Replication Data for: A multivariate account of particle alternation after bare-form try in native varieties of English

DOI

[Dataset abstract] This is the data and code from a multifactorial study reviewing the determinants of particle alternation after uninflected try in native varieties of English. The effects of a number of previously discussed and novel predictors (see Section 3.1 of the paper) are probed in data from well-known corpora (ICE, GloWbE, BNC and COCA). The paper is published in English Language and Linguistics (https://www.doi.org/10.1017/S1360674321000393). I used R (R Core Team 2021) for all data analyses, hence the code can best be replicated in R.

[Article abstract] This multifactorial study reviews the determinants of particle alternation after uninflected try in varieties where English is native. The effects of a number of previously discussed and novel predictors are probed in data from well-known corpora. The results confirm the inclinations of North American varieties (try to) in contrast with those of the Australasian, British and Irish varieties (try and in speech but try to in writing). The previously reported general effects of the tense of try, mode and horror aequi are also corroborated. As regards the effect of register, the study contributes the finding that following Latin-based infinitives favor try to in most varieties, especially in writing. The paper discusses the status of the substantiated effects with respect to the notions of conventionalization and entrenchment: crucially, the higher degree of conventionalization of try to in North American varieties (a) makes the use of this variant less conditional on the sequential need to license euphony and (b) neutralizes the general contextual/register distinction for the alternation. From a usage-based viewpoint, the findings suggest that the higher frequency of a multiword sequence in a specific variety, and the higher degree of activation in the language users’ minds, can make it less contingent on general probabilistic constraints.

R studio, 1.2.1335

R, 4.0.3

brms: Bayesian Regression Models using 'Stan', 2.16.1

Identifier
DOI https://doi.org/10.18710/GVUZWI
Related Identifier IsCitedBy https://doi.org/10.1017/S1360674321000393
Metadata Access https://dataverse.no/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18710/GVUZWI
Provenance
Creator Tizón-Couto, David ORCID logo
Publisher DataverseNO
Contributor Tizón-Couto, David; University of Vigo; The Tromsø Repository of Language and Linguistics (TROLLing)
Publication Year 2022
Funding Reference Spanish Ministry of Science and Innovation PID2020-118143GA-I00 ; Xunta de Galicia ED431C2021/52
Rights info:eu-repo/semantics/openAccess
OpenAccess true
Contact Tizón-Couto, David (University of Vigo)
Representation
Resource Type annotated corpus data; Dataset
Format text/plain; text/csv; application/pdf; type/x-r-syntax; application/x-rlang-transport
Size 7235; 285553; 128255; 3573467; 141736; 6008642; 219849; 109996; 83995; 166644; 7481; 8352; 698431924; 6858; 11702
Version 1.1
Discipline Humanities