Tweet
The shape and tempo of language evolution
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 6000-10 000 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 tree-like. Our results suggest that, while rates of vocabulary change are correlated between the two language families, the rates of evolution of typological features and structural subtypes show no consistent relationship across families.
Figure 1: NeighbourNet for the 99 most well-attested languages in the WALS database. This network is based on 138 typological characters and shows the signals grouping languages. Branch-lengths are proportional to amount of divergence between languages and the box-like structures reflect conflicting signal. Accepted family groups are color-coded and potential language areas are marked with dashed lines and numbered as described in the text. The dashed area and arrows on the map show the extent of the large Eurasian cluster (1). Cluster 2 appears to be a residual grouping containing languages from Australia, Africa and the Pacific.
This is an extremely interesting paper which addresses the claim that typological features of languages (e.g., whether they use Subject-Verb-Object) are more conservative than the lexicon. If that is the case, then typological features could be used to infer evolutionary relationships between languages that are older than ten thousand years or so (an upper limit on what can be inferred using vocabulary).
In general, the authors reject the idea of typological conservation, although they note that typological features differ in this respect, and some of them may appear to be conservative within some language family but evolve rapidly in another. Their tree reconstruction is able to infer well-known language families (e.g., Indo-European), or suspected ones (e.g., Nostratic), but the corresponding clusters are not robust (e.g., Hindi is broken away from the IE cluster, and unrelated non-Eurasian languages fall into the Nostratic one).
Figure 2: NeighbourNets for each lexical and typological dataset. Colors represent accepted subgroups.
Source:
http://simon.net.nz/files/2010/04/Greenhill_et_al2010-preprint.pdf
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 6000-10 000 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 tree-like. Our results suggest that, while rates of vocabulary change are correlated between the two language families, the rates of evolution of typological features and structural subtypes show no consistent relationship across families.
Figure 1: NeighbourNet for the 99 most well-attested languages in the WALS database. This network is based on 138 typological characters and shows the signals grouping languages. Branch-lengths are proportional to amount of divergence between languages and the box-like structures reflect conflicting signal. Accepted family groups are color-coded and potential language areas are marked with dashed lines and numbered as described in the text. The dashed area and arrows on the map show the extent of the large Eurasian cluster (1). Cluster 2 appears to be a residual grouping containing languages from Australia, Africa and the Pacific.
This is an extremely interesting paper which addresses the claim that typological features of languages (e.g., whether they use Subject-Verb-Object) are more conservative than the lexicon. If that is the case, then typological features could be used to infer evolutionary relationships between languages that are older than ten thousand years or so (an upper limit on what can be inferred using vocabulary).
In general, the authors reject the idea of typological conservation, although they note that typological features differ in this respect, and some of them may appear to be conservative within some language family but evolve rapidly in another. Their tree reconstruction is able to infer well-known language families (e.g., Indo-European), or suspected ones (e.g., Nostratic), but the corresponding clusters are not robust (e.g., Hindi is broken away from the IE cluster, and unrelated non-Eurasian languages fall into the Nostratic one).
Figure 2: NeighbourNets for each lexical and typological dataset. Colors represent accepted subgroups.
Source:
http://simon.net.nz/files/2010/04/Greenhill_et_al2010-preprint.pdf
Comment