Elamur Research⌕
☰
home / papers / 2025 / The English conative alternation between complexity effects and lexical biases: a historical perspective

The English conative alternation between complexity effects and lexical biases: a historical perspective

Paper · 2025 · Eva Zehentner

Summary

The paper asks why speakers of earlier English chose between a direct-object pattern (kick the ball) and a prepositional at-pattern (kick at the ball), the so-called conative alternation. Two explanations are weighed. The first is processing complexity: the more explicit PP should appear when parsing is harder, for example with long verb–object distance, ambiguity or rare verbs. The second is lexical bias: individual verbs prefer one variant. The data are clauses drawn from the Penn-Helsinki parsed corpora (PPCME2, PPCEME, PPCMBE2), covering roughly 1150–1914. The author analyses them with three methods: collostructional analysis, mixed-effects logistic regression, and elastic net regression, the last following Sevenants et al. (2024). Elastic net can put verb identities and high-level predictors into one model. Verb preferences turn out to dominate throughout the period, and the PP variant seems to spread to more verbs and meanings over time. Distance and verb frequency do show complexity effects, but ambiguity works against expectations. The study suggests this alternation is more lexically driven than the dative alternation. It also shows that the choice of method can change the conclusions.

Key points

  • The corpora are PPCME2, PPCEME and PPCMBE2, spanning Middle English to Late Modern English (1150–1914). Data and code are shared on OSF.
  • Three methods are compared: collostructional analysis, mixed-effects logistic regression and elastic net regression. Their results largely overlap.
  • The logistic regression found animacy/definiteness effects that would have supported a hypothesis. These effects vanished once lexical effects were modelled jointly in the elastic net.
  • Complexity effects survive for distance and verb frequency. Ambiguity pushes in the opposite direction from the prediction.
  • Several limitations are acknowledged:
    • No frequency threshold was applied, although rare verbs such as lash and muse still show up.
    • Ditransitives were included.
    • The verb set was broad, taking in admire and rejoice.
    • Only at was counted as the preposition.
    • Manual interchangeability judgements are partly subjective.

Interesting ideas

  • I1. Put lexical identity and structural predictors into a single regularised model, rather than fitting lexical items as random effects. This keeps structural effects from absorbing variance that really belongs to particular words.
  • I2. Treat agreement between methods as a robustness check, and report the points where they diverge. In this study, an effect that appeared under one method disappeared under another and changed the conclusions.
  • I3. The complexity principle says a more explicit marker is preferred when processing is harder, such as long dependencies or rare words. This gives a testable link between surface form and processing load.
  • I4. The conative contrast is meaningful. The at-variant marks attempted, possibly unsuccessful, repeated or less affecting action, while the direct object implies contact and completion.
  • I5. Verb biases toward a construction change over time, and the PP pattern expanded lexically. Construction preferences should therefore be stored per verb and not as global rules.

For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

  • I1 (learn): When evaluating which features drive parser or frame errors, fit lemma identity alongside length and distance features in one elastic-net model. Structural "causes" that disappear in that model are probably verb quirks.
  • I2 (learn): Run each diagnostic analysis with two or three methods and flag any finding supported by only one as a candidate artefact. This works as a kind of negative control.
  • I3 (tree): Add verb–object distance and verb frequency as features or diagnostics for the attachment of at-PPs. This could help decide when an at-phrase is an argument rather than an adjunct.
  • I4 (frames): When the parse shows a VerbNet impact or cutting verb with an at-oblique, assign the theme a weak-affectedness role and mark success as unknown, not achieved.
  • I5 (world): Record per-verb conative licensing and its entailments (contact, change of state, completion) in the verb-class knowledge. The world model can then avoid asserting that cut at the rope severed the rope.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓University of ZurichZurich · Switzerland78 works · 12,260 citations

 Fields, topics and concepts

📚 Shelves 2The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 works

🧭 Topics 1Research subjects and languages the work is about.English · 2,263 works

Cite

Cite as Eva Zehentner. 2025. The English conative alternation between complexity effects and lexical biases: a historical perspective. Language and Cognition 17.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.1017/langcog.2025.10007

@inproceedings{zehentner2025english,
  title = {{The English conative alternation between complexity effects and lexical biases: a historical perspective}},
  author = {Eva Zehentner},
  booktitle = {Language and Cognition 17},
  year = {2025},
  doi = {10.1017/langcog.2025.10007},
  url = {https://doi.org/10.1017/langcog.2025.10007}
}

References

97 references, 3 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

  1. Aissen, J. (2003). Differential object marking: Iconicity vs. economy. Natural Language & Linguistic Theory, 21(3), 435–483. https://doi.org/10.1023/a:1024109008573. ↗
  2. Allen, C. (1995). Case marking and reanalysis: Grammatical relations from old to early modern English. OUP. find
  3. Archer, D., Kytö, M., Baron, A., & Rayson, P. (2015). Guidelines for normalising early modern English corpora: Decisions and justifications. ICAME Journal, 39(1), 5–24. ↗
  4. Baron, A., & Rayson, P. (2008). VARD2: A tool for dealing with spelling variation in historical corpora. Postgraduate Conference in Corpus Linguistics, 2008-05-22, Birmingham, UK: Aston University. http://ucrel.lancs.ac.uk/people/paul/publications/BaronRaysonAston2008.pdf. ↗
  5. Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01. ↗
  6. Baugh, A., & Cable, T. (2002). A history of the English language (5th ed.). Taylor & Francis. https://doi.org/ 10.4324/9780203994634. ↗
  7. Beavers, J. (2010). The structure of lexical meaning. Language, 86(4), 821–864. https://doi.org/10.1353/ lan.2010.0040. ↗
  8. Beavers, J. (2011). On affectedness. Natural Language & Linguistic Theory, 29(2), 335–370. https://doi.org/ 10.1007/s11049-011-9124-6. ↗
  9. Bloem, J. (2021). Processing verb clusters. LOT. https://doi.org/10.48273/LOT0586. ↗
  10. Bloem, J., Versloot, A., & Weerman, F. (2017). Verbal cluster order and processing complexity. Language Sciences, 60, 94–119. https://doi.org/10.1016/j.langsci.2016.10.009. ↗
  11. Bosworth, J., & Toller, T. N. (Eds.) (2014). An Anglo–Saxon dictionary online. Edited and maintained by C. Sean & O. Tichy. Faculty of Arts, Charles University. https://bosworthtoller.com/. ↗
  12. Breheny, P., & Burchett, W. (2017). Visualization of regression models using visreg. The R Journal, 9, 56–71. ↗
  13. Bresnan, J., Cueni, A., Nikitina, T. & Baayen, H. (2007). Predicting the dative alternation. In G. Bouma, I. Kraemer & J. Zwarts (Eds.), Cognitive foundations of interpretation (pp. 69–94). Royal Netherlands Academy of Science. https://web.stanford.edu/~bresnan/qs-submit.pdf. ↗
  14. Broccias, C. (2001). Allative and ablative at-constructions. In M. Andronis, C. Ball, H. Elston, & S. Neuvel (Eds.), CLS 37: The main session. Volume 1 (pp. 67–82). Chicago Linguistic Society. find
  15. Broccias, C. (2003). The English change network: Forcing changes into categories. De Gruyter Mouton. https://doi.org/10.1515/9783110901207. ↗
  16. Bybee, J. (2007). Frequency of use and the organization of language. OUP. https://doi.org/10.1093/acprof: oso/9780195301571.001.0001. ↗
  17. Bybee, J., & Hopper, P. (2001). Frequency and the emergence of linguistic structure. Benjamins. https://doi.org/10.1075/tsl.45. ↗
  18. Colleman, T., & De Clerck, B. (2011). Constructional semantics on the move: On semantic specialization in the English double object construction. Cognitive Linguistics, 22(1), 183-209. https://doi.org/10.1515/ cogl.2011.008 De Smet, H., D’hoedt, F., Fonteyn, L., & Goethem, K. (2018). The changing functions of competing forms: Attraction and differentiation. Cognitive Linguistics, 29(2), 197–234. https://doi.org/10.1515/cog-2016-0025. ↗
  19. Divjak, D. (2019). Frequency in language: Context, memory and attention. CUP. https://doi.org/10.1017/ 9781316084410. ↗
  20. Dixon, R. M. W. (1991). A new approach to English grammar, on semantic principles. OUP. ↗
  21. Esteban-Segura, L., & Salles-Bernal, S. (2017). A diachronic study of the conative alternation construction in English. Unpublished conference abstract. http://hdl.handle.net/10630/13794. ↗
  22. Fedzechkina, M., Jaeger, T. F., & Newport, E. L. (2012). Language learners restructure their input to facilitate efficient communication. Proceedings of the National Academy of Sciences of the United States of America, 109(44), 17897–17902. https://doi.org/10.1073/pnas.1215776109. ↗
  23. Fedzechkina, M., Newport, E. L., & Jaeger, T. F. (2017). Balancing effort and information transmission during language acquisition. Cognitive Science, 41(2), 416–446. https://doi.org/10.1111/cogs.12346. ↗
  24. Fedzechkina, M., & Jaeger, T. F. (2020). Production efficiency can cause grammatical change. Cognition, 196(104115), 104115. https://doi.org/10.1016/j.cognition.2019.104115. ↗
  25. Fennell, B. A. (2001). A history of English: A sociolinguistic approach. Blackwell. find
  26. Flach, S. (2021). Collostructions: An R implementation for the family of collostructional methods. version v.0.2.0, https://sfla.ch/collostructions/. ↗
  27. Friedman, J., Tibshirani, R., & Hastie, T. (2010). Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software, 33(1), 1–22. https://doi.org/10.18637/jss.v033.i01. ↗
  28. Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/hierarchical models. CUP. ↗
  29. Gibson, E. (1998). Linguistic complexity: Locality of syntactic dependencies. Cognition, 68(1), 1–76. https://doi.org/10.1016/S0010-0277(98)00034-1. ↗
  30. Goldberg, A. (1995). Constructions: A construction grammar approach to argument structure. University of Chicago Press. find
  31. Grafmiller, J. (2019). jasongraf1/JGmermod: Custom functions for mixed-effects regression models. R package. https://rdrr.io/github/jasongraf1/JGmermod/. ↗
  32. Gries, S. T. (2019). 15 years of collostructions. International Journal of Corpus Linguistics, 24(3), 385–412. https://doi.org/10.1075/ijcl.00011.gri. ↗
  33. Gries, S. T., & Stefanowitsch, A. (2004). Extending collostructional analysis. International Journal of Corpus Linguistics, 9(1), 97–129. https://doi.org/10.1075/ijcl.9.1.06gri. ↗
  34. Guerrero-Medina, P. (2011). An antipassive interpretation of the English “conative alternation”. In P. Guerrero-Medina (Ed.), Morphosyntactic alternations in English (pp. 182–203). Equinox. find
  35. Guerrero-Medina, P. (2017). The English conative as a family of constructions. In F. J. R. de Mendoza Ibáñez, A. L. Oyón, & P. Pérez-Sobrino (Eds.), Constructing families of constructions (pp. 277–299). Benjamins. https://doi.org/10.1075/hcp.58.10gue. ↗
  36. Haspelmath, M. (2019). Differential place marking and differential object marking. Language Typology and Universals, 72(3), 313–334. https://doi.org/10.1515/stuf-2019-0013. ↗
  37. Haspelmath, M. (2021a). Explaining grammatical coding asymmetries. Journal of Linguistics, 57(3), 605–633. https://doi.org/10.1017/s0022226720000535. ↗
  38. Haspelmath, M. (2021b). Role-reference associations and the explanation of argument coding splits. Linguistics, 59(1), 123–174. https://doi.org/10.1515/ling-2020-0252. ↗
  39. Heller, B., Szmrecsanyi, B., & Grafmiller, J. (2017). Stability and fluidity in syntactic variation world-wide. Journal of English Linguistics, 45(1), 3–27. https://doi.org/10.1177/0075424216685405. ↗
  40. Hoop, H., & de Swart, P. (2008). Differential subject marking. Springer. https://doi.org/10.1007/978-1-4020-6497-5. ↗
  41. Huddleston, R. D., & Pullum, G. K. (2002). The Cambridge grammar of the English language. CUP. https://doi.org/10.1017/9781316423530. ↗
  42. Iemmolo, G. (2010). Topicality and differential object marking. Studies in Language, 34(2), 239–272. https://doi.org/10.1075/sl.34.2.01iem. ↗
  43. Iemmolo, G. (2013). Symmetric and asymmetric alternations in direct object encoding. Language Typology and Universals, 66(4), 378–403. https://doi.org/10.1524/stuf.2013.0019. ↗
  44. Klavan, J., & Schützler, O. (2023). The complexity principle and the morphosyntactic alternation between case affixes and postpositions in Estonian. Cognitive Linguistics, 34(2), 297–331. https://doi.org/10.1515/ cog-2021-0114. ↗
  45. Kroch, A., Santorini, B. & Delfs, L. (2004). The Penn-Helsinki Parsed Corpus of Early Modern English. Department of Linguistics, University of Pennsylvania, first edition, release 3. http://www.ling.upenn.edu/ ppche/ppche-release-2016/PPCEME-RELEASE-3. ↗
  46. Kroch, A., Santorini, B., & Diertani, A. (2016). The Penn Parsed Corpus of Modern British English. Department of Linguistics, University of Pennsylvania, second edition, release 1. http://www.ling.upenn.edu/ppche/ppche-release-2016/PPCMBE2-RELEASE-1. ↗
  47. Kroch, A., Taylor, A. & Santorini, B. (2000). The Penn-Helsinki Parsed Corpus of Middle English. Department of Linguistics, University of Pennsylvania, second edition, release 4. http://www.ling.upenn.edu/ppche/ppche-release-2016/PPCME2-RELEASE-4. ↗
  48. Lee, K. (2003). The conative construction in English. Discourse and Cognition, 10(3), 165–186. find
  49. Levin, B. (1993). English verb classes and alternations: A preliminary investigation. Chicago UP. find
  50. Levshina, N. (2015). How to do linguistics with R. Benjamins. https://doi.org/10.1075/z.195. ↗
  51. Levshina, N. (2018). Anybody (at) home? Communicative efficiency knocking on the construction grammar door. Yearbook of the German Cognitive Linguistics Association, 6(1), 71–90. https://doi.org/10.1515/gcla-2018-0004. ↗
  52. Levshina, N. (2021a). Communicative efficiency and differential case marking. Linguistics Vanguard: Multimodal Online Journal, 7(Suppl 3), 20190087. https://doi.org/10.1515/lingvan-2019-0087. ↗
  53. Levshina, N. (2021b). Cross-linguistic trade-offs and causal relationships between cues to grammatical subject and object, and the problem of efficiency-related explanations. Frontiers in Psychology, 12, 648200. https://doi.org/10.3389/fpsyg.2021.648200. ↗
  54. Levshina, N. (2022). Communicative efficiency. CUP. https://doi.org/10.1017/9781108887809. ↗
  55. Linzen, T., & Jaeger, F. (2014). Investigating the role of entropy in sentence processing. In Proceedings of the fifth workshop on cognitive Modeling and computational linguistics (pp. 10–18). Association for Computational Linguistics. find
  56. McFadden, T. (2002). The rise of the todative in middle English. In D. Lightfoot (Ed.), Syntactic effects of morphological change (pp. 107–123). OUP. https://doi.org/10.1093/acprof:oso/9780199250691.003.0006. ↗
  57. Mondorf, B. (2009). More support for more-support. Benjamins. https://doi.org/10.1075/silv.4. ↗
  58. Percillier, M. (2016). Verb lemmatization and semantic verb classes in a Middle English corpus. In Proceedings of the 13th Conference on Natural Language Processing (KONVENS 2016) (pp. 209–214). Ruhr-Universität Bochum. https://www.linguistics.rub.de/konvens16/pub/26_konvensproc.pdf. ↗
  59. Percillier, M. (2018). A toolkit for lemmatising, analysing, and visualising middle English data. In A. Frank, C. Ivanovic, F. Mambrini, M. Passarotti, & C. Sporleder (Eds.), Proceedings of the second workshop on corpus-based research in the humanities (pp. 153–160). Dept. of Geoinformation, TU Wien. https://www.oeaw.ac.at/fileadmin/subsites/academiaecorpora/PDF/CRH2.pdf. ↗
  60. Perek, F. (2014). Rethinking constructional polysemy. In D. Glynn & J. Robinson (Eds.), Human cognitive processing (pp. 61–85). Benjamins. https://doi.org/10.1075/hcp.43.03per. ↗
  61. Perek, F. (2015). Argument structure in usage-based construction grammar. Benjamins. https://doi.org/ 10.1075/cal.17. ↗
  62. Perek, F. & Lemmens, M. (2010). Getting at the meaning of the English at-construction. CogniTextes, 5, 1–28. http://cognitextes.revues.org/331. ↗
  63. Pijpops, D. (2020). What is an alternation? Belgian Journal of Linguistics, 34, 283–294. https://doi.org/ 10.1075/bjl.00053.pij. ↗
  64. Pijpops, D., Speelman, D., Grondelaers, S., & Van de Velde, F. (2018). Comparing explanations for the complexity principle. Language and Cognition, 10(3), 514–543. https://doi.org/10.1017/langcog.2018.13. ↗
  65. Pijpops, D., Speelman, D., Grondelaers, S., & Van de Velde, F. (2021). Incorporating the multi-level nature of the constructicon into hypothesis testing. Cognitive Linguistics, 32(3), 487–528. https://doi.org/10.1515/ cog-2020-0039. ↗
  66. Pijpops, D., Speelman, D., & van den Bosch, A. (2022). Generating hypotheses for alternations at low and intermediate levels of categoryticity: The use of memory-based learning. Linguistics Vanguard, 8(1), 305–319. https://doi.org/10.1515/lingvan-2021-0081. ↗
  67. Pinker, S. (1989). Learnability and cognition: The acquisition of argument structure. MIT Press. find
  68. R Core Team (2024). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. www.R-project.org/. find
  69. Riemer, N. (2012). Introducing semantics. CUP. https://doi.org/10.1017/cbo9780511808883. ↗
  70. Rinker, T. (2022). textstem: Tools for stemming and lemmatizing text, Version 0.1. 4. http://github.com/ trinker/textstem. ↗
  71. Rohdenburg, G. (1996). Cognitive complexity and increased grammatical explicitness in English. Cognitive Linguistics, 7(2), 149–182. https://doi.org/10.1515/cogl.1996.7.2.149. ↗
  72. Rohdenburg, G. (2002). Processing complexity and the variable use of prepositions in English. In H. Cuyckens & G. Radden (Eds.), Perspectives on prepositions (pp. 79–100). De Gruyter Mouton. https://doi.org/10.1515/9783110924787.79. ↗
  73. Rohdenburg, G. (2020). The complexity principle at work with rival prepositions. English Language and Linguistics, 24(4), 769–800. https://doi.org/10.1017/s1360674319000327. ↗
  74. Röthlisberger, M., Grafmiller, J., & Szmrecsanyi, B. (2017). Cognitive indigenization effects in the English dative alternation. Cognitive Linguistics, 28(4), 673–710. https://doi.org/10.5167/uzh-170210. ↗
  75. Röthlisberger, M. (2021). Between context and community: Regional variation in register effects in the English dative alternation. In E. Seoane & D. Biber (Eds.), Corpus-based approaches to register variation (pp. 111–142). Benjamins. https://doi.org/10.1075/scl.103.05rot. ↗
  76. Sato, K. (2009). The development from case-forms to prepositional constructions in old English prose. Peter Lang. find
  77. Schmid, H.-J. (2020). The dynamics of the linguistic system: Usage, conventionalization, and entrenchment. OUP. https://doi.org/10.1093/oso/9780198814771.001.0001. ↗
  78. Schmid, H.-J., & Küchenhoff, H. (2013). Collostructional analysis and other ways of measuring lexicogrammatical attraction. Cognitive Linguistics, 24(3), 531–577. https://doi.org/10.1515/cog-2013-0018. ↗
  79. Sevenants, A. (2023). ElasticToolsR. Version 1.3. Leuven. https://github.com/AntheSevenants/ElasticToolsR/ tree/v1.3. ↗
  80. Sevenants, A., Van de Velde, F., & Speelman, D. (2024). Investigating lexical-semantic effects on morphosyntactic variation using elastic net regression. Corpus Linguistics and Linguistic Theory, 1–43. https://doi.org/10.1515/cllt-2024-0068. ↗
  81. Sosa-Acevedo, E. (2009). Lexical classes and the conative construction in old English. Studia Anglica Posnaniensia, 45(1), 69–90. https://doi.org/10.2478/v10121-009-0005-6. ↗
  82. Stefanowitsch, A., & Gries, S. T. (2003). Collostructions: Investigating the interaction of words and constructions. International Journal of Corpus Linguistics, 8(2), 209–243. https://doi.org/10.1075/ijcl. 8.2.03ste. ↗
  83. Stefanowitsch, A. (2013). Collostructional analysis. In T. Hoffmann & G. Trousdale (Eds.), The Oxford handbook of construction grammar (pp. 290–306). OUP. https://doi.org/10.1093/oxfordhb/9780195396683. 013.0016. ↗
  84. Stefanowitsch, A., & Flach, S. (2020). Too big to fail but big enough to pay for their mistakes. In G. C. Pastor & J.-P. Colson (Eds.), Computational phraseology (pp. 248–272). Benjamins. https://doi.org/10.1075/ivitra. 24.13ste. ↗
  85. Szmrecsanyi, B. (2012). Analyticity and syntheticity in the history of English. In T. Nevalainen & E. Traugott (Eds.), The Oxford handbook of the history of English (pp. 654–665). OUP. https://doi.org/10.1093/ oxfordhb/9780199922765.013.0056. ↗
  86. Tal, S., Smith, K., Culbertson, J., Grossman, E., & Arnon, I. (2022). The impact of information structure on the emergence of differential object marking. Cognitive Science, 46(3), e13119. https://doi.org/10.1111/cogs. 13119. ↗
  87. Tizón-Couto, D., & Lorenz, D. (2021). Variables are valuable: Making a case for deductive modeling. Linguistics, 59(5), 1279–1309. https://doi.org/10.1515/ling-2019-0050. ↗
  88. Traugott, E. C., & Trousdale, G. (2013). Constructionalization and constructional changes. Oxford: OUP. ↗
  89. Trips, C., & Percillier, M. (2020). Lemmatising verbs in middle English corpora: The benefit of enriching the Penn-Helsinki parsed corpus of middle English 2 (PPCME2), the parsed corpus of middle English poetry (PCMEP), and a parsed linguistic atlas of early middle English (PLAEME). In Proceedings of the twelfth language resources and evaluation conference (pp. 7170–7178). European Language Resources Association. https://aclanthology.org/2020.lrec-1.886. University of Michigan Regents. (2013). The electronic Middle English dictionary. http://quod.lib.umich. edu/m/med/. ↗
  90. Van de Velde, F., & Pijpops, D. (2021). Investigating lexical effects in syntax with regularized regression (lasso). Journal of Research Design and Statistics in Linguistics and Communication Science, 6(2), 166–199. https://doi.org/10.1558/jrds.189. ↗
  91. Van der Leek, F. (1996). The English conative construction. In L. M. Dobrin, K. Singer, & L. McNair (Eds.), CLS 32: The main session (pp. 363–378). Chicago Linguistic Society. find
  92. Vincent, N. (2013). Conative. Linguistic Typology, 17(2), 269–289. https://doi.org/10.1515/lity-2013-0012. ↗
  93. Visser, F. (1963). An historical syntax of the English language. Brill. find
  94. Wickham, H. (2016). Ggplot2: Elegant graphics for data analysis (2nd ed.). Springer. https://doi.org/10.1007/ 978-3-319-24277-4 Winter, B. (2019). Statistics for linguists: An introduction using R. Routledge. ↗
  95. Witzlack-Makarevich, A., & Seržant, I. (2018). Differential argument marking: Patterns of variation. In I. Seržant & A. Witzlack-Makarevich (Eds.), Diachrony of differential argument marking (pp. 1–140). Language Science Press. https://doi.org/10.5281/zenodo.1228243. ↗
  96. Zehentner, E. (2019). Competition in language change: The rise of the English dative alternation. Mouton de Gruyter. https://doi.org/10.1515/9783110633856. ↗
  97. Zehentner, E. (2022). Ambiguity avoidance as a factor in the rise of the English dative alternation. Cognitive Linguistics, 33(1), 3–33. https://doi.org/10.1515/cog-2021-0018. ↗

Updated

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/papers/zehentner-2025-english-conative-alternation-between-complexity/