Volume 39, Issue 1
  • ISSN 0929-7332
  • E-ISSN: 1569-9919



So far, processing studies on grammatical norm violations (GNVs) in Dutch (i.e. ‘as’ in comparatives) have mainly focused on general differences between GNVs and their grammatical and ungrammatical counterparts. The present study is the first to also systematically investigate between-participant and between-construction variation in the processing of GNVs, using a self-paced reading task. Age and educational level were investigated as potential sources of between-participant variation, and between-construction variation was assessed by including three GNVs that vary in the amount of prescriptive attention they receive in society. Results indeed showed that the processing of GNVs was influenced by the age and educational level of participants. Moreover, different results were obtained for different norm violations. Based on these results, we conclude that it is very important to take into account differences between participants and constructions when studying the processing of GNVs.

Available under the CC BY 4.0 license.

Article metrics loading...

Loading full text...

Full text loading...



  1. Audring, Jenny
    2009 Reinventing pronoun gender. PhD dissertation, Vrije Universiteit Amsterdam. Utrecht: LOT publications.
    [Google Scholar]
  2. Bates, Douglas, Martin Mächler, Benjamin M. Bolker & Steven C. Walker
    2015 “Fitting Linear Mixed-Effects Models using lme4.” Journal of Statistical Software67 (1): 1–48, 10.18637/jss.v067.i01
    https://doi.org/10.18637/jss.v067.i01 [Google Scholar]
  3. de Hoop, Helen
    2020 “Het verlies van een persoonlijk voornaamwoord*.” Nederlandse Taalkunde25 (2): 355–362, 10.5117/NEDTAA2020.2‑3.018.DEHO
    https://doi.org/10.5117/NEDTAA2020.2-3.018.DEHO [Google Scholar]
  4. Delignette-Muller, Marie Laure & Christophe Dutang
    2015 fitdistrplus: An R Package for Fitting Distributions. Journal of Statistical Software64 (4): 1–34, https://www.jstatsoft.org/article/view/v064i04
    [Google Scholar]
  5. E-ANS
    E-ANS 2021 Algemene Nederlandse Spraakkunst (ANS), versie 3.1 2021, <https://e-ans.ivdnt.org/topics/pid/ans10031405lingtopic
  6. Ferreira, Fernanda & John M. Henderson
    1990 “Use of verb information in syntactic parsing: evidence from eye movements and word-by-word self-paced reading.” Journal of experimental psychology. Learning, memory, and cognition16 (4): 555–568, 10.1037/0278‑7393.16.4.555
    https://doi.org/10.1037/0278-7393.16.4.555 [Google Scholar]
  7. Giner, Göknur & Gordon K. Smyth
    2016 statmod: Probability Calculations for the Inverse Gaussian Distribution. R Journal8 (1): 339–351, (29March 2022). 10.32614/RJ‑2016‑024
    https://doi.org/10.32614/RJ-2016-024 [Google Scholar]
  8. Grondelaers, Stefan, Paul van Gent & Roeland van Hout
    2022 “On the Inevitability of Social Meaning and Ideology in Accounts of Syntactic Change: Evidence from Pronoun Competition in Netherlandic Dutch.” InExplanations in Sociosyntactic Variation, Tanya Karoli Christensen & Torben Juel Jensen. (eds), 120–143, 10.1017/9781108674942.006
    https://doi.org/10.1017/9781108674942.006 [Google Scholar]
  9. Hinskens, F. L. M. P. & H. J. Bennis
    2014 “Goed of fout. Niet-standaard inflectie in het hedendaags Standaardnederlands.” Nederlandse Taalkunde19 (2): 131–184, 10.5117/NEDTAA2014.2.BENN
    https://doi.org/10.5117/NEDTAA2014.2.BENN [Google Scholar]
  10. Hubers, Ferdy & Helen de Hoop
    2013 “The effect of prescriptivism on comparative markers in spoken Dutch.” Linguistics in the Netherlands301: 89–101, 10.1075/avt.30.07hub
    https://doi.org/10.1075/avt.30.07hub [Google Scholar]
  11. Hubers, Ferdy, Theresa Redl, Hugo de Vos, Lukas Reinarz & Helen de Hoop
    2020b “Processing Prescriptively Incorrect Comparative Particles: Evidence From Sentence-Matching and Eye-Tracking.” Frontiers in Psychology111, 10.3389/fpsyg.2020.00186
    https://doi.org/10.3389/fpsyg.2020.00186 [Google Scholar]
  12. Hubers, Ferdy, T. M. Snijders & H. de Hoop
    2016 “How the brain processes violations of the grammatical norm: An fMRI study.” Brain and Language1631, 10.1016/j.bandl.2016.08.006
    https://doi.org/10.1016/j.bandl.2016.08.006 [Google Scholar]
  13. Hubers, Ferdy, Thijs Trompenaars, Sebastian Collin, Kees de Schepper & Helen de Hoop
    2020a “Hypercorrection as a by-product of education.” Applied Linguistics41 (4): 552–574, 10.1093/applin/amz001
    https://doi.org/10.1093/applin/amz001 [Google Scholar]
  14. Just, M. A., P. A. Carpenter & J. D. Woolley
    1982 “Paradigms and processes in reading comprehension.” Journal of experimental psychology. General111 (2): 228–238, www.ncbi.nlm.nih.gov/pubmed/6213735 10.1037/0096‑3445.111.2.228
    https://doi.org/10.1037/0096-3445.111.2.228 [Google Scholar]
  15. Kuznetsova, Alexandra, Per B. Brockhoff & Rune H. B. Christensen
    2017 lmerTest Package: Tests in Linear Mixed Effects Models. Journal of Statistical Software82 (13), 10.18637/jss.v082.i13
    https://doi.org/10.18637/jss.v082.i13 [Google Scholar]
  16. Lenth, Russell v.
    2021 emmeans: Estimated Marginal Means, aka Least-Squares Means.
    [Google Scholar]
  17. Lo, Steson & Sally Andrews
    2015 “To transform or not to transform: using generalized linear mixed models to analyse reaction time data.” Frontiers in Psychology61: 1171, 10.3389/fpsyg.2015.01171
    https://doi.org/10.3389/fpsyg.2015.01171 [Google Scholar]
  18. R Development Core Team
    R Development Core Team 2008 R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing, https://www.r-project.org/
  19. Schoenmakers, Gert-Jan T.
    (accepted). “Linguistic judgments in 3D: The aesthetic quality, linguistic acceptability, and surface probability of stigmatized and non-stigmatized variation.” Linguistics.
    [Google Scholar]
  20. van Casteren, Maaarten & Matthew H. Davis
    2006 “Mix, a program for pseudorandomization.” Behavior Research Methods38 (4): 584–589, 10.3758/BF03193889
    https://doi.org/10.3758/BF03193889 [Google Scholar]

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error