Main Question: Modern Languages and the Digital: the Shape of the Discipline

Undeniably, the advent of digital technologies on the shape of ML research and publishing has been immense. First, regarding research, digital technologies have changed the way in which we engage in our research practice right across the full cycle of the research process: from our objects of study, which may no longer be the traditional print book (as was the basis of our conventional, philological training), but instead may now include genres as diverse as the hypermedia novel, twitter poetry, net art, hacktivism, social media, and many more, through to our tools of analysis, which may now include visualizations, big data approaches, and so on, ML has – along with many other humanities disciplines – seen its shape change over the past two decades. It also has led us to challenge what it means to describe ML as a discipline, or, at the very least to re-inscribe its boundaries.

Second, regarding publishing, the changes to conventional models, with the rise of the e-book, online early journal articles, open access publishing, and online only publishing on the one hand, coupled with the rise of self-publishing that has been afforded by digital technologies and social media in particular on the other – where we now ‘publish’ on Twitter, blogs, Facebook or other platforms just as often as we do in conventional print outlets – means that many of us have had to re-think what it means to ‘publish’ in ML.

The changes to the basis of ML research are not only methodological and practical, but also conceptual. We find ourselves availing of new tools for analysis, new methods for approaching objects of study, indeed, for some, even the objects of study themselves are new. All these require us to re-formulate what it means to carry out research and to consider the possible affordances of a plethora of platforms, spaces, and tools.

One of the significant impacts that digital technologies have had on our conceptualization of ML as a discipline is to make us re-think some of the place-based assumptions underpinning our research practice. If as creators, academics or practitioners we can exist virtually, does place and space matter? Conversely, geopolitical shifts, uneven access points, legal differentials, and cultural particularities demand that we consider how we can become even more fixed and attached to place and space.

Another big impact of recent changes is the question of how the digital may have made us re-think ourselves as a fundamentally philologically-based discipline. In other words, the phenomenal explosion of user-generated content enabled by digital technologies has been a wake-up call for many of us –we can no longer take as read that a common object of study is the canon (be that literary, film, art, etc); and, moreover, we need to look at practices, as much as texts.

Of course, all of this didn’t happen in a vacuum – with the rise of cultural studies approaches, ML was rethinking itself anyway. So, perhaps, it’s more a case of this all crystallising at the same time: that at the point at which ML was already in the process of questioning some of its assumptions (philology; study of high literature, etc), the rise of digital technologies then has become this disruptive element that demands a re-formulated genealogy.

As we look to the future of the discipline(s) there are as many questions as answers. As a consequence of this new landscape with its new tools and practices, do we need to find new nodes where our disciplines reside that belong within and outside of national territories? Do we need to be open to all changes and forget a boundaried sense of what we do? Or, are there needs for new frontiers where we establish our own silos with connections to those who want to share and exchange ideas and methodology? As adopters of technology, do we need to be more than just end users and become designers, makers, or programmers?

It’s certainly the case that ML has had to (and has to continue to) re-conceptualize itself, in the face of immense pressures. Worton’s call for ML as a discipline to articulate a clear and compelling identity, all the while maintaining itself as a trans-disciplinary field ( 2009: 37), seems to be fundamental- and it’s still one that we’ve never really answered. This is a huge challenge for us as Modern Linguists, and it’s not clear we’ve actually got there yet. If this is the main challenge, then the digital is one set of coordinates within this bigger picture; it’s one of the things (but not the sole thing) that we have to negotiate as we re-think our discipline(s). We have previously contributed to a conversation about our own ‘discipline’, Hispanic Studies, where we both expressed a desire for disciplinary renovation and interdisciplinary exchanges and we proposed some forms in which we, as journal editors, could make our contribution at this moment (Fraser and Henseler 2014). Situated as we are in language- and area-specific knowledge and research, we have to ask about the desirability of such an approach in other fields and in the appeal of seeing ML as one discipline or several inter-related polyphonous disciplines onto which we patch the shifting prefixes (such as, trans-, inter-, intra-, multi-) as the need arise. Can we be DH-MLers? Can this be a thing?

Without a fixed object of study (literature) that the discipline is founded on, yet with the tools to understand other cultural objects and with communication as a fundamental skill, ML is well-placed to tackle the user-oriented end of DH. As researchers capable of reaching across into the unfamiliar and uncomfortable we have the capacity to test the limits of knowledge. Some of these are skills integral to all of those in the Humanities. But, we invite ML faculty to look at those with whom you work daily and you will find that we are well used to working across disciplines. Linguistic specialists parsing language usage work with social media researchers side-by-side with historians of early modern periods. Sometimes, within so-called disciplines, we may not even have a shared second language, or national focus. Yet, ML binds us. What have we learnt from this that can contribute to a widening of the scope of DH and how can this be mutually beneficial?