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Glossa: A Journal of General Linguistics

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Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.


A challenge for grammatical theories and models of language processing alike is to explain conflicting online and offline judgments about the acceptability of sentences. A prominent example of the online/offline mismatch involves “agreement attraction” in sentences like *The key to the cabinets were rusty, which are often erroneously treated as acceptable in time-restricted “online” measures, but judged as less acceptable in untimed “offline” tasks. The prevailing assumption is that online/offline mismatches are the product of two linguistic analyzers: one analyzer for rapid communication (the “parser”) and another, slower analyzer that classifies grammaticality (the “grammar”). A competing hypothesis states that online/offline mismatches reflect a single linguistic analyzer implemented in a noisy memory architecture that creates the opportunity for errors and conflicting judgments at different points in time. A challenge for the single-analyzer account is to explain why online and offline tasks sometimes yield conflicting responses if they are mediated by the same analyzer. The current study addresses this challenge by showing how agreement attraction effects might come and go over time in a single-analyzer architecture. Experiments 1 and 2 use an agreement attraction paradigm to directly compare online and offline judgments, and confirm that the online/offline contrast reflects the time restriction in online tasks. Experiment 3 then uses computational modeling to capture the mapping from online to offline responses as a process of sequential memory sampling in a single-analyzer framework. This demonstration provides some proof-of-concept for the single-analyzer account and offers an explicit process model for the mapping between online and offline responses.


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