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Volume 43, Issue 2
  • ISSN 0176-4225
  • E-ISSN: 1569-9714
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Abstract

Abstract

This article investigates the effectiveness of sigmoid trajectories (S-curves) for statistically modelling language change. In diachronic linguistics, it is customary to fit a sigmoid regression line through data, on the assumption that such a curve fits the ideal language change. A coefficient with an associated p-value significantly different from zero is taken as evidence for the presence of a change. Here, we take the inverse perspective: given a known change, how well can the S-curve predict the actual data? We look at 15 well-known changes in Late Modern Dutch, in a genre-balanced corpus. For each change we built four different models: one model based on all the data and three partly blinded models, where either the beginning, middle or end of the S-curve is omitted. We check how well the S-curve can predict or reconstruct the unknown data, i.e. the blinded parts of the S-curve. We investigate in which cases (the type of change, the part of the data that is omitted, etc.) it is easier or harder to reconstruct the missing data.

© John Benjamins Publishing Company
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2026-03-23
2026-04-19

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Testing the performance of S-curves for language change
Diachronica 43, 189 (2026); https://doi.org/10.1075/dia.23065.nij
/content/journals/10.1075/dia.23065.nij
/content/journals/10.1075/dia.23065.nij
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  • Article Type: Research Article
Keyword(s): diachronic linguistics; drift; Dutch; inflection; logistic regression; S-curves

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