Article published In: Linguistics in the Netherlands 2025
Edited by Kristel Doreleijers, Remco Knooihuizen and Eva van Lier
[Nota Bene 2:2] 2025
► pp. 389–412
Un bietje lope schume in de Onderstad
A Bayesian multivariate regression analysis of variation in Nimwèègs
Available under the Creative Commons Attribution (CC BY) 4.0 license.
For any use beyond this license, please contact the publisher at rights@benjamins.nl.
Open Access publication of this article was funded through a Transformative Agreement with Radboud University Nijmegen.
Published online: 31 October 2025
https://doi.org/10.1075/nb.00040.sch
https://doi.org/10.1075/nb.00040.sch
Abstract
Nimwèègs, a variety of Cleverlandish spoken in Nijmegen, has been subject to extensive sociolinguistic inquiry.
Today, most remaining speakers reside in the so-called Onderstad and are active in the building of a new
linguistic identity with the organization of cultural events, alongside the promotion of the local football team (N.E.C.). In this
study, we focus on the social motivations behind the use of Nimwèègs in this community. We conducted linguistic fieldwork and
collected Frog Story narrations with 14 participants using the MPI Fieldkit. We identified 24 variables, based on previous studies
(Berns, Jan. 2002. Zuid-Gelderse
dialecten. Den Haag: Sdu Uitgevers.; Hout, Roeland van. 1989. De structuur van taalvariatie: Een
sociolinguïstisch onderzoek naar het stadsdialect van
Nijmegen. Dordrecht: Foris Publications.; Hout, Roeland van, Jan Roelofs & Leo van Stijn. 2006. Kie(k)
däör, wà räör: Woordenboek van het Nimweegs
dialect. Nijmegen: Dekker v.d. Vegt.). We then ran a Bayesian multivariate regression
model based on only 13 of these variables, to assess the interaction between these and social variables. These models indicated
that certain Nimwèègs features were used more frequently if speakers were members of the Nimwèègs Movement, potential interactions
between gender and language use were also found.
Article outline
- 1.Introduction
- 2.Nimwèègs within Cleverlandish
- 3.Methods
- 3.1Multivariate Bayesian regression models
- 4.Results
- 4.1Interactions
- 5.Discussion
- 5.1Interactions
- 6.Final remarks
- Acknowledgements
- Notes
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