International Journal of Practical and Pedagogical Issues in English Education

International Journal of Practical and Pedagogical Issues in English Education

Finding Symbolism in R.F. Kuang’s Yellowface (2023) by ChatGPT: A Qualitative Hermeneutic Inquiry

Document Type : Original Article

Authors
1 Postdoctorial researcher of Mazandaran University
2 Associate Professor of English Language and Literature, University of Mazandaran, Babolsar, Iranو
Abstract
This study undertakes a critical examination of the interpretative abilities of large language models (LLMs), with a particular focus on OpenAI’s ChatGPT-4, in discerning and analyzing complex literary symbolism embedded within culturally and politically nuanced fiction. Using R.F. Kuang’s 2023 satirical novel Yellowface as a focal point, the research adopts a qualitative and iterative prompting methodology to systematically assess the model’s capacity to engage with key symbolic passages. These passages address crucial themes such as cultural appropriation, digital performance, and the persistent phenomenon of historical erasure. The findings demonstrate that, while ChatGPT-4 can reliably recognize overt symbols and effectively apply established theoretical frameworks when given explicit, directive prompts, its default interpretive tendencies reveal notable limitations. Specifically, the model exhibits a consistent pattern of universalizing and, in effect, depoliticizing critiques that are inherently racially and culturally specific. This tendency results in interpretations that lack the contextual depth and specificity essential for a robust engagement with the novel’s satire and its nuanced interrogation of racial capitalism. Indeed, the model’s ability to grapple with satire, multivalent or layered meanings, and the necessity for contextual grounding remains markedly insufficient.
Keywords

Subjects


Alter, A. (2020). ‘American dirt’ roller coaster: Oprah’s pick, then backlash. The New York Timeshttps://www.nytimes.com/2020/01/26/books/american-dirt-controversy.html
Bender, E. M., & Koller, A. (2020). Climbing towards NLU: On meaning, form, and understanding in the age of data. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 5186–5198). Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.acl-main.463
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (pp. 610–623). ACM. https://doi.org/10.1145/3442188.3445922
Benjamin, R. (2019). Race after technology: Abolitionist tools for the new Jim Code. Polity Press.
Berlant, L. (2011). Cruel optimism. Duke University Press. https://doi.org/10.1215/9780822394716
Bode, K. (2018). A world of fiction: Digital collections and the future of literary history. University of Michigan Press. https://doi.org/10.3998/mpub.8784987
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Brock, A. (2020). Distributed blackness: African American cybercultures. New York University Press.
Brouillette, S. (2021). Literature and the creative economy. Stanford University Press.
Brouillette, S. (2021). UNESCO and the fate of the literary. Stanford University Press.
Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. In Proceedings of Machine Learning Research, 81 (pp. 1–15). http://proceedings.mlr.press/v81/buolamwini18a.html
Burkhardt, H., & Hahn, U. (2023). Natural language processing and computational linguistics: A historical perspective. Language and Linguistics Compass, 17(3), e12493. https://doi.org/10.1111/lnc3.12493
D’Ignazio, C., & Klein, L. F. (2020). Data feminism. The MIT Press. https://data-feminism.mitpress.mit.edu/
Da, N. Z. (2019). The computational case against computational literary studies. Critical Inquiry, 45(3), 601–639. https://doi.org/10.1086/702594
Da, N. Z. (2024). The ethical crisis of computational social science: A prolegomenon. Critical Inquiry, 50(3), 458–483. https://doi.org/10.1086/728783
Fisher, M. (2014). Ghosts of my life: Writings on depression, hauntology and lost futures. Zero Books.
Floridi, L. (2023). AI as agency without intelligence: On ChatGPT, large language models, and other generative models. Philosophy & Technology, 36(1), 15. https://doi.org/10.1007/s13347-023-00621-y
Floridi, L. (2023). The ethics of artificial intelligence: Principles, challenges, and opportunities. Oxford University Press.
Gillespie, T. (2014). The relevance of algorithms. In T. Gillespie, P. J. Boczkowski, & K. A. Foot (Eds.), Media technologies: Essays on communication, materiality, and society (pp. 167-194). The MIT Press. https://doi.org/10.7551/mitpress/9780262525374.003.0011
Gordon, A. F. (2008). Ghostly matters: Haunting and the sociological imagination (2nd ed.). University of Minnesota Press.
Han, B.-C. (2017). In the swarm: Digital prospects (E. Butler, Trans.). MIT Press.
Harris, C. I. (1993). Whiteness as property. Harvard Law Review, 106(8), 1707–1791. https://doi.org/10.2307/1341787
Hayles, N. K. (2017). Unthought: The power of the cognitive nonconscious. University of Chicago Press. https://doi.org/10.7208/chicago/9780226447919.001.0001
Hutcheon, L. (1994). Irony’s edge: The theory and politics of irony. Routledge.
Jockers, M. L. (2013). Macroanalysis: Digital methods and literary history. University of Illinois Press.
Jordan, T. (2023). Yellowface by R.F. Kuang review – A satirical tale of literary theft. The Guardianhttps://www.theguardian.com/books/2023/may/25/yellowface-by-rf-kuang-review-a-satirical-tale-of-literary-theft
Jurgenson, N. (2019). The social photo: On photography and social media. Verso Books.
Kim, J. (2023). Racial masquerade in the age of the algorithm. American Literary History, 35(4), 789–812. https://doi.org/10.1093/alh/ajad012
Klein, L. F., & D’Ignazio, C. (2020). Data feminism. MIT Press. https://doi.org/10.7551/mitpress/11805.001.0001
Kuang, R. F. (2023). Yellowface. William Morrow. https://www.harpercollins.com/products/yellowface-r-f-kuang
Lee, S. (2024). Algorithmic hauntings: AI and the spectrality of data. University of California Press.
Lee, Y. S. (2021). Modern minority: Asian American literature and everyday life. Oxford University Press.
Levine, C. (2015). Forms: Whole, rhythm, hierarchy, network. Princeton University Press.
Lin, Y. (2023). Digital blackface and the performance of pain in R.F. Kuang's Yellowface. Journal of Asian American Studies, 26(3), 45-68. https://doi.org/10.1353/jaas.2023.0045
Liu, C. (2023). Digital blackface and the limits of allyship. PMLA, 138(2), 134–156. https://doi.org/10.1632/S0030812923000070
Long, H., & So, R. J. (2021). Literary pattern recognition: Modernism between close reading and machine learning. University of Washington Press.
Lowe, L. (2015). The intimacies of four continents. Duke University Press. https://doi.org/10.1215/9780822375647
Lye, C. (2005). America’s Asia: Racial form and American literature, 1893–1945. Princeton University Press.
McMillan Cottom, T. (2020). Where platform capitalism and racial capitalism meet: The sociology of race and racism in the digital society. Sociology of Race and Ethnicity, 6(4), 441–449. https://doi.org/10.1177/2332649220947933
McMillan Cottom, T. (2023). Behind the diversity numbers: How platforms profit from racial performance. Public Bookshttps://www.publicbooks.org/behind-the-diversity-numbers-how-platforms-profit-from-racial-performance/
Melamed, J. (2015). Racial capitalism. Critical Ethnic Studies, 1(1), 76–85. https://doi.org/10.5749/jcritethnstud.1.1.0076
Moretti, F. (2013). Distant reading. Verso Books.
Morrison, T. (1987). Beloved. Alfred A. Knopf.
Nakamura, L. (2002). Cybertypes: Race, ethnicity, and identity on the internet. Routledge.
Nakamura, L. (2008). Digitizing race: Visual cultures of the internet. University of Minnesota Press.
Ngai, S. (2012). Ugly feelings. Harvard University Press.
Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York University Press. https://doi.org/10.18574/nyu/9781479833641.001.0001
OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com/chat
Park, J. (2023). Authenticity games in platform publishing. American Literary History, 35(3), 211–225. https://doi.org/10.1093/alh/ajad017
Risam, R. (2018). New digital worlds: Postcolonial digital humanities in theory, praxis, and pedagogy. Northwestern University Press.
Robinson, C. J. (1983). Black Marxism: The making of the Black radical tradition. The University of North Carolina Press.
Sandvig, C., Hamilton, K., Karahalios, K., & Langbort, C. (2014). Auditing algorithms: Research methods for detecting discrimination on internet platforms. In Data and Discrimination: Converting Critical Concerns into Productive Inquiry (pp. 1–23).
Spivak, G. C. (1988). Can the subaltern speak? In C. Nelson & L. Grossberg (Eds.), Marxism and the interpretation of culture (pp. 271–313). University of Illinois Press.
Stokes, C. (2021). Digital blackface: The repackaging of the black body in the age of social media. Social Media + Society, 7(4). https://doi.org/10.1177/20563051211053868
Underwood, T. (2019). Distant horizons: Digital evidence and literary change. University of Chicago Press. https://doi.org/10.7208/chicago/9780226612833.001.0001
Weidinger, L., Mellor, J., Rauh, M., Griffin, C., Uesato, J., Huang, P., & Gabriel, I. (2022). Ethical and social risks of harm from language models. In Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency (pp. 214–229). ACM. https://doi.org/10.1145/3531146.3533088
Wolfe, P. (2006). Settler colonialism and the elimination of the native. Journal of Genocide Research, 8(4), 387–409. https://doi.org/10.1080/14623520601056240
Volume 3, Issue 4
Autumn 2025
Pages 139-158

  • Receive Date 06 September 2025
  • Revise Date 27 November 2025
  • Accept Date 02 December 2025