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Conventional metaphors elicit greater real-time engagement than literal paraphrases or concrete sentences
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From partners to populations: A hierarchical Bayesian account of coordination and convention ...
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Accessibility and Historical Change: An Emergent Cluster Led Uncles and Aunts to Become Aunts and Uncles
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In: Front Psychol (2021)
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Generalizing meanings from partners to populations: Hierarchical inference supports convention formation on networks ...
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Investigating representations of verb bias in neural language models ...
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Metaphorical language processing and amygdala activation in L1 and L2
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When regularization gets it wrong: children over-simplify language input only in production
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Abstract:
Children tend to regularize their productions when exposed to artificial languages, an advantageous response to unpredictable variation. But generalizations in natural languages are typically conditioned by factors that children ultimately learn. In two experiments, adult and six-year-old learners witnessed two novel classifiers, probabilistically conditioned by semantics. Whereas adults displayed high accuracy in their productions – applying the semantic criteria to familiar and novel items – children were oblivious to the semantic conditioning. Instead, children regularized their productions, over-relying on only one classifier. However, in a two-alternative forced-choice task, children’s performance revealed greater respect for the system’s complexity: they selected both classifiers equally, without bias toward one or the other, and displayed better accuracy on familiar items. Given that natural languages are conditioned by multiple factors that children successfully learn, we suggest that their tendency to simplify in production stems from retrieval difficulty when a complex system has not yet been fully learned.
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URL: http://www.ncbi.nlm.nih.gov/pubmed/29463337 https://doi.org/10.1017/S0305000918000041 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6076332/
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Neural systems involved in processing novel linguistic constructions and their visual referents
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