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Adaptive Communication: Languages with More Non-Native Speakers Tend to Have Fewer Word Forms.

Bentz C, Verkerk A, Kiela D, Hill F, Buttery P - PLoS ONE (2015)

Bottom Line: We consider the effect of language contact-the number of non-native speakers a language has-on the way languages change and evolve.By analysing hundreds of languages within and across language families, regions, and text types, we show that languages with greater levels of contact typically employ fewer word forms to encode the same information content (a property we refer to as lexical diversity).Language evolution and change should be modeled as the co-evolution of multiple intertwined adaptive systems: On one hand, the structure of human societies and human learning capabilities, and on the other, the structure of language.

View Article: PubMed Central - PubMed

Affiliation: Department of Theoretical and Applied Linguistics, University of Cambridge, Cambridge, United Kingdom.

ABSTRACT
Explaining the diversity of languages across the world is one of the central aims of typological, historical, and evolutionary linguistics. We consider the effect of language contact-the number of non-native speakers a language has-on the way languages change and evolve. By analysing hundreds of languages within and across language families, regions, and text types, we show that languages with greater levels of contact typically employ fewer word forms to encode the same information content (a property we refer to as lexical diversity). Based on three types of statistical analyses, we demonstrate that this variance can in part be explained by the impact of non-native speakers on information encoding strategies. Finally, we argue that languages are information encoding systems shaped by the varying needs of their speakers. Language evolution and change should be modeled as the co-evolution of multiple intertwined adaptive systems: On one hand, the structure of human societies and human learning capabilities, and on the other, the structure of language.

No MeSH data available.


Related in: MedlinePlus

Regression plots by families.Scatterplots of log-transformed ratios of L2 speakers versus LDTs facetted by language families. Colored lines represent linear models by families with 95% confidence intervals. Languages of families with less than 10 data points are subsumed under “Other”. Note that this is just done for plotting, for statistical modeling language families are not collapsed.
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pone.0128254.g007: Regression plots by families.Scatterplots of log-transformed ratios of L2 speakers versus LDTs facetted by language families. Colored lines represent linear models by families with 95% confidence intervals. Languages of families with less than 10 data points are subsumed under “Other”. Note that this is just done for plotting, for statistical modeling language families are not collapsed.

Mentions: A visual way of establishing the significant result is to plot the relationship between log(RatioL2) and LDT for different families (Fig 7), different regions (Fig 8), different LDT measures (Fig 9) and different text types (Fig 10). These plots illustrate that the negative relationship holds for most families and regions, and for all three LDT measures as well as text types.


Adaptive Communication: Languages with More Non-Native Speakers Tend to Have Fewer Word Forms.

Bentz C, Verkerk A, Kiela D, Hill F, Buttery P - PLoS ONE (2015)

Regression plots by families.Scatterplots of log-transformed ratios of L2 speakers versus LDTs facetted by language families. Colored lines represent linear models by families with 95% confidence intervals. Languages of families with less than 10 data points are subsumed under “Other”. Note that this is just done for plotting, for statistical modeling language families are not collapsed.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4470635&req=5

pone.0128254.g007: Regression plots by families.Scatterplots of log-transformed ratios of L2 speakers versus LDTs facetted by language families. Colored lines represent linear models by families with 95% confidence intervals. Languages of families with less than 10 data points are subsumed under “Other”. Note that this is just done for plotting, for statistical modeling language families are not collapsed.
Mentions: A visual way of establishing the significant result is to plot the relationship between log(RatioL2) and LDT for different families (Fig 7), different regions (Fig 8), different LDT measures (Fig 9) and different text types (Fig 10). These plots illustrate that the negative relationship holds for most families and regions, and for all three LDT measures as well as text types.

Bottom Line: We consider the effect of language contact-the number of non-native speakers a language has-on the way languages change and evolve.By analysing hundreds of languages within and across language families, regions, and text types, we show that languages with greater levels of contact typically employ fewer word forms to encode the same information content (a property we refer to as lexical diversity).Language evolution and change should be modeled as the co-evolution of multiple intertwined adaptive systems: On one hand, the structure of human societies and human learning capabilities, and on the other, the structure of language.

View Article: PubMed Central - PubMed

Affiliation: Department of Theoretical and Applied Linguistics, University of Cambridge, Cambridge, United Kingdom.

ABSTRACT
Explaining the diversity of languages across the world is one of the central aims of typological, historical, and evolutionary linguistics. We consider the effect of language contact-the number of non-native speakers a language has-on the way languages change and evolve. By analysing hundreds of languages within and across language families, regions, and text types, we show that languages with greater levels of contact typically employ fewer word forms to encode the same information content (a property we refer to as lexical diversity). Based on three types of statistical analyses, we demonstrate that this variance can in part be explained by the impact of non-native speakers on information encoding strategies. Finally, we argue that languages are information encoding systems shaped by the varying needs of their speakers. Language evolution and change should be modeled as the co-evolution of multiple intertwined adaptive systems: On one hand, the structure of human societies and human learning capabilities, and on the other, the structure of language.

No MeSH data available.


Related in: MedlinePlus