Dative sickness: A phylogenetic analysis of argument structure evolution in Germanic

Abstract

A major argument against the feasibility of reconstructing syntax for proto-stages is the widely discussed lack of directionality of syntactic change. In a recent typology of changes in argument structure constructions based on Germanic (Barðdal 2015), several different, yet opposing, changes are reported. These include, among others, processes sometimes called dative sickness, nominative sickness, and accusative sickness. In order to tease apart the roles of the different processes, we have carried out a phylogenetic trait analysis on a predefined data set of twelve predicates found across the Germanic phyla using the MULTISTATE method. This is, as far as we are aware, the first application of the MULTISTATE method (Pagel et al. 2004) in historical syntax. The results clearly favor one of the models, the dative sickness model, over any other model, as this model is the only one that can accurately account for both the observed diversity of case frames and the independently proposed philological reconstructions. Methods of evolutionary trait analysis can be used to model evolutionary paths of argument structure constructions, and they provide the perfect testing ground for hypotheses arrived at through philological reconstruction, based on classical historical-comparative methods.*

Areal pressure in grammatical evolution

“…As automated ancestral state reconstruction gains increasing currency in historical linguistics, it has become common to evaluate the performance of ancestral state reconstruction against comparative reconstructions carried out by one or more experts (Dunn et al 2017;Jäger & List forthcoming). Given the long history of scholarship on Indo-European morphosyntax, as well as the frequently opposing views found in the literature, a full appraisal along these lines is beyond the scope of this paper; we set this evaluation aside for future work.…”

Modeling linguistic evolution: a look under the hood

“…Recent work by Widmer et al (2017) uses stochastic character mapping over a tree sample of Indo-European languages to demonstrate that at least one strategy of NP recursion was available over the course of Indo-European prehistory, according to their evolutionary model; ancestral state reconstruction is a crucial ingredient in this analysis. Dunn et al (2017) investigate the evolution of morphological case-marking on the subjects of a large number of verbs in Germanic languages; verbs in many Germanic languages co-occur with morphologically dative and accusative as well as nominative subjects. The study, based on a large amount of carefully curated data, is the first in linguistics to make use of (Pagel 1999) MULTISTATE methodology.…”

“…However, the degree to which ancestral state reconstruction agrees with a philological reconstruction should have no bearing on model selection. This accuracy no way serves as independent evidence in favor of the dative sickness model, as Dunn et al (2017) seem to imply; the authors have built their a priori assumptions regarding directionality of change in case assignment into the CTM model they use. When we look at reconstructions made by the unconstrained model (p. e15), we see that N subjects are erroneously reconstructed with high probability for a number of verbs, but for the dative sickness model, N subjects are reconstructed with zero probability; this appears to account for a large part of the model's accuracy, as assessed by the authors.…”

Investigating diachronic trends in phonological inventories using BDPROTO

“…Word lists that are coded for cognacy and phonetic similarity scores can be used as input for one of many algorithms that generate language family phylogenies. These language family trees can then be used as input to phylogenetic comparative methods that were developed by biologists for investigating the tree of life, which have now been adopted and adapted by linguists and evolutionary anthropologists to address research questions about ancient language structures, cultures, and population movements (e.g., Dediu 2010;Dunn et al 2011Dunn et al , 2017Verkerk 2015;Zhou and Bowern 2015).…”