Aug 2026· AI & SOCIETY· 0 citations· 28 references
TL;DR
Through a new formalist reading of English- and Spanish-language short stories generated by ChatGPT-5, it is demonstrated that distributional regularities in language modelling scale upward, producing gendered and culturally normative stylistic patterns.
Abstract
Creative texts produced wholly or partly by large-scale generative language models are increasingly circulating within literary markets and cultural institutions. Research on AI-generated texts has largely examined bias at the level of words and images; however, small-scale statistical co-occurrences in AI-output can generate macro-scale narrative phenomena, where narrative functions intersect with stylistic texture, for example through voice, focalisation, reliability, or omission. This article argues that literary criticism, and New Formalism in particular, offers a necessary methodological framework for identifying and historicising these stylistic asymmetries. A background premise, working against the current techno-utopian ethos that improving algorithms requires more algorithms, is that close, slow reading is necessary to addressing the ethical complexities in literary form, the unsettled nature of language, and the context-specific nature of bias, harm, and oppression (Jackson and Courneya 2023, p. 62). Through a new formalist reading of English- and Spanish-language short stories generated by ChatGPT-5, I demonstrate that distributional regularities in language modelling scale upward, producing gendered and culturally normative stylistic patterns. By shifting the analysis of AI creativity from representation to form, I hope to indicate how literary methods can illuminate narrative-specific dimensions of bias in generative AI output.
This critical narrative review synthesises evidence from ten recent publications in Scopus-indexed journals or conference proceedings, three directly relevant articles from Acta Humanitatis, DIALOGICA, and AI, and proposes a transparent protocol centred on identifiable texts, model and prompt documentation, repeated runs, preserved outputs, bilingual evaluation, linguistic evidence, negative cases, and explicit human responsibility.
The rapid growth of large language models (LLMs) has resurrected age-old questions in sociolinguistics and world Englishes, such as who decides what counts as legitimate English, whose English is suspect etc. This paper examines how AI systems, their uses and discourse on them reflect, reinforce, and occasionally challenge (standard) language ideologies, which privilege Inner Circle norms and marginalize non-dominant Englishes. Drawing on evidence from empirical studies, media commentary, social media debates, and examples from AI outputs, the paper shows that AI technologies reproduce dominant language ideologies at different levels: training data, design protocols, evaluation benchmarks, user feedback and public commentary. The analysis uses the public controversy over AI-sounding language, especially the fixation on the word delve, to illustrate how speakers of English from the Global North police the English language norms of Global South English users. The paper also identifies what Christian Mair has called a"standardisation paradox": AI may homogenize English by privileging standard forms and at the same time pluralize Englishes through exposure to wide-ranging corpora and annotation work carried out by Global South users. In doing so, the paper argues that generative AI is reigniting long-standing debates in World Englishes about standardization, legitimacy, and the ownership of English, now playing out in algorithmic systems, model training, evaluation practices, and public discourse, where non-dominant Englishes are increasingly conflated with AI-generated speech. Discussing AI systems as a site where language ideologies are (re)produced, the paper argues for more inclusive design approaches that recognize the plurality of Englishes in order to address the real-world negative consequences of treating some as more legitimate than others.
It is revealed that GenAI texts underrepresent the subtle interpersonal cues that give writing its persuasive, dialogic, and ethical texture, though they excel in both grammatical accuracy, and lexical variety.
Dr. Daniel Tchorkpa Yokossi, Dr. Servais Dieu-Donne Yedia Dadjo, Dr. Cocou Andre DATONDJI· International Journal of Adv...· 0 citations
Hindi popular cinema in its studio era as well as in its OTT era has been an enduring medium through which speaker types have been socially encoded. The paper uses a bounded corpus of 2025 Hindi language feature films (40 theatrically released and two long-form web series) to explore how the language and paralinguistic decisions create and produce stereotypes of regions, religion, class, occupation, and gender, and how these decisions have changed in the OTT era. The unit of analysis is the character-scene, which is an individual character in an identifiable scene; utterances, accent features, lexical selection, address form and code-mixing are coded as embedded units. Operationalization of six stereotype categories is done by explicit indicator sets and not by impressionistic labels. Gendered language is distinguished from sexist language as the former is grammatical or referential, the latter evaluative and derogatory, placing women in an inferior, subordinate, or consumable position. Dialogue in Hindi–Urdu language is consistently romanised, and each cited example includes a romanised original, an English translation, identification of the speaker, and context for the scene. The paper shows that, while the stereotype grammar of Bihari-as-comic, Christian-as-westernized, English-speaking-woman-as-morally-suspect has been somewhat replaced, it has not been eliminated from the OTT corpus and that gendered-language markings continue to be used even though overt sexist framings are absent.
Cognitive Stylistics occupies an uncomfortable but productive position — caught between cognitive linguistics, literary theory, and psychology, answerable to all three and fully at home in none. The question driving it is deceptively straightforward: what actually happens in a reader’s mind when they move through a text, and how does the language itself shape that experience? This paper takes that question seriously and follows it through the field’s major theoretical commitments, historical development, and methodological range. The argument developed here draws on the work of Reuven Tsur, Mark Turner, Gilles Fauconnier, Elena Semino, Peter Stockwell, and others working broadly within the cognitive-stylistic tradition. What emerges, I want to suggest, is that the field offers something neither formalist analysis nor reader-response criticism has managed to provide on its own: a principled account of aesthetic experience that is theoretically coherent and, at least in aspiration, empirically responsible. The frameworks it has developed — schema theory, mental spaces, conceptual metaphor, blending theory, Text World Theory — are not merely borrowed from cognitive science and applied wholesale to literature. They have been reworked, tested against textual evidence, and refined through sustained engagement with the specific challenges that literary language poses. The paper also steps back occasionally from methodological detail to ask a broader question: where does Cognitive Stylistics stand in relation to ongoing debates about literary meaning, and what does it actually contribute to them? The position it takes, and one this paper broadly endorses, is that the field's distinctive value lies in its refusal to treat text and reader as separate problems to be solved independently. Meaning, on this account, is neither lodged in the text waiting to be extracted nor freely constructed by readers unconstrained by linguistic structure. It happens in the encounter between the two — between a text shaped by deliberate and recoverable choices and a reader who is embodied, historically situated, and bringing a particular mind to the act of reading
Fatima Amin, Dr. Aisha Farid, Usman Ali Nawab· Journal of innovative resear...· 0 citations
The primary objective of this article is to examine the narrative strategies and linguistic style employed by Timeri N. Murari, a prominent author in contemporary Indian English fiction, in his three historical novels namely, Taj, The Imperial Agent, and The Last Victory. Murari redefines history and identity through an array of narrative techniques and stylistic choices. The article also explores key tenets of a literary work such as title, setting, plot, theme, point of view, narration time, and characterisation, highlighting how these techniques formalise both the personal and collective dimensions of history. It further investigates Murari’s peculiar use of diction, syntax, similes, metaphors, humour, and magic realism, which together enrich the texture of his fiction and localise English expression within the Indian context. By weaving cultural idioms, inter-texts, and mythological references into his fiction, Murari formulates a hybrid narrative form that harmonises linguistic innovation with historical imagination. In addition, it demonstrates that Murari’s novels function not only as re-interpretations of historical events but also as artistic explorations of colonialism, nationalism, love, and human experience. Finally, this article argues that Murari’s stylistic and narrative dexterity situates his fiction as an important contribution to the evolution of Indian English historical writing.
Mahendran Rengaraj, Muniyaraj Gurusamy· Communication and Linguistic...· 0 citations