[Note: When I originally wrote this post it was simply my reaction to David L. Hoover’s essay “Quantitative Analysis and Literary Studies.” The ending of the post was rather weak, largely because I was discouraged by my own desire for definitive and objective data within my project and the realisation that, at present, it does not exist. Perhaps I had fallen into the cognitive distortion of “All or Nothing” thinking,[1] where because it could not be perfect, I viewed my project as a total failure, unable to provide any knowledge about the emblems. So, I delayed posting it.
During the delay, I began reading Jerome McGann’s book Radiant Textuality: Literature after the World Wide Web. Hope returned, bringing with it a more realistic sense of how things stand. What follows is partially the original post, now edited with some references to McGann. As a nod toward McGann’s work with online archives, I have decided to clearly indicate my edits: additions are italicised in square brackets; deleted sections have been retained in footnotes. My goal with this experiment, is to retain both interpretations, to explicitly show my subjective view, simply because I believe my project, and other quantitative humanities projects, benefit from such candor, as it makes interpretive decisions more apparent for the end-user/reader. Thus, it seems a good idea to begin the practice now, showing what was changed much like the “historical log” of project changes McGann discusses (92-93).]
Given the problem I discussed last post, it is of little surprise that reading David L. Hoover frustrated me further. Hoover differentiates what close reading and quantifiable analysis can do, and thus what sort of arguments one can make based on the approach. Additionally, he emphasises the “numerical” nature of quantitative approaches especially the element of “accuracy” inherent in mathematics in “measurement, classification, and analysis” (“History, Goals,…”).[2] One thus gets the idea that Hoover wants to separate an individual’s interpretations from the gathering of the data itself. Such a reading is bolstered by his emphasis on automating steps (“Methods”) and his critical response to a quote regarding using “traditional critical interpretation” to “understand the meaning of those statistics.” Hoover indicates that such an approach could be misleading, though he does not seem to discount it entirely (“Four Exemplary Studies”).[3] [Hoover wants a high level, or even complete, objectivity; the objectivity of mathematics (“History, Goals,…”). Jerome McGann counters that “Objectively considered, objectivity is impossible” and the pursuit of it potentially a hindrance (24). What can/should be aimed for is “self-conscious subjectivity” (24), that is, a high-level awareness of one’s interpretations, influences and choices. Such a goal includes, ideally, an accounting of those choices/standards to one’s end-user/audience, allowing them to make a more informed decision as to the usefulness of your data and interpretations. That is not an easy task; Emblematica Online, for example, discusses that it will use Iconclass on its “About the Project” (last paragraph of “Metadata” section). However, I haven’t been able to locate a statement regarding how thorough and complete they intend to tag, or what decisions/guidelines they mandated in their tagging.[4] Where Hoover would likely discard the data I intend to use, McGann would likely accept it, granting that there are challenges to over-come as I go.]
Hoover presents several challenges in his first two sections. In discussing Woolf, he states that to claim something as “characteristic” as “unusual” requires quantified comparison (“History, Goals…”). I would like to know which symbols/symbol complexes are part of larger patterns and which are restricted to a particular work; but I cannot, at present, compare all 1,388 emblem books on Emblematica Online simply because not all of the emblems have been tagged, nor is there a program that can accurately search images for specific parts (given differences in drawing, for example). So perhaps I cannot make claims regarding what is truly a pattern for the whole genre, but I could make a statement regarding the texts I do sample, presenting it similarly to how Hoover does “in a corpus of 46 Victorian novels by six authors…” (“Methods”). Hoover is right when he says that anything “that can be reliably identified can be counted” (“Methods” my emphasis). The issue is inherent in the word “reliably”. Even Hoover admits that “semantic categories”, which images as signs/symbols arguably fall into, are “more difficult to count” (“Methods”), likely for that very reason. [While Hoover proposes an automated system to deal with “semantic categories”(“Methods”), McGann discusses the need for tools for individuals to mark up images, specifically allowing parts of images to be accessible to researchers in a searchable, and likely countable, way (62, 69, 94-95). McGann, unlike Hoover, seems to favour a hands-on approach in this regard. McGann leaves room for the human.]
[5][Originally, I bought in to Hoover’s statement that “poor initial choices can lead to wasted effort and worthless results” (“Methods”) and I considered whether using the Iconclass decisions of others was such a mistake. McGann himself writes “it does not bode well to begin with a logic one knows to be inadequate” (90). It is quite easy to see issues with the Iconclass data I intend to use; for example, individual taggers may have tagged things slightly differently.[6] If I aspire to Hoover’s level of objective certainty, then the issues with this data become unbearable. BUT, McGann’s next sentence applies: “On the other hand, what were the choices?” (90). Additionally, like McGann, I take issue with Hoover’s apparent assertion that failure is “worthless” (“Methods”). McGann writes about the “unexpected rewards of failure” (82). He indicates a growth in knowledge not just of the object(s) studied, but also of the one’s own methods.[7] He even relates an instance where playing, or experimenting, with tools revealed unexpected things, prompting further exploration (82-87). While Hoover seems to want each project to know exactly where it will go,[8]McGann is more open to serendipity, while still arguing for documentation of choices and standards (91-93 for example) and for consistent application (for example, image alterations that appeared useful in one instance, were recorded and exactly applied to others for comparative purposes; see 85). From such a perspective, one cannot know if a previous choice is “poor”, until one works with it, and since one still learns, the effort and results can never be completely “worthless”. I choose to follow McGann, and learn where I am going, as I am going there.]
Works Cited
Burns, David D. “Checklist of Cognitive Distortions.” 1999. PDF file.
Hoover, David L. “Quantitative Analysis and Literary Studies.” A Companion to Digital Literary Studies. Ed. Ray Siemens and Susan Schreibman. Oxford: Blackwell, 2008. Web. 4 Jan. 2016.
Lavagnino, John. “Digital and Analog Texts.” A Companion to Digital Literary Studies. Ed. Ray Siemens and Susan Schreibman. Oxford: Blackwell, 2008. Web. 12 Nov. 2015.
McGann, Jerome. Radiant Textuality: Literature after the World Wide Web. New York: Palgrave, 2001. Print.
Stäcker, Thomas et al. “About the Project.” Emblematica Online: Resources for Emblem Studies. University of Illinois and Herzog August Bibliothek. Web. 13 Jan. 2016.
[1] See this PDF for more info on cognitive distortions and “All or Nothing” thinking – particularly the first entry in section “The Ten Forms of Twisted Thinking”.
[2] Citations for Hoover indicate section headings due to the lack of page numbers.
[3] Original post: Since the Iconclass metadata relies on humans inputting the data, it seems that human interpretation of the images is inevitable, even if I get a computer to count the tags I am arguably not counting elements of the emblems themselves, (remember that Lavagnino discussed how difficult it is to program a way to count images, given how an object can be drawn many different ways), I am counting others interpretations, even if I can reasonably argue for a level of accuracy in those interpretations. While I am still questioning if that may offer something useful and meaningful, I don’t think Hoover would approve.
[4] [Even with that, McGann notes problems of ambiguity and interpretation of the markup systems within his own project (91). It seems that there is always some wiggle room, no matter how self-conscious or explicit one makes one’s subjectivity. My preference would be for each tag to ‘highlight’ or somehow indicate which portion of the image it is referring to, thereby giving me, and other end-users, an opportunity to evaluate the choice of tag. Alas.]
[5] Original concluding paragraph: Thus I am left with the question, is using the Iconclass tags a “poor initial choice” which “can lead to wasted effort and worthless results” (“Methods”)? I suppose it depends on what questions I want to answer and what claims I hope to make. Still, perhaps I can counter Hoover by asking, what makes a result worthless, even if a result cannot answer questions because of issues in its method, does it not at least teach us about the holes in the method itself and what needs to be improved? If so, is the effort actually wasted?
[6] [I haven’t been able to confirm or deny whether the emblems were tagged by more than one person each; I hope they were, as it at least gives the opportunity for one person to see and tag things the other missed.]
[7] [Or even the limitations of one’s software (94).]
[8] [To be fair, Hoover does leave room for “happy surprises”, though he seems to indicate that those should lead to a separate study in that they call for “further or different quantification” (“Methods”), rather than an integration into the present project.]
