The synchronic status of historical bound roots in the mental lexicon: A dynamic, psychocentric perspective
Many English words contain historical roots that do not occur as free morphemes (e.g., nov in innovate, dict in verdict). These words often retain an appearance of compositionality and are associated with effects on lexical processing (Pastizzo & Feldman, 2004; Taft & Forster, 1975), but frequently their roots are difficult to identify without recourse to historical etymologies, and they are semantically opaque and unproductive. More practically, although such words are prominent in academic vocabulary, they are often difficult to learn, and instruction inspired by their apparent morphological structure has yielded mixed results (McKeown et al., 2018). We explore these psycholinguistic and educational challenges through a dynamic view of the mental lexicon (Libben, 2022), understanding morphological resources as gradient, emergent, and contextually adaptable for meaning making. We quantified bound roots’ morphological families by training an unsupervised parser on a lexicon approximating that of an educated English user, and then assessing polysemy and coherence of roots’ meanings, using vector semantic representations. Testing against behavioral data supported the validity of these measures, suggesting new ways of measuring the properties of bound roots independent from etymological data and demonstrating sensitivity even to unproductive morphological structure, that can support academic vocabulary development and meaning-making.
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Work Title The synchronic status of historical bound roots in the mental lexicon: A dynamic, psychocentric perspective Access Creators - Matthew T. Carlson
- Amy Crosson
Keyword - bound roots
- academic vocabulary
- unsupervised parsing
- lexical semantics
License In Copyright (Rights Reserved) Work Type Article Publisher - The Mental Lexicon
Publication Date February 6, 2025 Publisher Identifier (DOI) - https://doi.org/10.1075/ml.24032.car
Deposited August 17, 2026 Versions
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- bound roots, academic vocabulary, unsupervised parsing, lexical semantics
