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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 5 of 5 1 Testing a computational model of causative overgeneralizations: Child judgment and production data from English, Hebrew, Hindi, Japanese and K’iche’ Ambridge, Ben; Doherty, Laura; Maitreyee, Ramya. - : F1000 Research Ltd, 2022 BASE Show details 2 Testing a computational model of causative overgeneralizations: Child judgment and production data from English, Hebrew, Hindi, Japanese and K’iche’ Ambridge, Ben; Doherty, Laura; Maitreyee, Ramya. - : F1000 Research Ltd, 2021 BASE Show details 3 The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'() Ambridge, Ben; Maitreyee, Ramya; Tatsumi, Tomoko... In: Cognition (2020) BASE Show details 4 The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche' Bannard, Colin; Tatsumi, Tomoko; Narasimhan, Bhuvana. - : Elsevier BV, 2020 BASE Show details 5 The crosslinguistic acquisition of sentence structure: Computational modeling and grammaticality judgments from adult and child speakers of English, Japanese, Hindi, Hebrew and K'iche'. Mendoza, Margarita Julajuj; Tatsumi, Tomoko; Pye, Clifton; Bannard, Colin; Efrati, Amir; Pixabaj, Sindy Fabiola Can; Narasimhan, Bhuvana; Nair, Rukmini Bhaya; Fukumura, Kumiko; Sharma, Dipti Misra; Pedro, Pedro Mateo; Doherty, Laura; Samanta, Soumitra; Maitreyee, Ramya; Arnon, Inbal; Pelíz, Mario Marroquín; Bekman, Dani; McCauley, Stewart; Zicherman, Shira; Campbell, Seth; Ambridge, Ben; Berman, Ruth. - 2020 Abstract: This preregistered study tested three theoretical proposals for how children form productive yet restricted linguistic generalizations, avoiding errors such as *The clown laughed the man, across three age groups (5-6 years, 9-10 years, adults) and five languages (English, Japanese, Hindi, Hebrew and K'iche'). Participants rated, on a five-point scale, correct and ungrammatical sentences describing events of causation (e.g., *Someone laughed the man; Someone made the man laugh; Someone broke the truck; ?Someone made the truck break). The verb-semantics hypothesis predicts that, for all languages, by-verb differences in acceptability ratings will be predicted by the extent to which the causing and caused event (e.g., amusing and laughing) merge conceptually into a single event (as rated by separate groups of adult participants). The entrenchment and preemption hypotheses predict, for all languages, that by-verb differences in acceptability ratings will be predicted by, respectively, the verb's relative overall frequency, and frequency in nearly-synonymous constructions (e.g., X made Y laugh for *Someone laughed the man). Analysis using mixed effects models revealed that entrenchment/preemption effects (which could not be distinguished due to collinearity) were observed for all age groups and all languages except K'iche', which suffered from a thin corpus and showed only preemption sporadically. All languages showed effects of event-merge semantics, except K'iche' which showed only effects of supplementary semantic predictors. We end by presenting a computational model which successfully simulates this pattern of results in a single discriminative-learning mechanism, achieving by-verb correlations of around r = 0.75 with human judgment data. URL: https://www.sciencedirect.com/science/article/pii/S0010027720301293 http://livrepository.liverpool.ac.uk/3095707/ http://livrepository.liverpool.ac.uk/3095707/1/CLASS1_Cognition.pdf BASE Hide details

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