessive ornamentation and “degenerate” ostentatious flourishes. They lamented how printers focused on the immediate and low-hanging technological fruit ahead of fundamental typographic principles. The extra ornament was considered a sham, a form of concealment.

Where letterpress printers did not, we must constantly reflect on our priorities and values as we embrace new technologies for organizing our overwhelmingly large and still growing archive of early modern sources. 21st-century organization of early modern texts must not be seen only as a technological prosthetic that enhances traditional practices, but rather an opportunity for creating and engaging with a new kind of archive.

modern information overload

As we all know, information overload is not new. One salient reminder comes from Ann Blair and her book Too Much To Know, in which she describes how early modern scholars developed various procedural strategies and textual apparati (many of which we still use) to help find and to organize the vast amount of information flooding into their personal libraries. In part, we have the same problem; we too have access to more texts than ever before.

Having access to more texts facilitates more opportunities for applying our traditional methods for organization. We might be tempted to emulate our early modern predecessors, but with modern equivalents—no longer curating shoeboxes of 3×5 cards, but rather Zotero libraries; perhaps moderating virtual group libraries instead of emailing bibliographies. On the whole, we—as did early modern scholars—tend to think in terms of individual technology solutions with some social tentacles, like Zotero and RefWorks. Even on the web, we do this also. We continue to create isolated databases, search engines for them, and even lists of links to help organize and connect early modern texts. But are we creating these because they are the most productive, or because they are most easily accessible technology “solutions”? Have our databases become our ornamental borders?

Unlike previous instances of information overload, however, organization is no longer an individual problem. Rather, it’s one that exists at the level of scholarly societies and broad research communities (notice that i’m not including libraries; more on why later). Our unprecedented access to the early modern period means that we have the potential for a vastly larger and much richer archive than we’ve had before. We must take an active role in organizing that archive to make it available, visible, and fully usable.

I want highlight two facets of the digital archive that will be crucial as digital methodologies become more integrated with our research practices: metadata and text transcriptions. In other words: creating and connecting texts.

2 important caveats
1) I want to emphasize at the outset that both of these are fundamentally social challenges, not technological ones. This is not about what technical standard to follow. This is not about which interface components or which ornamental border to use. These are important questions, but ones that should and will naturally follow a deliberate attempt to make archival content a value problem rather than a technology problem.

2) When speaking about metadata and text—and maybe even the digital humanities at large—skeptics often immediately seize upon the very impersonal and non-humanist kind of inquiry that seems to underlie techniques like text mining, or any vaguely quantitative methodology. Aren’t we simply outsourcing our interpretive powers to complex algorithms and code? NO. These are tools to help us do our work, not strategies for having the computer do interpretive work for us. The goal is to make the fullest use of the early modern record that has come down to us.

ethics and metaphysics of metadata
(connecting text)

It’s hardly news that finding relevant online resources can be problematic for many early modern scholars. As we all know, the bibliographic data we rely on—whether from Google Books, HathiTrust, Internet Archive, and even fully controlled catalogs like the Library of Congress—can be a mess, confused by lengthy and sometimes bizarre titles, language variants, non-standardized author names, foreign characters, uncertain dates…the list could go on and on.

Rejoinders against such mess typically frame these problems as repository problems (eg Google Books has failed us because its metadata is so poor). The problem here is that this kind of thinking embraces the traditional delineation of the researcher as a mere consumer of data. But using poor metadata as the sand in which to bury one’s head in is not a productive way forward. We need to consider the ethics and metaphysics of metadata: Exactly what does it take to create metadata? Whose responsibility is it?

It seems that many metadata critiques treat metadata as objective, descriptive information that simply should be correct. But anyone who’s ever produced any serious amount of metadata knows that it’s quite subjective, confusing, and takes considerable expertise to do properly—especially for early modern sources. Because we’re the ones with this expertise, we must be not only consumers, but also producers of this data.

But isn’t creating and improving metadata the work of librarians and archivists, you ask? Surely, research scholars don’t have the time, inclination or expertise to deal with metadata. We produce knowledge, not metadata!

Except that we don’t live in the binary producer/consumer world anymore. Even if we did, there is simply too much data to deal with. Its stewards simply do not have all necessary expertise or resources to organize it most effectively and flexibly. Without doubt, this involves plenty of technical challenges (standards, interfaces, infrastructure). But these are trivial in comparison to the real challenge: shifting community expectations that erroneous metadata can and should be edited by researchers themselves. And while we’re at it, we might broaden our view of metadata to include not only the usual fields (author, date, etc), but additional description as well (abstracts, section headings, keywords, etc) that makes the texts more findable.

The idea that we share a communal responsibility for metadata requires changes to typical research practices that need to happen more or less simultaneously.

a) The research community must recognize the scholarly value of this work. Making such contributions is the kind of peripheral scholarly work that we already do because we recognize its importance and necessity, such as peer review, review articles, editing, chairing sessions, etc. And we have to recognize that such effort does not have to stem from sheer altruism, as it helps us take fuller advantage of the vast archive we have at our fingertips. It’s far from value neutral, and it requires considerable expertise.

b) Repositories of information need to facilitate metadata suggestions from the scholarly community. This does not mean that they ought to adopt, anonymous, real-time data revisions. Instead: a controlled, but open community effort to improve data. As researchers, we must voice our desire to help make data more usable. Librarians and archivists are nothing if not sensitive to the needs of their constituents.

Framed in this way, the problem isn’t the erroneous metadata itself (woeful as it can be). The problem is that a) we continue to reinforce a division of labor that doesn’t make sense anymore, and b) remain bit too myopic about the kind of work we value as a scholarly community.

early modern übertext
(creating and using text)

Textual organizational challenges are not just about the connective tissue between texts (like metadata), but also part of the challenge of helping to produce the texts themselves.

There is no doubt that the rhetoric of the digital humanities embraces the bird’s eye view of text. Digital methodologies leverage the computer’s ability for mindless drudgery to help us do and see more than we would otherwise—and hopefully make discoveries that would otherwise go unnoticed. Like repairing metadata, such a perspective suggests a new expectation for our archival work: making text/data visible and available. Again, this is not so we can get the computer to interpret it for us. It’s about futzing around with our hermeneutical prism and engaging with the historical record by all available means (and texts).

Ongoing digitization projects, both small- and large-scale operations, are making the early modern world more accessible each day. Resources like Google Books, HathiTrust, EEBO, ECCO, etc, make access to primary sources easier than ever—at least in terms of facilitating our traditional strategy: search, find, and read closely. But image-only archives stored in carefully constructed databases, as useful as they are for improving accessibility, cannot be our only interest. We must not let them become our ornamental borders!

Imagine all the personal notes stashed on hard drives, all the long quotations stashed in notes in nearly impossible to find monographs. How might our interpretations change if we had access to that text?

To truly understand the early modern text (writ large), we need textual transcriptions. Now I am not suggesting that we all spend our time creating transcriptions for our unadulterated love of plain text. But we do an awful lot of work in transcribing for our own scholarship. Imagine all the personal notes stashed on hard drives, all the long quotations stashed in notes in nearly impossible to find monographs. What would our historical archive be like if we had access to that text? What if we put them all together? How would our interpretations be different? What else could we find out?

This isn’t as far-fetched as it may seem. The many (wildly) successful transcription projects (Transcribe Bentham, etc.) suggest the success of collaborative participation, patience, and persistence. The problem is that we don’t value this work as much as we should. As with metadata, it should be considered important scholarly work (but perhaps not scholarship per se). Various technologies and standards with linked open data are creating the connective tissue—but we need the bits to connect.

Several problems with text creation that require attention (merely mentioned here):

These are problems that will continue as long as we maintain a too narrow definition of useful work that doesn’t include creating and connecting texts, and as long as we expect other people to make texts available and useful for us.

• Favoritism: Text creation projects tend to favor the texts we already know—a bias of funded projects that must justify expense with appeals to established utility to a broad audience.
• Access: Full-text resources tend to be behind expensive pay walls, and usually mediated by well meaning but clunky search engines.
• Visibility: Our typical practices don’t support publishing these texts. We need to supplement our traditional forms of scholarship with co-publications on our blogs.
• Authority/Expertise: How do we know where metadata and text have come from? Do we trust them? We learn to make these judgments about scholarship generally; we can learn to do it for data, too.

The reason I mention these challenges (even so curtly), is to point out that they are neither library nor archive problems, nor are they reasons to avoid creating texts. They are our problems that will continue as long as we maintain a too narrow definition of useful work that doesn’t include creating and connecting texts, and as long as we expect other people to make texts available and useful for us. Open access is not a challenge for only archivists, librarians and publishers. It’s one that pervades the entire scholarly community to publish and preserve work they consider valuable.

More importantly, these problems persist especially when we employ individual organization solutions, even ones that attempt to aggregate information. We don’t need more search engines or more APIs. We need visible text. Use a database to store your text, but don’t make me interact with it. Databases are like closed stacks; the best retrieval mechanism doesn’t make either of them particularly visible and usable. Even if we have our eyes on the prize of linked open data, we must not forget about this first crucial step of creating texts to link to—and they should be openly published online.

So why bother creating and organizing such a textual archive? Not everyone will be interested, and that’s fine. But one can hardly ignore the potential here in terms of getting out of scholarly ruts. The literary critic Barbara Herrnstein Smith has suggested that the literary text acts “to shape and create the culture in which its value is produced and transmitted and, for that very reason, to perpetuate the conditions of its own flourishing” (Contingencies of Value, 1988). We could say the same thing about our digital organizational practices as well, as many important techniques that take broad views of texts and data can only be realized when we have an adequate, accessible and visible archive of digital, discrete, malleable, text. If we privilege only traditional archival strategies, we miss out on virtually all historical perspectives that aren’t exposed by those methodologies.

One obvious case is massive searching, which is self-explanatory. More important is malleability: combining unusual sets of texts to get a bird’s eye comparative view. This should not instantly conjure images of massive scatterplots and necessarily large-scale efforts. Small-scale work is also extremely valuable, especially when combining text across archives and disciplinary boundaries.

One of the most important reasons to value the creation of full text is the way searching is moving from linear to algorithmic searching. Our organizational strategies (databases, lists, catalogs, etc.) tend to re-enforce traditional, linear research practices. But the future of searching is not simply finding what you’re looking for. Having more text (and better metadata) allows us to take advantage of finding not only what we are looking for, but also what we’re not looking for—but should be. Imagine a “show me more like this…” feature that worked for our primary sources. Algorithmic searching is, of course, what Google does, but I’m not suggesting that their mysterious PageRank algorithm should reign over our sources. But as we think about how to organize an unprecedented volume of text, we also have to think about future access technologies. We need to think about the principles of data architecture (typography), and to be sure they are not being applied as technological band-aids (fanciful mauve borders).

Again, all of these efforts (fixing metadata, text encoding, creating and publishing transcriptions) require an expansion in the kind of scholarly work we value and reshaping relationship between producers and consumers of data. Simply waiting around for better data or better tools will make for both inferior tools and scholarship. While there are many examples of text creation projects—and such projects have produced excellent results—they tend to be specially grant-funded projects that create unnecessary labor bottlenecks. This model is wholly unsustainable. Worse yet, the products of such projects tend to reside in databases that we say are open, available, and connected, but are only trivially so, since so few people know about them or can access them.

imagining the future

If what I’ve described sounds like some fantasy utopia…let me reassure you: it is. But the imaginative possibilities are indeed tantalizing, and even such a utopian vision should guide our values and priorities. Necessity might be the mother of invention, but imagination is its milk.

Will our scholarship be reduced to overwrought font faces and massive visualizations that merely add knowledge without value?

With such a vastly accessible archive at our fingertips, Mike Witmore (who commented on the conference panel where an early version of this essay was presented) asked if we will lose our ability to ask good questions? Or will we simply be tinkering with texts because they are there? Will our questions still be meaningful? I interpret this as: Will our scholarship be reduced to overwrought font faces and massive visualizations that merely add knowledge without value? It remains to be seen, but I don’t think that fully exposing and connecting our early modern texts (and ways of accessing them) will jeopardize our critical faculties or ability to identify and frame interesting questions. Various digital humanities projects have already started to do that. As do new visualizations, a new kind of archive will facilitate new kinds of questions—ones that cannot possibly grow out of the textual archive the way we have traditionally organized it.

In terms of establishing values, our teaching is crucial. As educators of future early modernists, we have to increase awareness of and discuss new textual analytical techniques, and how to establish their requisite infrastructure (like metadata and the value of textual openness) in our courses. Furthermore, our teaching can contribute to the project of making more texts available and visible. We can take advantage of the necessary repetition that happens in both grad and undergrad training to shape the early modern archive into its most usable form. Ars longa, vita brevis. Other sessions have already suggested what a great process transcription is for teaching about editing and understanding the notion of a text.

As with our earlier letterpress printers, we’ll have our share of overly ornamented communication failures, where technological fascination obscures analytical objectives. And that’s okay. In a way that typical scholarship does not, we must embrace productive failure—tools, interfaces, processes that help us shape the resources at our disposal. Best practices for improving metadata or associating text with images are unclear: it’s not at all obvious whether we should be using Betamax or VHS right now. In the end, it doesn’t matter, as long as we must value the larger goals more than any particular technology.

We have to be thinking of books and texts not only in their contemporary contexts, but also in their modern digital contexts as well, and how we employ technologies to connect them to as many other relevant texts as possible (obvious: author, year, place, subject; cooler: word frequency, tone, style), and how we can profitably put these texts in conversation with each other. That is the organizational challenge ahead. At a superficial level, it’s not at all a new problem. Beneath the surface, though, it’s an entirely different kind of challenge that has the potential for an entirely new kind of early modern text and interpretations of it.

[This talk is a slightly revised version of a presentation from the 2012 Renaissance Society of America meeting in Washington, DC.]

Mark’s proposal highlighted for me two particular issues that warrant further discussion (as he intended), namely incentivizing participation in open peer review and the obligation of the review platform to facilitate that. Even though i disagree with Mark on a number of points, what follows is not intended as a criticism of the post itself—a deliberately rapid but insightful reaction to a Twitter flurry that followed the announcement about JDH itself—but a short stroll down the important path that Mark has thankfully pointed us down. In particular, i want to explore not only motivational forces, but also the nature and status of the scholarly work that open reviews can produce.

do we need to motivate peer review?

Rightly concerned with a principle obstacle to successful open peer review, Mark addresses the problem of providing motivation for diverse and qualified reviewers to do difficult and time consuming work (at least to do it well) who might not really get credit for doing it. With only a few hours per week for such work, how can such invisible labor be justified against the incessant ticking of a tenure or review clock? Or even other pressing deadlines? Even if we know that the work as useful and stimulating, why should it be a priority when it’s not properly recognized?

Mark offers an elegant plea that it is at least partially incumbent on the journal (or whatever) to incentivize and diversify the peer review process. One of his suggestions: badges. For roughly a zillion reasons that i won’t go into here, i remain highly skeptical of the utility and viability of badges. He might be right: something like badges could conceivably provide a tangible way to assess the productive contributions that an individual has made in evaluating and critiquing the work of colleagues. But Marks’s reason for writing, as I take it, isn’t to demand badges per se, but to highlight the need for a motivating force.

We should keep in mind, however, that contributions to an open peer review (even if not easily measured or validated) are already motivated by the grubby, practical realities of professionalization (thankfully made easier by a generally welcoming DH community). Participating publicly in the conversation, the critique, is a crucial form of community engagement (if not a kind of necessary performance) that is far from invisible. As Mark points out, knowledge creation doesn’t happen in solitary archives, but within broader communities. The open forum—and its space for insightful comments and questions—presents an almost unprecedented opportunity for preening. Akin to the really great question from an audience member that swivels heads after a conference paper (and perhaps is remembered even more than the paper itself), it affords one the chance to strut one’s stuff, so to speak. It helps establish one’s own value to a community. This very real value provides an indispensable foundation for many recommendations (either via formal letters or informal conversations), whether for a new job, tenure, or promotion. Furthermore, such public work can lead to more tangible opportunities as well, like collaborations on high-profile projects, solicitations for contributions to journals or edited volumes, etc—all of the kinds of measurable productivity that even most traditional evaluators want to see on a CV.

All this is to say that at least one major incentive (besides sheer altruism) that helps to cultivate a diverse pool of reviewers and fuel the review process itself already exists. This might be pointing out the obvious, but I would submit that this and other incentives (and their implications) are much more complex than we’ve appreciated so far. In general, we have not typically discussed how peer review participation fits into the larger structures of professionalization because, simply, it hasn’t. Peer review has remained a rather exclusionary tribal ritual where the elite exert a uni-directional downward force on the semi-initiated masses. Yet even as this begins to change in the wake of some early open peer review projects, there has not been much discussion (as Mark points out) about how to situate the products of peer review in a larger professional scholarly context. Of course it all starts with people making comments—so exactly what role should the review platform play in such considerations?

the role of the reviewer

A mechanism like badges—or any similar mechanism—places a significant onus on the review platform to facilitate—if not manage outright—some kind of participation metrics or credentialing process. Partially because of existing motive forces as explained above, I’m not yet convinced this is fully necessary. But it raises what seems to be a large and pressing question: What are the functional obligations of the journal or press that conducts open peer review?

DH projects have well demonstrated that “if you build it, they often don’t come.” Simply enabling and promoting open peer review is no recipe for either getting good comments or for changing the way such knowledge-work and community engagement can be appreciated. There can be little doubt that success in shifting (broader humanities) community values w/r/t open peer review will depend intimately on the aesthetics and interface design and functionality that creates a new kind of scholarly experience (more on why theory helps with this below). But thinking about particular functional or usability requirements that might help incentivize participation at the platform level cannot be our only (or perhaps even first) concern. In order to understand the functional obligations of the publisher and review platform, we need to understand the larger social obligations that such review work might create. As a start, i’d like to affirm the importance of the agency of the reviewer in promoting and establishing the value of review contributions. Up until now, this agency has been approximately zero. But that’s not the case anymore.

To complement Mark’s proposal, i would suggest that considerations of motivations and mechanisms for open peer review (and obligations of the platform) must go well beyond the review platform itself. For example, reviewers themselves might experiment with new approaches to presenting (dare i say marketing?) their review work. Of course it’s not the case that reviewers have simply been lazy about documenting their effort. Review work has remained invisible not just because of individual scholars, but because of the generally cloaked process of peer review, which has remained a highly mediated and private exchange. Open peer review, however, largely alliviates the expectation of future secrecy.

Reviewers who have done work they are proud of (even if unrecognized or unacknowledged) might, for example, cultivate something like a digital portfolio of their review contributions, each in a short (and i mean it!) essay form that describes the broader value of each review. Of course there is the issue of external validation of quality, a concern that something like badges might address in the way they could serve as a community nod to good work. But would such a mechanism be too abstract for its own good? Perhaps editors or authors whose work has been substantially improved by a reviewer could attest to such efficacy with a brief comment in the reviewer’s portfolio. Especially if from a major press or established scholar, could this be viable grist for the promotion committee’s mill? There are some reasons not to do this, not least of which is the extra work it would entail, but bear with me for a moment longer.

I wonder, too, if expectations that we might showcase our own value as a reviewer, and possibly solicit appraisals from relevant parties, wouldn’t help make our critical engagement with each other’s work—even while in progress (it’s like 95% done, right?)—much more permanent and useful. Perhaps we might think in terms of a new social contract of scholarly publishing that presents to readers not just a polished and vetted product (whether a book or blog post), but a glimpse into the forces that have shaped that product. Such machinations won’t always be interesting, but that’s where the magic of jQuery comes in.

Beyond visibility and transparency (to say nothing of the pedagogical potential here) the expectation that we should repackage our review contributions to get more credit for them might encourage reviewers to focus on broadly useful comments, whether concerning historiography, theory, practice, structure, or style. Not all comments should address only the big picture, obviously, but i would argue that most helpful, substantive comments (and ones we hope to get credit for) are more along those lines than of the line-item correction variety (and no, this does not disparage the difficult and under-appreciated work of quality copyediting). But has any scholar not received sadly myopic comments that threw the whole process of peer review into question? Admittedly, any sort of repackaging would be much easier when properly enabled by the review platform. And this emphasizes Mark’s larger aim in writing (in my view): the extent to which the review platform should provide such services (or badges) requires much more discussion.

At any rate, the broader point here is that open peer review affords us new ways of capturing and leveraging our critical engagement with each other’s work. As a result, we need to think more carefully about the lifecycle and status of our review work, even beyond how we might credential it at the site of production. At all levels of rethinking how to motivate and recognize reviewing efforts, we should be limited by creativity, not convention. We cannot simply appeal to existing procedures and venues; we might well need new ones.

where does it fit?

My remarks thus far have obviously privileged the spirit of discussion over practical solutions. As Mark immediately recognized, it’s a conversation well worth having. It will help establish conventions for not only how we can provide more effective critiques, but also how we can incorporate that work into a larger scholarly discourse. As past open review projects have demonstrated, some very insightful comments and discussions take place in the margins—sometimes just as valuable as the original piece.

But then shouldn’t we just do it? Do we really need to talk about doing it?

We might look to Salerno, Italy in second half of the twelfth century for an answer. (perhaps not the most obvious place, i know…) As theory-heavy Greek and Arabic medical (and other philosophical) works were translated into Latin, physicians struggled to assimilate and situate medical knowledge in the larger hierarchy of knowledge and to craft a curriculum for physicians studying at the burgeoning universities. Their main challenge was to address the theory/practice divide. Medicine was seen fundamentally as an art or craft and therefore had little place among the true sciences, like ethics, logic, and metaphysics. Bartholomaeus of Salerno, a physician and teacher who became one of the most influential leaders of the charge to legitimate medicine as a science (and thus worthy of a place in a university curriculum), argued successfully (not for the first time, but perhaps most influentially) that practice cannot exist without theory. This may sound absurd (as in: i do stuff all the time without having theorized about it beforehand!), but of course he was really saying that all practice is informed by theory whether we know how it is or not.

In terms of open peer review, we need to get clear about what we want (both socially and technically) out of new review practices, as well as how they should serve not only a publication and its readership, but also the process of knowledge production. I say “should” because such reflection might involve reshaping practices as much as appealing to them, as was the case at Salerno. And as Salernitan physicians (and their followers) did, we also must consider—and argue for—where review work should stand in the larger ecosystem (if not hierarchy) of scholarly discourse and knowledge. Is open peer review an opportunity to highlight some very important intellectual work that we’ve kept under the table? Is it best left by the wayside? Should our professional websites aggregate and highlight our public review work that can be supported/verified by the community? Would this help or hinder either the quality or quantity of reviews?

Hashing out our underlying needs and wants and the causal forces that will drive them (ie theorizing about best practices) will help ensure that we don’t see our open peer review efforts as deterministically and self-evidently improving peer review by dint of their mere existence. Instead we’ll be able to deliberately pursue and defend targeted strategies to make the entire process and its products more useful, sustainable, and transformative both within and without the digital humanities community.