The English progressive
Alina Ladygina and Igor Yanovich trace fine-grained temporal trajectories of the rise of the English progressive, as in “The girl is reading the book”. That construction is known to have risen significantly in prominence during the 19th century, but nobody systematically studied its rise on the level of individual words. Using a much larger dataset than in the preceding literature, Ladygina and Yanovich find that verbs have radically different histories with regard to the progressive. Their different trajectories cannot be explained by obvious linguistic features of those verbs, but at the same time are directional for most words. This raises important evolutionary questions: the differentiation suggests drift, but the directionality suggests systematic force.
The spatial distributions of linguistic dialects
Dialectal data mostly come in categorical form. In order to study the spatial distributions of linguistic dialects, student assistant Mei-Shin Wu and long-term DFG Center fellow Igor Yanovich developed a simple extension of familiar Moran’s I measure and corresponding correlogram for categorical data. They currently investigate whether taking into account population density leads to a more adequate notion of distance in spatial analyses.
Language phylogenetic inference and temporal predictions
Igor Yanovich investigates the robustness of the temporal predictions resulting from state-of-the-art phylogenetic inference methods for language families. In order to estimate the time of language origins and divergence in the absence of independent knowledge about linguistic rates of change, one needs to specify calibration points. The timing of particular language splits is used by algorithms to estimate actual rates of change. Naturally, calibrations based on historical events are much easier to obtain than prehistoric calibrations, but are historical time calibrations enough? Yanovich finds that they often are not. In phylogenetic analyses, temporal estimates for the root of the tree can shift significantly when one adds just one or two high-probability constraints based on archaeological and historical linguistic sources. For example, these estimates can differ on the order of a thousand years for Indo-European. This underscores that only by combining multiple lines of evidence from different sciences of human (pre)history can one obtain meaningful predictions about the past.
Evolutionary game theory framework for understanding language change
Igor Yanovich extends Ashwini Deo’s recently proposed evolutionary-game-theoretic framework for the analysis of cross-linguistically robust progressive-to-imperfective cycle of language change. The original framework by Deo adopts the infinite population assumption, which simplifies the analysis. However, Yanovich shows that in the infinite-population model, some important features of the cycle cannot be reproduced, while a finite-population model fares much better, though analytically it is harder to work with. With his modification of Deo’s model, Yanovich obtains novel empirical predictions about the relative length and stability of different stages of the progressive-to-imperfective cycle that allow for empirical testing.