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Published online by Cambridge University Press: 06 September 2021
This article asks, on a systemic scale, how published articles in “Slavic Studies” do and do not reflect critically on race and other cultural constructions of identity. Digital Humanities methods provide a digital bird's-eye view of over 100,000 scholarly texts, primarily in Russian and English, through three computational approaches: frequency analysis, topic modeling, and perspectival modeling. The authors demonstrate that there is an absence of critical tools for conducting research about race in our field, despite a prevalence of racialized subject matter. These results offer a data-based refutation of the common misconception that race is outside the scholarly concerns of our field. Rather, the data affirms student accounts of the field's inadequacies in grappling with race and racism, both in historical objects of study and in the world that scholars navigate. Digital methods also locate scholarship inside and outside Slavic Studies that offers positive guidance for future work.
1. Sarah Valentine, “Russian Studies’ Alt-Right Problem,” The Chronicle of Higher Education, September 29, 2017 at https://www.chronicle.com/article/russian-studies-alt-right-problem/ (accessed May 3, 2021).
2. Ibid.
3. See also, Bonilla-Silva, Eduardo, Racism Without Racists: Color-Blind Racism and the Persistence of Racial Inequality in America (Lanham, MD, 2017)Google Scholar.
4. AATSEEL Executive Council, “AATSEEL Statement Concerning Systemic Racism and Police Brutality in the United States,” June 2020 at https://www.aatseel.org/about/presidents-message/messages/#stop_racism (accessed May 3, 2021).
5. For example, Waclaw Lednicki and Roman Jakobson traded statements in 1954. Lednicki, Waclaw, “The State of Slavic Studies in America,” The American Slavic and East European Review 13, no. 1 (February 1954)CrossRefGoogle Scholar; Jakobson, Roman, “Comparative Slavic Studies,” The Review of Politics 16, no. 1 (January, 1954): 67–90CrossRefGoogle Scholar. In Lednicki’s call to the “state of the field,” Slavic Studies must serve to “explain to the American people the cultural differentiation which exists behind the ‘Iron Curtain’….” Lednicki, 108. Jakobson promoted a definition of “Slavic Studies” on linguistic grounds. Jakobson writes, “Slavic peoples are to be defined basically as a Slavic-speaking peoples.” Questions of ethnic identity are smoothed to encompass a unified classification capable of countering the “subsidiary, marginal” position “Slavs” had in the US scholarly landscape. Jakobson, 67.
6. Gorenburg, Dmitry P. and Suny, Ronald G., “Where Are We Going? What is To Be Done?,” AAASS NewsNet 46, no.4 (August 2006): 1, 3Google Scholar, available at https://pitt.app.box.com/s/5jbxq0iql803x6m99g62ki413nvtb5ll (accessed May 3, 2021). The American Association for the Advancement of Slavic Studies transitioned to become the Association for Slavic, East European, and Eurasian Studies. AATSEEL remains the American Association of Teachers of Slavic and East European Languages.
7. Ani Kokobobo, “What’s in a Name? Are We Slavic, East European, Eurasian, or All of the Above?” ASEEES NewsNet (August 2020), 17, available at https://www.aseees.org/news-events/aseees-blog-feed/what%E2%80%99s-name-are-we-slavic-east-european-eurasian-or-all-above (accessed May 3, 2021).
8. Rachel Poser, “He Wants to Save Classics From Whiteness. Can the Field Survive?,” New York Times Magazine (February 20, 2021) at https://www.nytimes.com/2021/02/02/magazine/classics-greece-rome-whiteness.html (accessed May 3, 2021).
9. Ibid.
10. See Matthew K. Gold, ed., Debates in the Digital Humanities (Minneapolis, 2012) at https://dhdebates.gc.cuny.edu/projects/debates-in-the-digital-humanities (accessed May 3, 2021).
11. Tara McPherson, “Why Are the Digital Humanities So White? or Thinking the Histories of Race and Computation,” in Matthew K. God, ed., Debates in the Digital Humanities at https://dhdebates.gc.cuny.edu/read/untitled-88c11800–9446–469b-a3be-3fdb36bfbd1e/section/20df8acd-9ab9–4f35–8a5d-e91aa5f4a0ea#ch09 (accessed May 3, 2021).
12. “Rapid Response Research (RRR) projects are quickly deployed scholarly interventions in pressing political, social, and cultural crises. Together, teams of researchers, technologists, librarians, faculty, and students can pool their existing skills and knowledge to make swift and thoughtful contributions through digital scholarship in these times of crisis.” The Nimble Tents Toolkit at https://nimbletents.github.io (accessed May 3, 2021).
13. See Chike Jeffers, “Cultural Constructionism,” in Joshua Glasgow, Sally Haslanger, Chike Jeffers, and Quayshawn Spencer, eds., What Is Race?: Four Philosophical Views (New York, 2019).
14. Our project GitHub repository is available at https://github.com/Russian-NLP/Reading-Racial-Discrimination-in-Slavic-Studies-Scholarship (accessed May 3, 2021).
15. See Hatebase at https://hatebase.org/ (accessed May 3, 2021). This database contains terms related to nationality, ethnicity, religion, gender, sexual orientation, disability, and class in ninety-five languages. It is based on texts from 175 countries.
16. To filter out the adjective for black in Spanish (“negro”) we identified the language of each text and did not include Spanish-language texts in the count. A regular expression r“\bnegro\b” was used to exclude the word Montenegro and other similar terms that might give false positive matches.
17. Frequency analysis can point to articles that use Hatebase terms often. This approach is most likely to locate positive role models. For example, scholars of southeastern Europe have already demonstrated the feasibility of a mass shift away from the casual repetition of racialized hate speech in their increasing use of the words “Romani” and “Roma” rather than the often-pejorative term “gypsy.” While the terms “gypsy” and “gypsies” were the most common Hatebase terms in our corpus, with 1,872 and 2,058 uses respectively (and 4,664 uses for tsygan[e] in Russian), we found that their use has decreased noticeably since 2016. Recent pieces that do include these words often use “Romani” as well and contextualize the difference.
18. In brief, we used the BERT model for TF-IDF. See the GitHub for a full explanation.
19. For an accessible and brief explanation of topic modeling, see Teddy Roland, “Topic Modeling: What Humanists Actually Do With It,” Digital Humanities at Berkeley, July 14, 2016 at https://digitalhumanities.berkeley.edu/blog/16/07/14/topic-modeling-what-humanists-actually-do-it-guest-post-teddy-roland-university (accessed May 3, 2021).
20. Note that this topic is actually listed second in our results, as there is a topic #0. In topic #1, the first thirty terms in order are as follows: feminist, feminism, trafficking, papa, mama, gay, feminists, girls, lesbian, husband, mothers, sisters, yesterday, dowry, zhenotdel, daughter, sex, daughters, married, husbands, divorce, sexuality, pokrovskaia, prostitution, rosslyn, motherhood, khaia, marriage, parnok, heroine. For our full results from this algorithm, see the following file on this article’s GitHub repository at https://github.com/Russian-NLP/Reading-Racial-Discrimination-in-Slavic-Studies-Scholarship/blob/main/1_topic_modeling/SlavicStudiesN3_BERTopic.csv (accessed May 3, 2021).
21. Recent Anglophone contributions to this line of thought have come from scholars in a wide range of subfields. In Critical Romani Studies, these scholars include Dušan Bjelić, Alaina Lemon, Sunnie Rucker-Chang, Chelsi West Ohueri, Catherine Baker, Alicia Strong, and many more. In Jewish Studies, they include Marina Mogilner, Eugene Avrutin, and Amelia Glaser. In Soviet and socialist history, contributions have emerged from Eric Weitz, Maria Gertrudis van Enckevort, Kate Baldwin, Maxim Matusevich, Joy Gleason Carew, Meredith Roman, Carole Boyce Davies, Steven Lee, Hilary Lynd, Kimberly St. Julian-Varnon, and others. Jennifer Wilson has examined Russian racial ideologies and the Haitian Revolution; Bolaji Balogun and Lenny A. Ureña Valerio have written on race in Poland. For a summative look at some of these developments as well as new directions, see Rainbow, David, ed., Ideologies of Race: Imperial Russia and the Soviet Union in Global Context (Montreal, 2019)CrossRefGoogle Scholar.
22. Another topic, #43, included occasional ethnic designations (such as “roma,” 8th) following terms related to World War II (“vojcehovskij,” 2nd; “truman,” 5th; “wartime,” 7th).
23. The fingerprint for Topic #79 included scattered demonyms and place names related to eastern Europe as well as two framing terms: “nationalisation” (3rd) and “postcolonial” (9th). This topic reflects a tendency in our field to use these terms widely without reference to the perceived categories of hereditary physiological or physiognomic difference (namely, ethnicity and race) that often underlay nationalization and colonization, particularly to the east and south of Moscow.
24. For example, topic #0 foregrounded more than a dozen terms historically related to non-Slavic identity, from “estonian” (9th) and “armenia” (15th) to “sakha” (48th), “romanians” (73rd), and “tatars” (77th). However, the topic’s fingerprint as a whole was centered not on ethnicity but on 20th-century literature and policy, with terms like “yeltsin” (8th), “kgb” (10th), “gorky” (11th), “platonov” (16th), and “perestroika” (49th).
25. See Topic #50 in our 2-gram model at https://github.com/Russian-NLP/Reading-Racial-Discrimination-in-Slavic-Studies-Scholarship/blob/main/1_topic_modeling/SlavicStudiesN3_BERTopic.csv (accessed June 11, 2021).
26. Underwood, Ted, Distant Horizons: Digital Evidence and Literary Change (Chicago, 2019), 67CrossRefGoogle Scholar. See also: Bode, Katherine, “Why You Can’t Model Away Bias” Modern Language Quarterly 81, no. 1 (March 2020): 95–124CrossRefGoogle Scholar, Jockers, Matthew Lee, Macroanalysis: Digital Methods and Literary History (Urbana, IL, 2013)CrossRefGoogle Scholar.
27. The classifiers were trained using the spaCy natural language processing library. Full notebooks for this process can be found in the article’s code repository.
28. Bellows, Amanda Brickell, American Slavery and Russian Serfdom in the Post-Emancipation Imagination (Chapel Hill, NC, 2020)CrossRefGoogle Scholar.
29. We can identify terms that most distinguish the African American Studies group from the Slavic Studies group using raw frequency counts or a scaled F-Score. If these terms (e.g., “black,” “tuskegee,” or “liberia”) are included in a work of Slavic Studies, they increase the African American Studies classification score of that text. Similarly, there are terms that are highly distinctive of Slavic Studies. They include any words written in Cyrillic, “dostoevskii,” “aatseel,” and “clitics,” among others. The texts most strongly identified as Slavic (0.999955) are a biography of Dostoevskii, a history of communist Europe, and a history of the Russian steppe.
30. The shift is evident in the African American Studies data as a 3516% increase in the interquartile range (IQR), which is a common measure of statistical spread. In the Gender Studies predictions the IQR changes by 583%. Rather than being clustered near 0 or 1, the predictions between 2015 and 2020 are far more uncertain with more points spread near the middle of the graph (0.5).
31. Cf. Vladimir Davydov, Latinoamérica y Rusia (Buenos Aires, 2018); Jan Bazant, Tres prominentes checos: Tomas Masaryk, Eduardo Benes y Alejandro Dubcek: Ensayos biográficos y textos (Mexico City, 1999); Jean Meyer, “¿Se Puede Hablar Hoy De Populismo En Rusia?” in Guy Hermet, Soledad Loaeza, and Jean-François Prud’homme, eds., Del populismo de los antiguos al populismo de los modernos (Mexico City, 2001).
32. The language of each text was predicted using the langdetect Python library at https://pypi.org/project/langdetect/ (accessed May 3, 2021). Full data can be found in the GitHub repository.
33. There is an equally significant dearth of Slavic languages in the Gender Studies corpus. There is only one Gender Studies article published in Czech, two in Croatian, and one in Romanian. There are no articles in Russian. Given that there is significant Gender Studies scholarship being published in these languages, their absence is likely a sampling problem that reflects the materials available in JSTOR. A keyword search for “Slavic Studies” in Worldcat returns materials in 57 languages. However, 87% of those texts are in English followed by Russian (5%) and German (3%). Fifty of the languages each compose less than 1% of the Worldcat sample. See https://www.worldcat.org/search?q=kw%3ASlavic+Studies, accessed on March 17, 2021.
34. Underwood, Distant Horizons, 34.
35. See articles by Rachel Stauffer, B. Amarilis Lugo De Fabritz, Amber Casandra Walden, and Kristin Torres in AATSEEL Newsletter 58 no. 3 (October 2015) at https://www.aatseel.org/100111/pdf/aatseel_newsletter_october_2015.pdf (accessed May 3, 2021); B. Amarilis Lugo De Fabritz, “Race, Diversity, and Our Students in Russia,” NYU Jordan Center (blog), August 21, 2013 at http://jordanrussiacenter.org/news/race-diversity-and-our-students-in-russia/ (accessed May 3, 2021); Aisha Powell, “Black Bread: A Look inside the World of Black Slavic Studies Scholars,” Trumplandia Magazine, December 8, 2018 at https://trumplandiamagazine.com/black-bread-a-look-inside-the-world-of-black-slavic-studies-scholars-7579c6b2d5cd (accessed May 3, 2021); Jennifer Wilson, “Is Slavic ready for Minorities?” NYU Jordan Center (blog), July 22, 2014 at https://jordanrussiacenter.org/news/slavic-studies-racially-tone-deaf/#.X20jM31Khv1 (accessed May 3, 2021); Kimberly St. Julian-Varnon, “A Voice from the Slavic Studies Edge: On Being a Black Woman in the Field,” ASEEES Newsletter, September 2020 at https://www.aseees.org/news-events/aseees-blog-feed/voice-slavic-studies-edge-being-black-woman-field (accessed May 3, 2021); Sarah Valentine, “The Divine Auditor,” Prairie Schooner 87, no. 2 (Summer 2013): 91–104; Emily Couch, “Beyond Diversity: Integrating Racial Justice into REECA Studies,” ASEEES NewsNet 60, no. 5 (October 2020): 11–13 available at https://www.aseees.org/news-events/aseees-blog-feed/beyond-diversity-integrating-racial-justice-reeca-studies (accessed May 3, 2021).
