Found 4290 Hypotheses across 429 Pages (0.006 seconds)
  1. Grammatical features of language tend to change at a slower rate than basic vocabulary.Greenhill, Simon J. - Evolutionary dynamics of language systems, 2017 - 2 Variables

    How do subsystems of language evolve over time? It is commonly assumed that grammatical changes of language are slower than vocabulary changes. Using a Dirichlet process mixture model to analyze rates of language evolution in 81 Austronesian languages, the authors find that to the contrary, the grammatical features of language tend to change at a faster rate than basic vocabulary. Furthermore, their results show that grammatical features have higher rates of homoplasy, more frequent contact-induced change, and less deliberate differentiation than basic vocabulary.

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  2. Grammatical features have higher rates of homoplasy than basic vocabulary.Greenhill, Simon J. - Evolutionary dynamics of language systems, 2017 - 2 Variables

    How do subsystems of language evolve over time? It is commonly assumed that grammatical changes of language are slower than vocabulary changes. Using a Dirichlet process mixture model to analyze rates of language evolution in 81 Austronesian languages, the authors find that to the contrary, the grammatical features of language tend to change at a faster rate than basic vocabulary. Furthermore, their results show that grammatical features have higher rates of homoplasy, more frequent contact-induced change, and less deliberate differentiation than basic vocabulary.

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  3. Languages with a smaller number of speakers had higher rates of loss of lexemes from basic vocabulary than did their larger sister languages (2100).Bromham, Lindell - Rate of language evolution is affected by population size, 2012 - 2 Variables

    Population size is generally assumed to play a pivotal role in the evolution of languages and cultures, but the expected patterns and potential mechanisms of change are unsettled. Theoretical models are limited by this uncertainty because they require making prior assumptions about language evolution. Using a sample of 20 Polynesian languages, authors test the effect of population size on the gain, loss, and total change of basic vocabulary words.

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  4. Total rate of change (word gain plus word loss) is related to population size.Bromham, Lindell - Rate of language evolution is affected by population size, 2012 - 2 Variables

    Population size is generally assumed to play a pivotal role in the evolution of languages and cultures, but the expected patterns and potential mechanisms of change are unsettled. Theoretical models are limited by this uncertainty because they require making prior assumptions about language evolution. Using a sample of 20 Polynesian languages, authors test the effect of population size on the gain, loss, and total change of basic vocabulary words.

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  5. Languages with larger speaker populations had higher rates of gain of new words than did their smaller sister languages (2100).Bromham, Lindell - Rate of language evolution is affected by population size, 2012 - 2 Variables

    Population size is generally assumed to play a pivotal role in the evolution of languages and cultures, but the expected patterns and potential mechanisms of change are unsettled. Theoretical models are limited by this uncertainty because they require making prior assumptions about language evolution. Using a sample of 20 Polynesian languages, authors test the effect of population size on the gain, loss, and total change of basic vocabulary words.

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  6. There is a trade-off of complexity between nominal and verbal domains across languages in a global scale.Shcherbakova, Olena - A quantitative global test of the complexity trade-off hypothesis: the case ..., 2023 - 2 Variables

    The "equi-complexity hypothesis" suggests that there is an equal complexity across languages, meaning that there are constant trade-offs between different domains. Using phylogenetic modelling in a sample of 244 languages, this study follows a diachronic perspective to explore if there is an inversed coevolution within the grammatical coding of nominal and verbal domains. The results show that while there appears to be a coevolutionary relationship between some features of these two domains, there is no evidence to support the idea that all languages maintain an overall equilibrium of grammatical complexity. Rather, the correlation nominal and verbal domains vary between lineages. Austronesian languages do not show a coevolution between the domains. Sino-Tibetan languages seem to have a positive correlation while Indo-European languages appear to have a negative correlation, meaning that this inverse coevolution can be lineage specific.

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  7. The number of language speakers will predict the rate of word change in a language.Greenhill, Simon J. - Population Size and the Rate of Language Evolution: A Test Across Indo-Europ..., 2018 - 2 Variables

    How is the evolution of language shaped by speaker population size? Through comparative data analyses of 153 language pairs from the Austronesian, Indo-European, and Niger-Congo language families, the authors find that the influence of population size on language evolution is not the same in the three language families. Only in Indo-European languages did a smaller population size of language-speakers significantly predict more word loss.

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  8. Grammatical complexity is predicted by language phylogeny and spatial contiguity.Shcherbakova, Olena - Societies of strangers do not speak less complex languages, 2023 - 3 Variables

    Is grammatical complexity shaped by sociodemographic and sociolinguistic factors? The previously accepted "linguistic niche hypothesis" claims that with an increased number of nonnative speakers in a social group (high exotericity), grammatic complexity decreases; on the other hand, grammatical complexity increases amongst isolated linguistic communities (low exotericity). Through the use of spatiophylogenetic modelling of 1314 languages, the authors of this study do not find adequate evidence to support the linguistic niche hypothesis. Instead, they suggest that linguistic complexity is better predicted by phylogeny and geographic contiguity.

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  9. Grammatical complexity of a language is predicted by the proportion of nonnative speakers.Shcherbakova, Olena - Societies of strangers do not speak less complex languages, 2023 - 5 Variables

    Is grammatical complexity shaped by sociodemographic and sociolinguistic factors? The previously accepted "linguistic niche hypothesis" claims that with an increased number of nonnative speakers in a social group (high exotericity), grammatic complexity decreases; on the other hand, grammatical complexity increases amongst isolated linguistic communities (low exotericity). Through the use of spatiophylogenetic modelling of 1314 languages, the authors of this study do not find adequate evidence to support the linguistic niche hypothesis. Instead, they suggest that linguistic complexity is better predicted by phylogeny and geographic contiguity.

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  10. Geographic proximity is positively correlated with similarity in emotion semantics across language families (1519).Jackson, Joshua Conrad - Emotion semantics show both cultural variation and universal structure, 2019 - 2 Variables

    Researchers looked at the meaning of various emotion concepts, 'emotion semantics' in an attempt to determine the patterns and processes behind meaning cross-culturally. They used maps of colexification patterns (where semantically related concepts are named with the same word), adjusted Rand indices (ARIs) which indicated the similarities of two community's network structures, and various psychophysiological dimensions to test relationships and patterns of variability /structure in emotion semantics. These methods shed light on the underlying mechanisms behind emotions, both their words and their meanings in languages across the world. Their findings show substantial difference in language families and relationships between geographic proximity of language families and subsequent variation in emotion colexification tied to an evolutionary relationship, while also finding cultural universals in emotion colexification networks with languages primarily differentiating emotions on the basis of valence and activation.

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