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.

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.

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.

In this paper we outline two debates about the nature of human cultural history. The first focuses on the extent to which human history is treelike (its shape), and the second on 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 consists 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 phylogenies, 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 treelike in different parts of the world and to evaluate the coherence of cultural and linguistic lineages.

Phylogenetic comparative methods (PCMs) provide a potentially powerful toolkit for testing hypotheses about cultural evolution. Here we build on previous simulation work by Nunn et al. (2006) to assess the effect horizontal transmission between cultures has on the ability of both phylogenetic and non-phylogenetic methods to make inferences about trait evolution.

We found that the mode of horizontal transmission of traits has important consequences for both methods. Where traits were horizontally transmitted separately PCMs accurately reported when trait evolution was not correlated even at the highest levels of horizontal transmission.

In contrast, linear regression analyses often incorrectly concluded that traits were correlated. Where simulated trait evolution was not correlated and traits were horizontally transmitted as a pair both methods showed increased levels of positive correlation with increasing horizontal transmission.

Where simulated trait evolution was correlated increasing rates of separate horizontal transmission led to decreasing levels of correlation for both methods, but that increasing rates of paired horizontal transmission did not. Furthermore, the PCM was also able to make accurate inferences about the ancestral state of traits.

These results suggest that under certain conditions PCMs can be robust to the effects of horizontal transmission. We discuss ways that future work can investigate the mode and tempo of horizontal transmission of cultural traits.

There are approximately 7000 languages spoken in the world today. This diversity reflects the legacy of thousands of years of cultural evolution. How far back we can trace this history depends largely on the rate at which the different components of language evolve. Rates of lexical evolution are widely thought to impose an upper limit of 6-10 thousand years on reliably identifying language relationships. In contrast, it has been argued that certain structural elements of language are much more stable. Just as biologists use highly conserved genes to uncover the deepest branches in the tree of life, highly stable linguistic features hold the promise of identifying deep relationships between the world’s languages.
Here we present the first global network of languages based on this typological information. We evaluate the relative evolutionary rates of both typological and lexical features in the Austronesian and Indo-European language families. The first indications are that typological features evolve at similar rates to basic vocabulary but their evolution is substantially less treelike. Our results suggest that, whilst rates of vocabulary change are correlated between the two language families, the rates of evolution of typological features and structural sub-types show no consistent relationship across families.

You can download a preprint of this paper here.

A network showing the relationships between 99 languages across the world. This network is built from structural information about language properties (phonology, morphology, grammar and lexicon). The length of the branches is proportional to the amount of divergence between the languages, and the box-like structures on the network show conflicting signal due to borrowing between languages and chance similarity.

We recently used computational phylogenetic methods on lexical data to test between two scenarios for the peopling of the Pacific. Our analyses of lexical data supported a pulse-pause scenario of Pacific settlement in which the Austronesian speakers originated in Taiwan around 5,200 years ago and rapidly spread through the Pacific in a series of expansion pulses and settlement pauses. We claimed that there was high congruence between traditional language subgroups and those observed in the language phylogenies, and that the estimated age of the Austronesian expansion at 5,200 years ago was consistent with the archaeological evidence. However, the congruence between the language phylogenies and the evidence from historical linguistics was not quantitatively assessed using tree comparison metrics. The robustness of the divergence time estimates to different calibration points was also not investigated exhaustively. Here we address these limitations by using a systematic tree comparison metric to calculate the similarity between the Bayesian phylogenetic trees and the subgroups proposed by historical linguistics, and by re-estimating the age of the Austronesian expansion using only the most robust calibrations. The results show that the Austronesian language phylogenies are highly congruent with the traditional subgroupings, and the date estimates are robust even when calculated using a restricted set of historical calibrations.