Vernacular Language Use and Social Networking in an EastsideDetroit Neighborhood
{'Code': '04040500', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}
{'SignBlockName': 'Paul G. Chapin', 'PO_EMAI': None, 'PO_PHON': None}
Abstract Narrative                                                                                                                                                   Sociolinguistic research of the past two decades has                       established, in a rigorous quantitative way, numerous patterns of               socially conditioned linguistic variation among individual                      speakers, and between identifiable dialect communities.  Still                  open to question, however, is a comprehensive theoretical                       explanation of this phenomenon.  The aim of the project proposed                here is to move in the direction of such an explanation, in the                 context of a study of Black English Vernacular (BEV) in an urban                setting (Detroit).                                                                                                                                                   Social Network Theory (SNT) is the framework which will be                 used.  This theory seeks causal social variables not in the                     standard social categorizations such as age, education, and                     socioeconomic level, but rather in the depth and breadth of                     individuals' attachments to and involvement in their local                      communities.  These are explored by tracing out the networks of                 their relationships with others.  SNT will be supplemented in the               present project by the development of a Vernacular Culture Index,               which assesses the individual attitudes toward the community.                   The investigator will examine a number of linguistic variables                  known to be salient as markers of BEV as a distinct dialect of                  English, and correlate the incidence of them with the speakers'                 profiles according to the SNT.  Some pilot work has indicated                   that SNT scores are highly predictive of the incidence of these                 variables.  If the full study bears this out, it will be a                      significant contribution to our understanding of the dynamics of                linguistic variation and change.                                                                                                                                     The Principal Investigator is an experienced and accom-                    plished sociolinguist.  As a member of the minority community                   himself, he has a particular advantage in gaining access to the                 BEV speakers who will participate in the project.  The pilot work               he has already carried out helps assure confidence that the                     project can and will lead to successful results.
{'FirstName': 'Walter', 'LastName': 'Edwards', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Walter F Edwards', 'EmailAddress': 'aa5842@wayne.edu', 'NSF_ID': '000318377', 'StartDate': '09/01/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'Wayne State University', 'CityName': 'DETROIT', 'ZipCode': '482023692', 'PhoneNumber': '3135772424', 'StreetAddress': '5700 CASS AVE STE 4900', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'MI13', 'ORG_UEI_NUM': 'M6K6NTJ2MNE5', 'ORG_LGL_BUS_NAME': 'WAYNE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}
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[{'Code': '1185', 'Text': 'SENSORY SYSTEMS'}, {'Code': '1190', 'Text': 'DEVELOPMENTAL NEUROSCIENCE'}, {'Code': '1191', 'Text': 'BEHAVIORAL NEUROSCIENCE'}, {'Code': '1311', 'Text': 'Linguistics'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8712232.xml'}