{"ID":3053207,"CreatedAt":"2026-06-04T04:41:36.695875263Z","UpdatedAt":"2026-06-05T19:19:17.853951865Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.04152","arxiv_id":"2606.04152","title":"Thinking Through Signs: PEEL as a Semiotic Scaffolding for Epistemically Accountable AI-Enabled Research","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.","short_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, g...","url_abs":"https://arxiv.org/abs/2606.04152","url_pdf":"https://arxiv.org/pdf/2606.04152v1","authors":"[\"Clarisse de Souza\",\"Gabriel Barbosa\",\"Simone Diniz Junqueira Barbosa\",\"Bárbara Betts\",\"Renato Cerqueira\",\"Juliana Jansen Ferreira\"]","published":"2026-06-02T19:19:52Z","proceeding":"cs.AI","tasks":"[\"cs.AI\",\"cs.CY\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}