Operationalizing The Urn: Part 1

This post is the first in a series on operationalizing the close reading method in Cleanth Brooks’s The Well Wrought Urn. This post lays out the rationale and stakes for such a method of reading. The second post will perform that distant reading in order to test Brooks’s literary historical claims, and the third post will explore the statistical model in order to ask whether it has captured Brooks’s definition of irony.

Meaning & Structure

keats_urnCleanth Brooks’s The Well Wrought Urn lays out a program of close reading that continues to enjoy great purchase in literary study more than seventy years on. Each of ten chapters performs a virtuosic reading of an individual, canonic poem, while the eleventh chapter steps back to discuss findings and theorize methods. That theorization is familiar today: to paraphrase is heresy; literary interpretation must be highly sensitive to irony, ambiguity, and paradox; and aesthetic texts are taken as “total patterns” or “unities” that give structure to heterogenous materials. These are, of course, the tenets of close reading.

For Brooks, it is precisely the structuring of the subject matter which produces a text’s meaning. On the relationship between these, he claims, “The nature of the material sets the problem to be solved, and the solution is the ordering of the material” (194). A poem is not simply a meditation on a theme, but unfolds as a sequence of ideas, emotions, and images. This framework for understanding the textual object is partly reflected by his method of reading texts dramatically. The mode of reading Brooks advocates requires attention to the process of qualification and revision that is brought by each new phrase and stanza.

This textual structure takes the form of a hierarchy of “resolved tensions,” which produce irony. It is telling that Brooks initially casts textual tension and resolution as a synchronic, spatial pattern, akin to architecture or painting. We may zoom in to observe the text’s images in detail to observe how one particular phrase qualifies the previous one, or we may zoom out to reveal how so many micro-tensions are arranged in relation to one another. To perform this kind of reading, “the relation of each item to the whole context is crucial” (207). Often, irony is a way of accounting for the double meanings that context produces, as it traverses multiple scales of the text.

More recently, distant readers have taken up different scales of textual structure as sites of interpretation. The early LitLab pamphlet, “Style at the Scale of the Sentence” by Sarah Allison et al, offers a taxonomy of the literary sentence observed in thousands of novels. At its root, the taxonomy is characterized by the ordering of independent and dependent clauses — what comes first and how it is qualified. A later pamphlet, “On Paragraphs. Scale, Themes, and Narrative Form” by Mark Algee-Hewitt et al, takes up the paragraph as the novel’s structural middle-scale, where themes are constructed and interpenetrate. Moving to the highest structural level, Andrew Piper’s article “Novel Devotions: Conversional Reading, Computational Modeling, and the Modern Novel”examines how the second half a of novel constitutes a transformation away from its first half in his article.1

Each of these distant readings offers a theorization of its scale of analysis: sentence, paragraph, novel. In the first example, Allison et al ask how it is possible that the relationship between the first half of a given sentence and the second encodes so much information about the larger narrative in which it appears. Indeed, all of the instances above take narrative — the grand unity of the text — as an open question, which they attempt to answer by way of patterns revealed at a particular scale. Brooks offers us a challenge, then: to read at these multiple scales simultaneously.

This simultaneity directs us to an ontological question behind the distant readings mentioned above. (Here, I use ontology especially in its taxonomic sense from information science.) Despite the different scales examined, each of those studies takes the word as a baseline feature for representing a text to the computer. That is, all studies take the word as the site in which narrative patterns have been encoded. Yet, paradoxically, each study decodes a pattern that only becomes visible at a particular scale. For example, the first study interprets patterns of words’ organization within sentence-level boundaries. This is not to imply that the models developed in each of those studies are somehow incomplete — after all, each deals with research questions whose terms are properly defined by their scale. However, the fact that multiple studies have found the word-feature to do differently-scaled work indicates an understanding of its ontological plurality.

Although ontology will not be taken up as an explicit question in this blog series, it haunts the distant readings performed in Parts 2 & 3. In brief, when texts are represented to the computer, it will be shown all three scales of groupings at once. (Only one scale per text to prevent overfitting.) Reading across ontological difference is partly motivated by Alan Liu’s article, “N+1: A Plea for Cross Domain  Data in the Digital Humanities.” There, he calls for distant readings across types of cultural objects, in order to produce unexpected encounters which render them ontologically alien. Liu’s goal is to unsettle familiar disciplinary divisions, so, by that metric, this blog series is the tamest version of such a project. That said, my contention is that irony partly registers the alienness of the cross-scale encounter at the site of the word. Close reading is a method for navigating this all-too-familiar alienness.

While close reading is characterized by its final treatment of texts as closed, organic unities, it is important to remember that this method rests on a fundamentally intertextual and historical claim. Describing the selection of texts he dramatically reads in The Well Wrought Urn, Brooks claims to have represented all important periods “since Shakespeare” and that poems have been chosen in order to demonstrate what they have in common. Rather than content or subject matter, poems from the Early Modern to High Modernism share the structure of meaning described above. Irony would seem to be an invariant feature of modernity.

We can finally raise this as a set of questions. If we perform a distant reading of textual structure at multiple, simultaneous levels, would we find any changes to that structure at the scale of the century? Could such a structure show some of the multiple meanings that traverse individual words in a text? More suggestively: would that be irony?


1. Related work in Schmidt’s “Plot Arceology: a vector-space model of narrative structure.” Similar to the other studies mentioned, Schmidt takes narrative as a driving concern, following the movement of each text through plot space. Methodologically, that article segments texts (in this case, film and TV scripts) into 2-4 minute chunks. This mode of articulation does not square easily with any particular level of novelistic scale, although it speaks to some of the issues of segmentation raised in “On Paragraphs.”


Algee-Hewitt, Mark, et al. “On Paragraphs. Scale, Themes, and Narrative Form.” Literary Lab Pamphlet 10. 2015.

Allison, Sarah, et al. “Style at the Scale of the Sentence.” Literary Lab Pamphlet 5. 2013.

Brooks, Cleanth. The Well Wrought Urn: Studies in the Structure of Poetry. New York : Harcourt, Brace, Jovanovich. 1975.

Liu, Alan. “N+1: A Plea for Cross Domain  Data in the Digital Humanities.” Debates in the Digital Humanities 2016. eds, Matthew K. Gold and Lauren F. Klein. 2016. Accessed March 2, 2017. http://dhdebates.gc.cuny.edu/debates/text/101

Piper, Andrew. “Novel Devotions: Conversional Reading, Computational Modeling, and the Modern Novel.” New Literary History, 46:1 (2015). 63–98.

Schmidt, Ben. “Plot arceology: A vector-space model of narrative structure,” 2015 IEEE International Conference on Big Data (Big Data). Santa Clara, CA. 2015. 1667-1672.

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