Bertrand Russell and the Nature of Propositions

A History and Defence of the Multiple Relation Theory of Judgement

Samuel Lebens

• Publisher: Routledge
• Year: 2017
• ISBN:
  9781351733878
• Edition: 1
• Topic: Filosofía
• Subtopic: Historia y teoría filosóficas

Bertrand Russell and the Nature of Propositions offers the first book-length defence of the Multiple Relation Theory of Judgement (MRTJ). Although the theory was much maligned by Wittgenstein and ultimately rejected by Russell himself, Lebens shows that it provides a rich and insightful way to understand the nature of propositional content.

In Part I, Lebens charts the trajectory of Russell's thought before he adopted the MRTJ. Part II reviews the historical story of the theory: What led Russell to deny the existence of propositions altogether? Why did the theory keep evolving throughout its short life? What role did G. F. Stout play in the evolution of the theory? What was Wittgenstein's concern with the theory, and, if we can't know what his concern was exactly, then what are the best contending hypotheses? And why did Russell give the theory up? In Part III, Lebens makes the case that Russell's concerns with the theory weren't worth its rejection. Moreover, he argues that the MRTJ does most of what we could want from an account of propositions at little philosophical cost.

This book bridges the history of early analytic philosophy with work in contemporary philosophy of language. It advances a bold reading of the theory of descriptions and offers a new understanding of the role of Stout and the representation concern in the evolution of the MRTJ. It also makes a decisive contribution to philosophy of language by demonstrating the viability of a no-proposition theory of propositions.

1 Comics and Empirical Research

An Introduction

Alexander Dunst, Jochen Laubrock, and Janina Wildfeuer

Indeed if I had one single ambition in literary studies it would be to rejoin them with experimental science.

(Williams 341)

We have only begun to discover the benefits of seeing science and art as one.

(Kuhn, “Comment” 405)

It is a lesson that is imparted to us from every part of the history of the natural sciences that the progress of any science is closely connected to the progress made regarding its methods.

(Wundt xi, translation ours)

1. Empirical Cultural Research

Compared to dominant hermeneutic paradigms, empirical research that engages with culture and the arts plays a minor, sometimes even neglected, role. Several factors are currently challenging this status quo. The combination of large-scale digitization efforts, computational tools that enable sophisticated analysis on personal computers, and the online availability of research software are reconfiguring the humanities in ways that are imperfectly captured by references to a digital turn. To date, commentators have paid most attention to quantification—both in terms of the sheer volume of humanities data that is now becoming accessible and efforts to adjust the scales of inquiry accordingly (Schöch; English and Underwood). At least equally important are arguably more basic consequences of digitization: The transformation into binary information makes cultural data amenable to computational analysis via the machine-readable formalization of concepts and their integration into software. Unlike a hermeneutical process, whose outlines may be documented in writing but remain bound to subjectivity, computational calculation can be archived directly, as well as studied, repeated, and adapted by others.

This externalization of the research process generalizes an element that has long characterized the sciences but played only a minor role in the humanities—empirical testing. Testing in turn introduces a novel explicitness and provides the basis for mediating between different arguments and positions. As Andrew Piper argues, the humanities by and large develop in an agonistic fashion. Too often in the humanities, what counts as a research outcome takes the form of disagreeing with an existing opinion. The sheer number of methodological frameworks that fragment into incompatible schools, the recourse to individual sets of texts that form the objects of study, and the ultimate opacity of hermeneutics all mitigate against agreement. In contrast, formalization and computation act as constraints that make each step of the research process legible. As a consequence, Piper writes, “the tools and information for mediating disagreement are made more mutually available” (“Numbers”). In this sense, empirical cultural research presents an opportunity to readjust the scales, not only by way of quantification, but also by making the humanities more consensus-driven. Where tools and corpora, algorithms and data can be shared digitally, we might see the emergence of a qualitatively different research culture in the humanities: One in which existing knowledge provides the building blocks of future research, where the daily practice of scholarship becomes more collective and less captive to the mystique of individual insight.

It is this spirit that animates the present volume. Most of the chapters collected here were presented at a conference titled “The Empirical Study of Comics” and held at the University of Bremen in February 2017. This meeting, the first to focus on the topic, brought together an unusually broad mix of disciplines in an atmosphere of genuine scientific discovery. In similar ways, this volume combines input from linguistics, literary and media studies, as well as cognitive and computer science. Comics, once looked down upon as a lowly form of mass culture, have interested researchers for several decades now. Their study has become increasingly institutionalized, with new journals and associations accompanying a constant stream of publications. In keeping with the humanities at large, however, empirical comics research remains at an early stage of development.

One motivation in editing this book consists in providing a single reference point that may form the basis of future research. More fundamentally, it is our aim to sketch the contours of a new research program. In keeping with this ambition, we define empirical comics research as a set of methods capable of supporting or falsifying its hypotheses about the medium of comics, often constructed by theoretically and methodologically fine-grained analyses, with the help of empirical testing and quantitative corpus studies. We strongly believe that empirical approaches have the potential to transform research on comics, and narrative media more generally. Success in this undertaking ultimately will depend on the development of a distinct research culture that frees itself from the (often implicit) expectations of parent disciplines to produce results that appeal to scholars from a variety of backgrounds. Given the number of disciplines that may potentially contribute to empirical comics research and the strength of established paradigms, this ambition remains an acute challenge.

Nonetheless, a shared set of concerns can be seen to emerge from this volume. These include:

1. 1 A clear distinction between the told and the telling, or, in other words, between a multimodal document and its reception by empirical readers. The consequences of this distinction can be felt across several contributions, most importantly in the inclusion of a section on cognitive research. In a sign of the methodological synthesis that will form a necessary part of the research culture envisioned above, eye-tracking studies and reader questionnaires contribute to chapters written by linguists and psychologists on topics such as page layout, narrative cohesion, mental model construction, and bridging inferences (see Bateman et al., Tseng et al., Magliano et al., Loschky et al., Kirtley et al., Laubrock et al., this volume).
2. 2 An emphasis on representative corpora that challenges the dominance of impressionistic case studies in comics research. While much work remains to be done before reference corpora are fully established and can be shared among researchers, this volume includes several chapters that document their construction and base their analysis on them (see Beaty et al., Dunst and Hartel, Walsh et al., this volume).
3. 3 The integration of case studies, corpus analysis, and reception research into a triangulated framework. As several contributors note, one of the most promising areas of future growth lies in mobilizing elements of the research process that too often remain isolated. Creating feedback loops between them will allow for the formulation of new, and the testing of established, theories, the development of experimental methods, and the integration of disciplinary frameworks into a more fine-grained understanding of comics (see Cohn, Kirtley et al., Laubrock et al., this volume).
4. 4 Finally, the emergence of a distinct vocabulary of empirical comics research is apparent throughout this volume in the repeated use of terms such as saliency, page composition, and low-level features. Because this vocabulary draws on the different disciplines that contribute to empirical approaches, their meaning may not be readily apparent, even to other researchers in the field of comics research. The glossary we have included in this book intends to address this issue.

As editors, our belief in the transformative potential of empirical research is strengthened by a number of intersecting developments in contemporary academia. We have already mentioned the explosive growth of what has come to be called the digital humanities. The present volume contributes to this emerging field with a section that decisively expands computational work on comics: marking the first application of a method known as topic modeling to comics text, documenting the construction of the first representative corpus of US-American comic books, applying convolutional neural networks to comics, and, for the first time, proposing a visual stylometry for graphic novels. However, the emphasis on reception studies across these pages also moves this volume beyond a purely quantitative perspective.

In recent years, concepts drawn from cognitive psychology have had a considerable impact on literary studies and linguistics. Within the mainstream of literary studies, including narratology, most of this influence has been limited to the importation of theoretical concepts. At times, this limitation has also characterized comics research (see, for instance, Kukkonen) but the wide readership enjoyed by the work of Neil Cohn has ensured an openness to experimental science (Visual Language). Further afield, the discipline of empirical aesthetics has enjoyed somewhat of a renaissance, albeit without taking much interest in comics so far (e.g., Shimamura and Palmer; Palmer et al.). Linguistics, on the contrary, has successfully expanded into media analysis, leaving behind an earlier emphasis on verbal data for a focus on multimodal resources. The area of multimodal linguistics, or multimodal semiotics in particular, offers frameworks for the study of comics that focus on the patterns of meaning-making, the interplay of text and images, and the specific affordances of the medium (e.g., Bateman et al., Multimodality). Working closely with cognitive science, significant advances have been made in the computational modeling and processing of natural languages. Once we add the analysis of digital data and corpora, linguistics provides an important foundation for interdisciplinary empirical research. Of particular value here are the ways in which linguistics offers levels of abstraction that enable researchers to go beyond theoretical and methodological discussions.

These intersections bring Raymond Williams’ aim to unite the humanities and experimental science, quoted at the start of this introduction, a step closer to fruition. First expressed during the height of poststructuralism’s influence on the humanities, the developments we have sketched here suggest that Williams’ ambition is much more in step with today’s academic landscape than it was forty years ago. The digital humanities, the growing awareness of the cognitive dimensions of storytelling, and the shift towards media specificity all point in this direction and enable more fluid exchange between disciplines. A literary historian and theorist by trade, Williams imagined such a project as an “active collaboration” that would investigate “the overlap of the biological and the social in the acquisition and deployment of ‘ways of seeing’” (Williams 341; Prendergast 43). Coming of age at a time of large-scale interdisciplinary efforts during World War II, Williams and the physicist (and later historian of science) Thomas Kuhn were acutely aware of the potential benefits of these border crossings and the risks of disciplinary detachment.

The seemingly straightforward distinction between the sciences and the humanities, of course, masks a more complex reality. The distance between these two terms in Anglophone countries is less apparent in languages such as Russian, German, and Italian, which all extend the moniker science to the study of language, literature, and culture—variously speaking of Literaturwissenschaft or scienza della letteratura (Bod et al. 4). And while the division between the human and the natural sciences goes back to Giambattista Vico’s Scienza Nuova, published as early as 1726, it was canonized in the late nineteenth-century philosophy of Wilhelm Dilthey. In fact, the basis for Dilthey’s dichotomy proves informative precisely because recent developments so thoroughly call it into question. For Dilthey, the sciences and the humanities could be distinguished according to their methods and their objects of study. Where the former explain the world as countable and measurable regularities, the latter seek to understand the expressions of the human mind (Bod 3; Dilthey). The digital turn has severely undermined this distinction, and it might, in time, vanish altogether. Very soon, most expressions of the mind will likely become countable, their regularities measurable, and scholars will become capable of explanation and interpretation. Kuhn’s anticipation of the unity of science and the arts regains new urgency in this context, as does Williams’ call for active collaboration—a convergence that will prove all the more fruitful if its participants can construct an equitable engagement.

As several commentators have noted, the digital humanities have mostly explored the practical uses of computer science to date (e.g., Hall 782). In practice, this relationship often assumes the character of a direct importation of tools and methods that delegates computer scientists to the status of mere technicians. In turn, the sciences are frequently content to see the humanities as providers of complex data and a smattering of cultural expertise. These academic one-way streets, mirror images of one another, impoverish all participants. Hall’s argument that we should not conflate the computational turn in the humanities with the current state of scholarship may inspire us to imagine a different or, as he calls it, “postdigital humanities” (782). According to Hall, these postdigital humanities would explore the “irresolvable yet productive tension” between the human and natural sciences and prove “capable of generating new findings, insights, and realizations in the other—to the point where both of their identities are brought into question” (802). Only time will tell whether such a convergence can be forged. However, “the benefits of seeing science and art as one,” to cite Kuhn’s words once again, are already becoming visible (405).

Somewhat counterintuitively, the most interesting path may not lie in asking what benefits the sciences bring to the humanities. After all, this direction is being taken already by the current upsurge in quantitative and empirical humanities research—with the visible benefit of a set of increasingly unified methodologies, described below. Inspired by this pragmatic advantage, the humanities are undergoing a period of intense self-examination. As James English and Ted Underwood write from their own standpoint in English Studies, “We are experiencing a much more concerted effort than occurred in the late twentieth century actually to recalibrate the entire analytic apparatus of literary study” (282). Their diagnosis may be extended to other humanities disciplines: Difficult questions are being asked about the basic assumptions of humanistic study, and will continue to be asked over the next few years. What are the scales of analysis at which cultural research may best be conducted, and how can they be connected? What does the digitization of objects of study mean for the theoretical frameworks of the humanities, both in their philosophical ontologies and in their research epistemologies? How can the dependence on digitality be squared with the necessary return to analog sources? How can new standards of evidence be constructed that simultaneously satisfy humanistic self-reflexivity and a scientific empiricism? Or, in other words, how do we combine explanation with interpretation? To reverse the direction, to ask what new findings, insights, and realizations the humanities can provoke in the sciences means to go against the grain of the digital humanities as they are practiced today.

This reversal would return to the sciences the questions that digital humanities asks itself, and challenge the basic tenets of their research culture. In The Structure of Scientific Revolutions, Kuhn describes the every-day business of “normal science” as one that purposefully eschews the “deep debates over legitimate methods, problems, and standards of solution” that characterize the paradigm shifts of the book’s title (48). One of the primary benefits that the humanities may bring to a converging research program consists in a closer entwining of method and reflection, of explanation and critique. Williams had written of another entanglement, between the biological and the social, as the site of this “active collaboration” (341). The ways of seeing that arise from this intersection lie at the center of the empirical study of comics, a medium that combines reading and viewing in ways we are only beginning to understand. Humanistic reflection can thus correct a tendency to simplify the meeting point of biology, society, and culture.

This constant triangulation of biology, society, and culture seems fundamental to empirical research in the humanities. As much as works of art emerge from their historical and political context, cognitive processes do not operate in isolation, but are always situated. To give an example that applies specifically to comics research: There is a clear need for analytical guidelines that enable individual case studies to contribute to systematic knowledge and subsequently encourage empirical testing and computing. A broader understanding of visual artifacts, their internal structures and contexts, can guide further experimentation and testing on their reception and interpretation. As a consequence, here as elsewhere, empirical research demands constant self-reflection from its practitioners, who must remain aware of their own ideological preconceptions to move forward in their research program. However, such reflection often remains excluded from the everyday activity of empirical disciplines. To combine these two might provide a starting point in the effort to transcend the division instituted by Dilthey and to approach the vision expressed by Kuhn, of science and art as one. In its focus on comics—a popular form that lies at the intersection of art history, literary studies, and empirical aesthetics but escapes their disciplinary boundaries—this volume hopes to mark one beginning of this convergence. The present collection aims to do so by providing insight into three emerging areas of study, which categorize the contributions in this book. We will elaborate on this categorization in the remainder of the introduction.

2. Digital Approaches to Comics Research

Computational methods represent a relatively recent addition to comics research, and it’s fair to say that their potential is not yet recognized by the majority of scholars. Nonetheless, digital approaches to comics already demonstrate a remarkable range across disciplines. At a basic level, any form of empirical research today depends on computation—for the manipulation of experimental material, for implementing and documenting surveys or experiments, and, most importantly, for subsequent statistical analysis. Fields such as linguistics, sociology, and cognitive science have already gone through their respective ‘digital turns’ and, as a consequence, may offer significant expertise to humanists interested in empirical work. For most humanities scholars, in contrast, computation first enters their professional lives in the form of digitization. Given that comics were historically disseminated in print, their retroactive digitization constitutes an essential undertaking that enables further research but also raises important questions in its own right, including documentation standards and copyright law. These will continue to prove important considerations for empirical comics researchers for the foreseeable future.

However, digitization constitutes only one starting point if we want to apply computation to comics. Scholars such as John Walsh, Christophe Rigaud, and John Bateman have laid important foundations in recent years by formally describi...