A Methodological Innovation in Creating Representative      Samples of Organizations
{'Code': '04050200', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}
{'SignBlockName': 'Shelton White', 'PO_EMAI': None, 'PO_PHON': None}
Attempts to generalize about organizations have been seriously                  hampered by the absense of an organization data base, or even a sampling        procedure, generally recognized as valid, by which a representative             sample of organizations could be selected.  One potentially promising           approach to this sampling problem entails selecting a representative            sample of individuals, and asking them in some other manner.  This              approach is promising because a great deal is known about how to conduct        sample surveys on populations of individuals.  However, there is no             known certainty that a representative sample of individuals will yield a        representative sample of organizations.   What is needed is some                independently generated distribution of organizations, believed to be           representative of the population of organizations, which can be used as         a criterion to assess the validity of the  individual - produced                distribution.  Such a criterion may be found in the files of the                Internal Revenue Service.  They may provide a comprehensive--and                potentially exhaustive -- listing of organizations against which an             individually - produced distribution of organiztions can be examined.           This study will examine an area that corresponds roughly with                   metropolitan Los Angeles.  A sample of nearly 1,000 individuals                 surveyed by telephone last Spring, produced information on over 1,000           voluntary and work organizations.  The frequency with which different           types of organizations appear in the tax-related records of the                 Internal Revenue Service will be compared to the distribution obtained          from the greater Los Angeles survey.  The significance of any observed          differences will be assessed using Chow tests.
{'FirstName': 'Lynne', 'LastName': 'Zucker', 'PI_MID_INIT': 'G', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lynne G Zucker', 'EmailAddress': 'lynne_zucker@nber.org', 'NSF_ID': '000298696', 'StartDate': '11/15/1987', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of California-Los Angeles', 'CityName': 'LOS ANGELES', 'ZipCode': '900244200', 'PhoneNumber': '3107940102', 'StreetAddress': '10889 WILSHIRE BLVD STE 700', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '36', 'CONGRESS_DISTRICT_ORG': 'CA36', 'ORG_UEI_NUM': 'RN64EPNH8JC6', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, LOS ANGELES', 'ORG_PRNT_UEI_NUM': None}
{'Name': None, 'CityName': None, 'StateCode': None, 'ZipCode': None, 'StreetAddress': None, 'CountryCode': None, 'CountryName': None, 'StateName': None, 'CountryFlag': None, 'CONGRESSDISTRICT': None, 'CONGRESS_DISTRICT_PERF': '""'}
[{'Code': '1331', 'Text': 'Sociology'}, {'Code': '9120', 'Text': 'CROSS-DIRECTORATE PROGRAMS'}]
{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=1987&All=true', 'xml': '8718474.xml'}