We claim that making sense of the typological diversity of languages demands a historical/evolutionary approach. We are pleased that the target paper (Dunn et al. 2011a) has served to bring discussion of this claim into prominence, and are grateful that leading typologists have taken the time to respond (commentaries denoted by boldface). It is unfortunate though that a number of the commentaries in this special issue show significant misunderstandings of our paper.
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In the following section we try to explain the basic underlying reasoning, turning in the remaining sections to some of these recurrent points of contention. In the final section, we collect some responses to points made in individual commentaries that did not fit neatly into the body of our response.

Simon J. Greenhill and Russell D. Gray.

The shape and the fabric of human cultural history is the focus of two long-standing debates in linguistics and anthropology. The first concerns the extent to which human history is tree-like (its shape), and the second concerns the unity of that history (its fabric). Proponents of cultural phylogenetics are often accused of assuming that human history has been both highly tree-like and consisting of tightly linked lineages. Critics have pointed out obvious exceptions to these assumptions. Instead of a priori dichotomous disputes about the validity of cultural phylogenetics, we suggest that the debate is better conceptualized as involving positions along continuous dimensions. The challenge for empirical research is, therefore, to determine where particular aspects of culture lie on these dimensions. We discuss the ability of current computational methods derived from evolutionary biology to address these questions. These methods are then used to compare the extent to which lexical evolution is tree-like in different parts of the world and to evaluate the coherence of cultural and linguistic lineages.

The Polynesian lexicon project, POLLEX, was initiated in 1965 by Bruce Biggs in order to provide a large-scale comparative dictionary of Polynesian languages. Since then, POLLEX has grown to include over 55,000 reflexes of more than 4,700 reconstructed forms in 68 languages. These data have enabled many fundamental advances in Polynesian linguistics and prehistory. At almost half a century old, POLLEX is one of the longest-standing databases of linguistic information, and has moved through various incarnations, from type- writer and edge-punched cards, through microfiche to mainframe computer. In the last few years, online databases of linguistic information have become increasingly more prevalent, representing a major shift in the way linguistics is conducted. Online databases provide many advantages over the older forms of data distribution, including high availability, more robust data storage, and easy data manipulation and searching, and they also facilitate the replication of previous studies. This paper announces the latest reincarnation of the POLLEX database as an online resource, POLLEX-Online (http://pollex.org.nz), and describes the technical implementation details.

The Levenshtein distance is a simple distance metric derived from the number of edit operations needed to transform one string into another. This metric has received recent attention as a means of automatically classifying languages into genealogical subgroups. In this paper I test the performance of the Levenshtein distance for classifying languages by subsampling three language subsets from a large database of Austronesian languages. Comparing the classification proposed by the Levenshtein distance to that of the comparative method shows that the Levenshtein classification is correct only 40% of time. Standardising the orthography increases the performance, but only to a maximum of 65% accuracy within language subgroups. The accuracy of the Levenshtein classification decreases rapidly with phylogenetic distance, failing to discriminate homology and chance similarity across distantly related languages. This poor performance suggests the need for more linguistically nuanced methods for automated language classification tasks.

The Abstract:

Languages vary widely but not without limit. The central goal of linguistics is to describe the diversity of human languages and explain the constraints on that diversity. Generative linguists following Chomsky have claimed that linguistic diversity must be constrained by innate parameters that are set as a child learns a language. In contrast, other linguists following Greenberg have claimed that there are statistical tendencies for co-occurrence of traits reflecting universal systems biases, rather than absolute constraints or parametric variation. Here we use computational phylogenetic methods to address the nature of constraints on linguistic diversity in an evolutionary framework. First, contrary to the generative account of parameter setting, we show that the evolution of only a few word-order features of languages are strongly correlated. Second, contrary to the Greenbergian generalizations, we show that most observed functional dependencies between traits are lineage-specific rather than universal tendencies. These findings support the view that—at least with respect to word order—cultural evolution is the primary factor that determines linguistic structure, with the current state of a linguistic system shaping and constraining future states.

The last few years have seen a wave of new computational phylogenetic approaches entering historical linguistics. The application of these computational methods to linguistics is perhaps “one of the most vibrant contemporary streams of comparative linguistics”. Whilst linguistics is not unfamiliar with computational methods, these new methods go far beyond the simplistic and flawed analyses of lexicostatistics or glottochronology. The new approaches have great potential for illuminating long-standing questions about language subgrouping and human prehistory, for exploring how different aspects of languages change and evolve over time, and for investigating the co-evolution of language structures. In this talk I will discuss some of my recent work on these issues.

Historical inference is at its most powerful when independent lines of evidence can be integrated into a coherent account. Dating linguistic and cultural lineages can potentially play a vital role in the inte- gration of evidence from linguistics, anthropology, archaeology and genetics. Unfortunately, although the comparative method in historical linguistics can provide a relative chronology, it cannot provide absolute date estimates and an alternative approach, called glottochronology, is fundamentally flawed. In this paper we outline how computational phylogenetic methods can reliably estimate language divergence dates and thus help resolve long-standing debates about human prehistory ranging from the origin of the Indo-European language family to the peopling of the Pacific.

There is disagreement about whether human political evolution has proceeded through a sequence of incremental increases in complexity, or whether larger, non-sequential increases have occurred. The extent to which societies have decreased in complexity is also unclear. These debates have continued largely in the absence of rigorous, quantitative tests. We evaluated six competing models of political evolution in Austronesian-speaking societies using phylogenetic methods. Here we show that in the best-fitting model political complexity rises and falls in a sequence of small steps. This is closely followed by another model in which increases are sequential but decreases can be either sequential or in bigger drops.

The results indicate that large, non-sequential jumps in political complexity have not occurred during the evolutionary history of these societies. This suggests that, despite the numerous contingent pathways of human history, there are regularities in cultural evolution that can be detected using computational phylogenetic methods.