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Journal article

Variation isn’t that hard: Morphosyntactic choice does not predict production difficulty

Abstract:
There is ample psycholinguistic evidence that speakers behave efficiently, using shorter and less effortful constructions when the meaning is more predictable, and longer and more effortful ones when it is less predictable. However, the Principle of No Synonymy requires that all formally distinct variants should also be functionally different. The question is how much two related constructions should overlap semantically and pragmatically in order to be used for the purposes of efficient communication. The case study focuses on want to + Infinitive and its reduced variant with wanna, which have different stylistic and sociolinguistic connotations. Bayesian mixed-effects regression modelling based on the spoken part of the British National Corpus reveals a very limited effect of efficiency: predictability increases the chances of the reduced variant only in fast speech. We conclude that efficient use of more and less effortful variants is restricted when two variants are associated with different registers or styles. This paper also pursues a methodological goal regarding missing values in speech corpora. We impute missing data based on the existing values. A comparison of regression models with and without imputed values reveals similar tendencies. This means that imputation is useful for dealing with missing values in corpora
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.pone.0252602

Authors

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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-1878-4232
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Role:
Author
ORCID:
0000-0001-8844-6602


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Funder identifier:
10.13039/501100003130
Grant:
G.0C59.13N


Publisher:
Public Library of Science
Journal:
PLoS ONE More from this journal
Volume:
16
Issue:
6
Pages:
e0252602-e0252602
Publication date:
2021-06-21
DOI:
EISSN:
1932-6203
ISSN:
1932-6203


Language:
English
Keywords:
Pubs id:
1607280
Local pid:
pubs:1607280
Source identifiers:
W3177371562
Deposit date:
2026-06-05
ARK identifier:
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