Distance Reading and Quantification

I like the main point that Ted Underwood made about the separation between digital techniques and the long history of distance reading in his article, “A Genealogy of Distant Reading.”[1]  Underwood recognizes that scholars have been doing distant reading of texts long before digital techniques came about and were applied to it. Digital tools and methods can aid in the process but are not required to undertake complicated literary analysis. This distinction was made clear to me in the Voyant lab exercise we did in class. I ran General William “Tecumseh” Sherman’s 1875 memoir through Voyant. The word analysis did not reveal to me anything I did not already understand about the memoir. I knew it was Sherman’s explanation of his command decisions over the course of the American Civil War.  The fact that the most common words were “general, army, men, time, war, colonel, command, major, Sherman, division, enemy and river” did not significantly alter this view, nor did these provide me with new, revelatory insights. My thoughts about quantification were also reinforced this week after reading and presenting Jacqueline Wernimont’s chapter “Quantification.”[2]  She argues, and I agree, that quantification is to a certain degree unavoidable.  But it is of critical importance to recognize that numbers are not “truth” or indisputable “facts.’”  There are underlying variables that always render quantification inaccurate.  Additionally, we must always be aware that the selection of criteria for quantification will always mask or disadvantage some groups of people from inclusion or consideration. Practitioners in DH need to remain aware that generating numbers, or applying quantification tools, or using digital techniques to analyze data are inherently flawed.

[1] Ted Underwood, “A Genealogy of Distant Reading,” Digital Humanities Quarterly 11 (no. 2), 2017.  Accessed October 13, 2021. http://www.digitalhumanities.org/dhq/vol/11/2/000317/000317.html

[2] Jacqueline Wernimont, “Quantification,” In Nanna Bonde Thylstrup, Daniela Agostinho, Annie Ring, Catherine D’Ignazio and Kristin Veel (Eds.) Uncertain Archives: Critical Keywords for Big Data.  MIT Press, 2021. Pp. 427-431.