Ento-Linguistics: Language, Ambiguity, and Scientific Communication in Entomology

Scientific language does not merely describe biological phenomena; it actively constitutes the generative models through which researchers parse complex systems. This paper makes three core contributions to understanding—and correcting—the epistemic consequences of this constitutive role. First, we introduce a six-domain Ento-Linguistic framework that decomposes the terminological landscape of insect research into analytically tractable themes, isolating domains where anthropomorphic language most severely distorts causal modeling. Second, we develop an open-source computational pipeline that integrates automated term extraction, co-occurrence network construction, and information-theoretic ambiguity scoring with principles from Active Inference and Complex Systems Theory. Third, we propose and validate four evidence-based meta-standards—Clarity, Appropriateness, Consistency, and Evolvab