NHC Summer Institute in Digital Textual Studies: Readings
The readings are of two kinds corresponding to the methodological discussions in the morning, prior to each day’s workshop, and the theoretical discussions in the afternoon. The former are meant to orient you to the work that follows, the latter to give you a chance to probe the significance of computing for your research and of this research for computing. Provocations for the afternoon discussions will of course come from the methodological focus of the workshops. But the history of our engagement with computing, its disciplinary connections and theoretical inheritances surround digital humanities on all sides and comprise an essential part of what it does. Together with your own scholarly interests and experience they form the context needed for us to make full sense of digital research.
Based on the day’s readings, discussion will be introduced by the conveners in order to start — but not to define or limit — discussions. The essential readings (marked by *) we ask you to have done prior to the start of the Institute, the rest to the extent possible. Suggestions for further readings are most welcome.
I. Basic books
Three basic books are supplied in printed form: Arthur and Bode 2015; Jockers 2014; McCarty 2014/2005. One reference work, Schreibman, Siemens and Unsworth 2004, is available online. Jockers 2014 is the textbook for the lab. Arthur and Bode 2015 and McCarty 2014/2005, first theoretical work on digital humanities, supply various readings. For those who are interested, the former provides a useful survey of the current state of the digital humanities art.
II. Readings for the workshops
These follow the corresponding sections of Jockers 2014.
- 1. *Allison et al 2012; Flanders 2005; Potter 1988
- 2. *Hoover 2003a; Whitmore 2007
- 3. Schilit and Kolak 2007; Nunberg 2009; Schultz 2011; Michel et al 2011; *Anderson 2008; Jockers and Witten 2010; *Koppel, Argamon and Shimoni 2002; *Blevins 2010; *Block 2006; Chang et al 2009; *Tynjanov 1978
III. Readings for the theoretical discussions (by topic)
1. Historical overview
These readings are intended to illumine ongoing problems and theoretical issues from the ‘incunabular’ period of digital humanities (ca 1949-early 1990s) to the present day: *Milic 1966; Busa 1976; *Busa 1980; *Olsen 1993/1991; *Kenny 1992; *Liu 2012; *Bode and Arthur 2015. *Mahoney 2005, on the history of computing, is essential.
2. The interpretative disciplines and the natural sciences
You may wish to concentrate on your own discipline, but there is considerable profit from seeing how analogous if not identical problems arise in the others, take on different forms and receive different treatment. These problems lead in turn to fundamental issues taken up by historical, philosophical and sociological studies of the natural sciences. Such studies have much to offer the interpretative disciplines in their problematizing engagement with the technoscientific equipment of digital computing.
We suggest you begin reading with McCarty 2016 (an attempt to come to terms with the challenging project of the interdisciplinary exploration recommended here), then proceed as time permits through the following disciplinary areas:
- History: *Stone 1979 (on cliometrics); *Cohen and Rosenzweig 2005; *Blaxill 2013
- Social sciences: *Krippendorff 2014; Grimmer and Stewart 2013
- Literary studies and textual scholarship: Rommel 2004; *Flanders 2009; McGann 2013; Stubbs 2005
- Science studies: *Kuhn 1970/1962; *Hacking 1983a; *Hacking 1990; *Hacking 2002; *Keller 2002; Galison 2004
- Cultural criticism: *Scarry 1992 (and Liu 2012, as above)
3. Modelling and experimenting
‘Model’ is a notoriously polysemous term but for our purposes may be defined as a digital representation of something that makes it computationally tractable. Constructing a digital model requires complete explicitness and absolute consistency, which of course means that anything which cannot be described in that way is missed. Modelling is the iterative process of adjusting the model better to conform to the modelled object as you see it. Thereby the significance of that which the model omits becomes greater with each perfective iteration. The epistemic value of modelling is thus a combination of manipulatory power and incompleteness, which is true of any formulation but is sharpened when an object is translated into digital form.
The speed with which modelling can be done gives digital research an experimental dimension and so makes it kin to the experimental sciences. Since Kuhn we have known that experimentation is no mere handmaiden to theory but has “a life of its own”; in Ian Hacking’s terms it constitutes one of the basic ‘styles’ of scientific reasoning (Hacking 1983b: 150; 2002). Digital humanities inherits this style by virtue of the machine at its core. Developing an experimental understanding of digital humanities is one of the field’s most urgent imperatives.
- Modelling: *McCarty 2014/2005: 20-53; *McGann 2004; *Epstein 2008; Moretti 2013; Frye 1991; Shanin 1972; Leff 1972
- Experimenting: *Burrows 2010; *Hacking 1983b; *Gooding 1986; Gooding 2003
Simulation is the other half of the epistemological story begun with modelling. Apart from building online resources, it names the synthetic side of computing complementary to the analytic. Simulation is complex, evolving and diverse across the disciplines. Terminology here is often confused, but for our purposes we can say that whereas modelling is declarative, making statements as close to the truth as we can manage, yielding its greatest value in what it does not catch, simulation is subjunctive, generating parallel or even alternative worlds that begin with current knowledge but proceed beyond it. Whereas modelling is oriented to fact, simulation is speculative. Modelling converges on stability; simulation expands “the alternativeness of human possibility” (Bruner 1986: 53).
Many simulations are visually expressed, often as ‘immersive’ visualisations involving avatars controlled by software or the participant. But as a kind of storytelling simulations can be textual, hence their relevance for this Institute. Currently the majority form is known as ‘agent-based modelling’ (again the terminological confusion), i.e. simulations populated by autonomous agents that can interact in unpredictable ways though constrained by their given characteristics. Simulation, though a subject of active interest, is underdeveloped in the humanities, much less so in the social sciences.
- Begin with *McCarty 2015 (forthcoming) then proceed to:
- Historical studies: *Düring 2014; Gavin 2014
- Social sciences: *Epstein 1999
- Literary studies: *Drucker 2009; *Wall 2014
5. Futures: to the Institute in 2016 and meanwhile
The last discussion period for the first part of the Institute is chiefly for critical summing up and planning for part 2 in June 2016. But we begin with two readings: *Liu 2014 and *McCarty 2014.
If time permits (but especially recommended for subsequent reading) three essays from the social scientific, historical and literary areas of the interpretative disciplines: Bruner 1986; Ginzburg 1996; McGann 2015.