Volume 45, Issue 3-4 - Current Work on Historical Linguistics Target Articles: Anne Breitbarth, Ailís Cournane, Gerhard Jäger, George Walkden, Issue Editor: Hans-Martin Gärtner

Acquisition is an intuitive place to look for explanation in language change. Each child must learn their individual grammar(s) via the indirect process of analyzing the output of others’ grammars, and the process necessarily involves social transmission over several years. On the basis of child language learning behaviors, I ask whether it is reasonable to expect the incrementation (advancement) of new variants to be kicked off by and sustained by the acquisition process. I discuss literature on how children respond to input variation, and a series of new studies experimentally testing incrementation, and argue that at least for some phenomena, young children overgeneralize innovative variants beyond their input. I sketch a model of incrementation based on initial overgeneralization, and offer further thoughts on next steps. Much collaborative work remains to precisely link analogous dynamic phenomena in learning and change.

Computational approaches to historical linguistics have been proposed for half a century. Within the last decade, this line of research has received a major boost, owing both to the transfer of ideas and software from computational biology and to the release of several large electronic data resources suitable for systematic comparative work. In this article, some of the central research topics of this new wave of computational historical linguistics are introduced and discussed. These are automatic assessment of genetic relatedness , automatic cognate detection , phylogenetic inference and ancestral state reconstruction . They will be demonstrated by means of a case study of automatically reconstructing a Proto-Romance word list from lexical data of 50 modern Romance languages and dialects. The results illustrate both the strengths and the weaknesses of the current state of the art of automating the comparative method.

Recent work has cast doubt on the idea that all languages are equally complex; however, the notion of syntactic complexity remains underexplored. Taking complexity to equate to difficulty of acquisition for late L2 acquirers, we propose an operationalization of syntactic complexity in terms of uninterpretable features. Trudgill’s sociolinguistic typology predicts that sociohistorical situations involving substantial late L2 acquisition should be conducive to simplification, i.e. loss of such features. We sketch a programme for investigating this prediction. In particular, we suggest that the loss of bipartite negation in the history of Low German and other languages indicates that it may be on the right track.

In this paper, I discuss differences between representational change (i. e. in formal features and structures involved in grammatical competence) and change in quantitative patterns (i. e. in the quantitative properties of the language system in use), as relevant to my approach to incrementation. My approach differs from the standard variationist sociolinguistic approach because I argue that representational Language processing differences between children and adults could also contribute, but I set these aside here. Note that Biberaurer (this volume) also considers these relevant factors to the role of children in change. input-divergence Input-divergence (Cournane 2017) is used very broadly, as a way to capture any child language properties that deviate from the input model the child learns from. This includes what we standardly call child “errors”, without using that term, which assumes that there is a fixed target when learning a language and interim analyses are wrong. Rather “errors” are only such in comparison to the input/intake grammars, so I opt to call these “input-divergent” properties. along the child learning path contributes to quantitative differences between children and older speakers, most importantly the input speakers. In this way, the Inverted U Model (IUM) for incrementation offers an initial sketch of a linking theory between (a) child developmental findings for competence-related changes over acquisitional time in the individual, and (b) the change-in-progress phenomenon of incrementation which describes how usage rates for innovative variants advance relative to conservative variants in speakers in the community over generational time. Maximize Minimal Means (MMM), this volume similarly attributes a principled, creative role in change to the child-learner, offering a linking theory between (a), and (c), discrete changes in representations between grammars in historical time, grounded in Minimalism. I’ll also respond to Westergaard’s (this volume) argument that the IUM’s reliance on child overgeneralization conflicts with a set of linguistic phenomena for which directional, child-driven changes have been proposed, namely syntactic changes characterized by economy or simplification. In syntax, relative to common language change pathways (e. g. biclausal>monoclausal reanalyses), children typically acquire the (potentially) innovative grammatical structure earlier than the conservative one as they develop complexity (e. g. they develop from monoclausal>biclausal ). It is indeed not clear how these child interim syntactic structures relate to overgeneralization, if at all. Rather, syntactic innovations are typically attributed to economy principles, and syntactic learning is sometimes characterized as conservative, also not obviously related to overgeneralization. I’ll show that neither economy in change nor child conservativity in syntactic development directly undermine the proposed model, as both are concerned with representational changes in grammars, not differences in quantitative patterns and changes-in-progress (the purview of incrementation and the IUM). Finally I will say a few words on the case study on Norwegian gender-system changes laid-out in Westergaard (this volume). These elicited production data are a valuable contribution to the roles of children in changes-in-progress, and while the data patterns conflict with some aspects of the IUM as proposed, the overall approach of Rodina and Westergaard is in line with a child-learning-centered contribution to the directionality and shape of changes-in-progress.

This is a reply to the comments by Hammarström et al. (This volume) and List (This volume) on the target article Computational Historical Linguistics (This volume). There I proposed several methodological principles for research in Computational Historical Linguistics pertaining to suitable techniques for model fitting and model evaluation. Hammarström et al. debate the usefulness of these principles, and List proposes a novel evaluation measure specifically aimed at the task of proto-form reconstruction. This reply will focus on the role of model evaluation in our field.