2011
DOI: 10.1353/lan.2011.0012
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Learning What NOT to Say: The Role of Statistical Preemption and Categorization in A -Adjective Production

Abstract: A persistent mystery in language acquisition is how speakers are able to learn seemingly arbitrary distributional restrictions. This article investigates one such case: the fact that speakers resist using certain adjectives prenominally (e.g. ?? the asleep man ). Experiment 1 indicates that speakers tentatively generalize or categorize the distributional restriction beyond their previous experience. Experiment 2 demonstrates that speakers are sensitive to statistical preemption —that is, speakers learn not to … Show more

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Cited by 147 publications
(120 citation statements)
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References 48 publications
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“…For example, in language production, the frequencies with which verbs appear in alternative syntactic contexts has consequences for sentence production choices of sentences containing those verbs (Arnold, Wasow, Asudeh & Alrenga, 2004;Bernolet & Hartsuiker, 2010;Stallings et al, 1998) as do the distributional pairings between noun animacy and sentence structure (Bresnan & Ford, 2010;Reali & Christiansen, 2007;Gennari & MacDonald, 2009). Like comprehenders, language producers implicitly learn statistical patterns of their linguistic environment, and this information affects production choices and accuracy (Boyd & Goldberg, 2011;Chang, 2009;Dell, Reed, Adams & Meyer, 2000;Warker & Dell, 2006). Language users also have learned the statistics of their visual environment, with consequences for codability in picture description tasks, where, for example, recognition of a ball is influenced by recognition of a throwing action and vice versa (Almor et al, 2009;Handy et al, 2003;Knoeferle & Crocker, 2006;Palmer, 1975).…”
Section: Multiple Forces Shaping Production Choicesmentioning
confidence: 99%
“…For example, in language production, the frequencies with which verbs appear in alternative syntactic contexts has consequences for sentence production choices of sentences containing those verbs (Arnold, Wasow, Asudeh & Alrenga, 2004;Bernolet & Hartsuiker, 2010;Stallings et al, 1998) as do the distributional pairings between noun animacy and sentence structure (Bresnan & Ford, 2010;Reali & Christiansen, 2007;Gennari & MacDonald, 2009). Like comprehenders, language producers implicitly learn statistical patterns of their linguistic environment, and this information affects production choices and accuracy (Boyd & Goldberg, 2011;Chang, 2009;Dell, Reed, Adams & Meyer, 2000;Warker & Dell, 2006). Language users also have learned the statistics of their visual environment, with consequences for codability in picture description tasks, where, for example, recognition of a ball is influenced by recognition of a throwing action and vice versa (Almor et al, 2009;Handy et al, 2003;Knoeferle & Crocker, 2006;Palmer, 1975).…”
Section: Multiple Forces Shaping Production Choicesmentioning
confidence: 99%
“…Conditional inference trees are particularly useful for analyzing data that are expected to yield complex interactions. The method works by successively partitioning the data into maximally homogenous subsets, using the factor structure specified by the user (see Boyd & Goldberg 2011 for an example). Thus, for the present data set, the analysis creates groups of sentences that received similar acceptability ratings by partitioning the data on the basis of verb type (PO-only, DO-only, alternating) and sentence type (PO, DO) (the inclusion of semantic verb class, nested within verb type, was not supported by either this analysis or the subsequent regression analysis).…”
Section: Experiments 1: Semantic Verb Class (And Entrenchment) Hypothementioning
confidence: 99%
“…81 Further research-for example on the transitive-causative construction-is needed to clarify whether the effect of pre-emption genuinely differs across constructions, or whether this pattern is due to methodological differences between the two studies (e.g., the different numbers of verbs used). In addition to the un-prefixation judgment study discussed above, 20 a further production study 74 found evidence for pre-emption in the domain of aadjectives (e.g., *the asleep boy is pre-empted by the boy who is asleep). This study avoided the methodological problems associated with the transitivecausative studies discussed above 78,79 by testing generalization to novel items, though it was conducted on adults, and has not yet been extended to children.…”
Section: Pre-emptionmentioning
confidence: 90%
“…80,94,120 Relatedly, the findings of one recent study suggest that the adjective slot in the adjectival construction (ADJECTIVE) (NP) exhibits properties that could be described as morphophonological (or perhaps etymological) and rejects incompatible adjectives. The restriction is that the filler of the adjective slot must not be segmentable into a-plus a related stem (e.g., the scared/astute/*alive/*afraid man) and, again, adult learners respect this restriction even with novel adjectives 74 (though pre-emption also seems to be at work here).…”
Section: Slots With Complex Propertiesmentioning
confidence: 94%
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