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</script>This thesis grew out of the project "Exploring probabilistic grammar(s) in varieties of English around the World" and explores the underlying constraints that shape syntactic variation in new varieties of English around the World. More precisely, the research is concerned with the probabilistic constraints that influence the choice between a ditransitive (e.g. "Mary gives John the apple") and a prepositional dative (e.g. "Mary gives the apple to John") and the extent to which these constraints are socially or regionally malleable. Situated thus at the cross-roads of research in Cognitive Sociolinguistics, the probabilistic grammar framework and World Englishes, the study aims to tease apart the extent to which speakers' grammatical knowledge differs across a wide set of different varieties of the same language. Using mixed-effects modeling, conditional random forests, collexeme analysis and multidimensional scaling techniques, the study shows that probabilistic grammars are not as stable as hitherto assumed and that their presumed stability or variability is dependent on the lexical items and the syntactic alternation included in one’s analysis.
Research Foundation Flanders (FWO) grant no. G.0C59.13N
language, language variation and change, dative alternation, linguistics, World Englishes
language, language variation and change, dative alternation, linguistics, World Englishes
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 6 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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