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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Yale University |
| Country | United States |
| Start Date | Sep 01, 2021 |
| End Date | Apr 30, 2025 |
| Duration | 1,337 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2116164 |
Human languages have many ways of describing things that do not, have not, or will not happen in the world. This area of language is called 'negation'. Languages across the world have different ways of describing these topics, and this area of language changes over time.
The concept is not explicitly taught (children are never explicitly instructed in how to talk about things that aren't there, or that don't happen), and being able to understand negation is critical to understanding what people say when they speak or sign. Yet even within a language, strategies for negation can vary extensively. This combination of basic, universal meaning and variation is what makes linguistics--the scientific study of language--such a powerful tool for investigating both the human mind and human society.
Language patterns can be investigated like archaeological sites, to uncover past aspects of human society, such as which groups have been in contact with one another. By exploring the limits of how languages vary, this project offers a window into the human mind.
This research project uses several methods to study language. The first involves detailed investigations of languages with prior documentation--that is, languages which already have some written information about them, such as corpora and reference grammars. The second involves work (in person and through video chat) with native speakers of indigenous languages, conducting experiments about precise meanings of words and phrases.
Methods include translation tasks, linguistic analysis of narratives, and eliciting descriptions of pictures. Thirdly, this project uses state of the art statistical methods in machine learning, data science, and computational phylogenetics, to discover and to understand the relationships between different languages. Through analyzing the systematic patterns inherent in language, it is possible to understand how languages change over time and why some meanings are stable while others are not.
This project provides training in quantitative methods to students, and involves teaching about language and society. It is planned that research findings will be published in academic journals and through public science outlets.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Yale University
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