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Thinking Through Signs: PEEL as a Semiotic Scaffolding for Epistemically Accountable AI-Enabled Research

Researchers have introduced PEEL (Protocols for Epistemically Engaged Literacy in AI), a semiotic scaffolding framework that combines deterministic distant reading with LLM interpretation to address epistemic accountability in AI-enabled research. Applied to AI-generated condensations of three source texts, PEEL revealed systematic distortions in quantity, term frequency, and epistemic voice that remain invisible without non-AI measurement tools. The framework yields three design implications: deterministic instruments must accompany AI tools, fluency does not equal fidelity, and epistemic authority must be designed into research systems rather than assumed.

read2 min publishedJun 4, 2026
[Submitted on 2 Jun 2026]


[View PDF](/pdf/2606.04152)

Abstract:Large language models are reshaping research practice while quietly eroding researchers epistemic accountability. This commentary introduces PEEL - Protocols for Epistemically Engaged Literacy in AI, a working scaffolding that combines deterministic distant reading via Voyant Tools with LLM interpretation via Claude, grounded in Peircean semiotics and abductive reasoning. Applied to AI-generated condensations of three source texts, PEEL reveals systematic distortions in quantity, term frequency, and epistemic voice that are invisible without non-AI measurement -- and yields three design implications: deterministic instruments must accompany AI tools; fluency is not fidelity; epistemic authority must be designed in, not assumed.

Submission history #

From: Juliana Ferreira J [[view email](/show-email/e703b72b/2606.04152)]

**[v1]** Tue, 2 Jun 2026 19:19:52 UTC (1,821 KB)

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