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Found 6 result(s)
The Polinsky Language Sciences Lab at Harvard University is a linguistics lab that examines questions of language structure and its effect on the ways in which people use and process language in real time. We engage in linguistic and interdisciplinary research projects ourselves; offer linguistic research capabilities for undergraduate and graduate students, faculty, and visitors; and build relationships with the linguistic communities in which we do our research. We are interested in a broad range of issues pertaining to syntax, interfaces, and cross-linguistic variation. We place a particular emphasis on novel experimental evidence that facilitates the construction of linguistic theory. We have a strong cross-linguistic focus, drawing upon English, Russian, Chinese, Korean, Mayan languages, Basque, Austronesian languages, languages of the Caucasus, and others. We believe that challenging existing theories with data from as broad a range of languages as possible is a crucial component of the successful development of linguistic theory. We investigate both fluent speakers and heritage speakers—those who grew up hearing or speaking a particular language but who are now more fluent in a different, societally dominant language. Heritage languages, a novel field of linguistic inquiry, are important because they provide new insights into processes of linguistic development and attrition in general, thus increasing our understanding of the human capacity to maintain and acquire language. Understanding language use and processing in real time and how children acquire language helps us improve language study and pedagogy, which in turn improves communication across the globe. Although our lab does not specialize in language acquisition, we have conducted some studies of acquisition of lesser-studied languages and heritage languages, with the purpose of comparing heritage speakers to adults.
ScienceBase provides access to aggregated information derived from many data and information domains, including feeds from existing data systems, metadata catalogs, and scientists contributing new and original content. ScienceBase architecture is designed to help science teams and data practitioners centralize their data and information resources to create a foundation needed for their work. ScienceBase, both original software and engineered components, is released as an open source project to promote involvement from the larger scientific programming community both inside and outside the USGS.
Repository for New Mexico Experimental Program to Stimulate Competitive Research Data Collection. Provides access to data generated by the Energize New Mexico project as well as data gathered in our previous project that focused on Climate Change Impacts (RII 3). NM EPSCoR contributes its data to the DataONE network as a member node: https://search.dataone.org/#profile/NMEPSCOR Digital Repository NM EPSCoR is part of UNM Digital Repository https://digitalrepository.unm.edu/ see also: https://data.nmepscor.org/
The National Data Archive on Child Abuse and Neglect (NDACAN) promotes scholarly exchange among researchers in the child maltreatment field. NDACAN acquires microdata from leading researchers and national data collection efforts and makes these datasets available to the research community for secondary analysis.