Thinking Through Signs: PEEL as a Semiotic Scaffolding for Epistemically Accountable AI-Enabled Research
Summary
This paper introduces PEEL (Protocols for Epistemically Engaged Literacy in AI), a framework combining deterministic text analysis via Voyant Tools with LLM interpretation via Claude, grounded in Peircean semiotics, to expose systematic distortions in AI-generated research summaries and promote epistemic accountability.
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# Thinking Through Signs: PEEL as a Semiotic Scaffolding for Epistemically Accountable AI-Enabled Research Source: [https://arxiv.org/abs/2606.04152](https://arxiv.org/abs/2606.04152) [View PDF](https://arxiv.org/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 \[[view email](https://arxiv.org/show-email/e703b72b/2606.04152)\] **\[v1\]**Tue, 2 Jun 2026 19:19:52 UTC \(1,821 KB\)
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