Maite Taboada

Toward Automated Discourse Network Analysis

Discourse Network Analysis has long been capped by the price of expert judgment. Here is a design for automating it at corpus scale without surrendering command of meaning — and FineStructure, the open-source workbench I am building for it.

Computation and its Connotations

A Review of Language Machines by Leif Weatherby

Reflexive discourse analysis: A methodology for the practice of reflexivity

How to implement reflexivity in practice? Can the knowledge we produce be emancipatory when our discourses recursively originate in the world we aim to challenge? Critical International Relations (IR) scholars have successfully put reflexivity on the agenda based on the theoretical premise that discourse and knowledge play a socio-political role. However, academics often find themselves at a loss when it comes to implementing reflexivity due to the lack of adapted methodological and pedagogical material. This article shifts reflexivity from meta-reflections on the situatedness of research into a distinctive practice of research and writing that can be learned and taught alongside other research practices. To do so, I develop a methodology based on discourse: reflexive discourse analysis (RDA). Based on the discourse analysis of our own discourse and self-resocialisation, RDA aims to reflexively assess and transform our socio-discursive engagement with the world, so as to render it consistent with our intentional socio-political objectives. RDA builds upon a theoretical framework integrating discourse theory to Bourdieu’s conceptual apparatus for reflexivity and practices illustrated in the works of Comte and La Boétie. To illustrate this methodology, I used this very article as a recursive performance. I show how RDA enabled me to identify implicit discriminative mechanisms within my discourse and transform them into an alternative based on love, to produce an article more in line with my socio-political objectives. Overall, this article turns reflexivity into a critical methodology for social change and demonstrates how to integrate criticality methodologically into research and writing.

lexicon

Word clouds and lexicon-tagged views of someone's prose.

We Have Always Been Action TheoristsToward a Critical Theory of Language for the Era of “Large Language Models”

Scholars of literature and culture understandably place themselves among the world’s premiere experts on matters of language. But they also know that fields like linguistics and communication have their own ways of studying how people express themselves through speech and written media. A key difference concerns the theories and methodologies...

Thinking modes

Floating in linguistic space.

Getting started - Docs

Discourse Graphs are a tool and ecosystem for collaborative knowledge synthesis, enabling researchers to map ideas and arguments in a modular, composable graph format.

Contra Literacy-Laundering: Mechanistic Critical AI Literacy

Critical discourse on large language models (LLMs) has bifurcated between epistemic dismissal that invokes some form of the stochastic parrot metaphor to puncture hype, and pragmatic accommodation that treats LLM capability improvements as grounds for updating the critique. We argue that both misdiagnose the problem as the issue is not whether or not LLMs work, but what kind of working is happening and at whose cost. Drawing on meta-theoretical frameworks of cognitive science, feminist labor analysis and critical pedagogy, we propose a conceptual reorientation. We develop this claim through registers of (i) the cognitive, examining what is forfeited when statistical pattern-matching substitutes for the iterative, grounded processes that constitute thinking; (ii) the pedagogical, examining how “AI literacy” as currently deployed is itself a symptom of the confusion it purports to address; and (iii) the political, examining how the infrastructure framing of AI naturalizes asymmetric labor displacement, particularly of feminized cognitive and reproductive work. The stochastic parrot, deployed with mechanistic precision rather than mere rhetorical convenience, specifies what is forfeited when cognitive labor is delegated, who bears the cost, and why a literacy adequate to this moment must begin from the epistemology of those most harmed by the systems it describes. We conclude with underlining that critical AI literacy, which this paper embodies an instance of, is the only sensible way forward.

Why mental metaphors do not help us understand chatbot mistakes

The function of chatbots like OpenAI’s ChatGPT is based on detecting probabilistic patterns in the training data. This makes them vulnerable to generating factual mistakes in their outputs. Recently, it has become commonplace in philosophical, scientific, and popular discourses to capture such mistakes by metaphors that draw on discourses about the human mind. The two most popular metaphors at present are hallucinating and bullshitting. In this paper, we review, discuss, and criticise these mental metaphors. By applying conceptual metaphor theory, we provide numerous reasons why they do not succeed in providing us with a better understanding of factual chatbot mistakes. We conclude by calling for justifications of the epistemic feasibility and fruitfulness of the metaphors at issue. Furthermore, we raise the question what would be lost if we stopped trying to capture factual chatbot mistakes by mental metaphors.

ChatGPT is bullshit

Ethics and Information Technology - Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of...

Do LLMs write like humans? Variation in grammatical and rhetorical styles

As large language models (LLMs) have grown in power and become more widely available, research has focused on their ability to complete various tasks and the biases they exhibit when doing so. In this study, we instead examine their writing style in detail. We show that instruction-tuned models, which are trained to answer questions and solve problems, have a distinct noun-heavy, informationally dense writing style, even when prompted to match the style of informal speech and writing. These findings suggest that instruction-tuned models generate text that does not align with genre conventions familiar to human audiences, and demonstrate the value of linguistic variables in evaluating the output of LLMs., Large language models (LLMs) are capable of writing grammatical text that follows instructions, answers questions, and solves problems. As they have advanced, it has become difficult to distinguish their output from human-written text. While past research has found some differences in features such as word choice and punctuation and developed classifiers to detect LLM output, none has studied the rhetorical styles of LLMs. Using several variants of Llama 3 and GPT-4o, we construct two parallel corpora of human- and LLM-written texts from common prompts. Using Douglas Biber’s set of lexical, grammatical, and rhetorical features, we identify systematic differences between LLMs and humans and between different LLMs. These differences persist when moving from smaller models to larger ones and are larger for instruction-tuned models than base models. This observation of differences demonstrates that despite their advanced abilities, LLMs struggle to match human stylistic variation. Attention to more advanced linguistic features can hence detect patterns in their behavior not previously recognized.

Marking one’s own viewpoint: The Finnish evidential verb+kseni ‘as far as I understand’ construction

This article examines evidentiality in the frame of inferential adverbs in written interaction from the perspective of Finnish, a language that does not have evidentiality as a grammatical category. The analysis focuses on six adverbs, such as käsittääkseni ‘as far as I understand’ and tietääkseni ‘to my knowledge, as far as I know’. Evidentiality and epistemic modality intertwine in their semantics, as these adverbs represent a writer’s access to information, but also indicate her evaluation of its reliability. First, this article offers a description of the interactional functions of these adverbs such as marking a writer’s opinion in contrasts, expressing slight hedging in order to anticipate corrections, to allow space for other opinions, or to create irony. Second, in the framework of cognitive grammar, the analysis focuses on the meaning of the evidential verb+kseni construction and the effect of different verb stems on it. These adverbs share similar functions in texts, which is due to their flexible constructional meaning. While varying from lexeme to lexeme, specific evidential and epistemic dimensions can either be foregrounded and relevant in a situation or remain backgrounded and not activated.